CN108304585A - A kind of result data choosing method and relevant apparatus based on spatial key search - Google Patents

Abstract

This application discloses a method for selecting result data based on spatial keyword search. First, the diversity of spatial text objects is measured by the number of diverse topics, and then the number of each candidate spatial text object is determined by the distance coefficient and the number of diverse topics. Boundary cost, select the candidate space text object with the smallest boundary cost to the result set, so that the distance between the object in the result set and the query object is relatively short and the number of diverse topics is kept at a high state, that is, while selecting based on the distance coefficient, each The diversity of individual search results improves the diversity of result sets and meets the diverse search needs of users. The application also discloses a device for selecting result data based on spatial keyword search, a server, and a computer-readable storage medium, which have the above-mentioned advantageous effects.

Description

A method and related device for selecting result data based on spatial keyword search

technical field

The present application relates to the field of computer technology, and in particular to a method for selecting result data based on spatial keyword search, a device for selecting result data, a server, and a computer-readable storage medium.

Background technique

With the emergence of location-based service technology, more and more applications associate real phenomena with spatial locations, resulting in widely used spatial keyword queries, that is, hybrid queries that combine spatial queries and text queries to seek optimal results.

Generally, spatial keyword query is divided into three steps, which are formally measuring spatial text objects and related data, establishing corresponding index structures for all spatial text objects, and querying through received query keywords. Among them, there is a unified measurement standard for the formal measurement of the spatial text object, and the corresponding spatial text object query can be performed efficiently through the measurement standard. Based on the above method, it is possible to perform further query operations on spatial keywords, and obtain query results related to the query keywords.

However, the current query methods for spatial keywords generally return query results, that is, the returned spatial text objects have a high degree of similarity with the query keywords, and there is no requirement for the relationship between the interest points in the result set, usually these are returned The points are very similar and cannot meet the diverse needs of users. For example, a user wants to search for nearby restaurants of as many categories as possible, so as to choose among different types of restaurants, but the search engine may only return nearby restaurants of the same type, which cannot help the user to make a choice.

Therefore, how to improve the diversity of search results through spatial keyword search and meet the diverse needs of users is a key issue that those skilled in the art are concerned about.

Contents of the invention

The purpose of this application is to provide a method for selecting result data based on spatial keyword search, a device for selecting result data, a server, and a computer-readable storage medium, and determine the boundary cost of each candidate space text object through the distance coefficient and the number of diverse topics , select the candidate space text object with the smallest boundary cost to the result set, so that the distance between the object in the result set and the query object is relatively short and the number of diverse topics is kept high, that is, each search is considered while selecting based on the distance coefficient The diversity of results improves the diversity of result sets and meets the diverse search needs of users.

In order to solve the above technical problems, the application provides a method for selecting result data based on spatial keyword search, including:

Execute the index structure building operation on multiple spatial text objects to obtain the index structure;

Selecting a plurality of candidate spatial text objects according to the obtained query object using the index structure to obtain a candidate set;

Determine the distance between each of the candidate spatial text objects and the query object, and obtain a distance coefficient between each of the candidate spatial text objects and the query object;

Determine the number of topics that each of the candidate spatial text objects includes in addition to all the topics initialized, and obtain the first diversity topic number of each of the candidate spatial text objects;

Determine the first boundary cost of each of the candidate space text objects according to all the distance coefficients and all the first diversity topics; wherein, the distance coefficient is directly proportional to the first boundary cost, so The number of the first diversity topics is inversely proportional to the first boundary cost;

Select the candidate space text object with the minimum cost of the first boundary and add it to the result set.

Optionally, also include:

When selecting the candidate space text object with the smallest boundary cost to add to the result set, it is determined that each of the candidate space text objects includes The number of topics, obtain the second diversity topic number of each of the candidate spatial text objects;

Determine the second boundary cost of the corresponding candidate space text object according to all the distance coefficients and all the second diversity topic numbers; wherein, the distance coefficient is directly proportional to the second boundary cost, so The number of the second diversity topics is inversely proportional to the second boundary cost;

Selecting the candidate space text object with the minimum second boundary cost and adding it to the result set.

Optionally, perform an index structure building operation on multiple spatial text objects to obtain an index structure, including:

determining the number of keyword occurrences for each of said spatial text objects;

Setting the space text object whose occurrence frequency of the keyword is less than the preset number of times as a block structure to obtain multiple block structures;

Setting the space text objects whose keyword occurrence times are greater than or equal to the preset times as a tree structure to obtain multiple tree structures;

All the block structures and all the tree structures are used as the index structures.

Optionally, using the index structure to select a plurality of candidate spatial text objects according to the obtained query object to obtain a candidate set, including:

According to the obtained query object, the index structure is used to select multiple candidate spatial text objects from all the spatial text objects according to a greedy algorithm to obtain the candidate set.

The present application also provides a device for selecting result data based on spatial keyword search, including:

An index building module is used to perform an index structure building operation on multiple spatial text objects to obtain an index structure;

The candidate set acquisition module is used to select a plurality of candidate spatial text objects according to the obtained query object using the index structure to obtain the candidate set;

A distance coefficient acquisition module, configured to determine the distance between each of the candidate spatial text objects and the query object, and obtain the distance coefficient between each of the candidate spatial text objects and the query object;

The first diversity topic number acquisition module is used to determine the number of topics included in each of the candidate space text objects in addition to all the topics initialized, and obtain the first diversity topic number of each of the candidate space text objects ;

The first boundary cost acquisition module is used to determine the first boundary cost of each of the candidate space text objects according to all the distance coefficients and all the first diversity topic numbers; wherein, the distance coefficient and the The first boundary cost is in a proportional relationship, and the number of the first diversity topics is inversely proportional to the first boundary cost;

The first result data selection module is used to select the candidate space text object with the smallest boundary cost and add it to the result set.

Optionally, also include:

The second diversity topic number acquisition module is used to determine each of the candidate space text objects at the minimum cost of the first boundary when selecting the candidate space text object with the minimum cost of the first boundary and adding it to the result set. After the candidate spatial text object is added, the number of topics included outside all topics is obtained to obtain the second diversity topic number of each of the candidate spatial text objects;

The second boundary cost acquisition module is used to determine the second boundary cost of the corresponding candidate space text object according to all the distance coefficients and all the second diversity topic numbers; wherein, the distance coefficient is the same as the The second boundary cost is in a proportional relationship, and the number of the second diversity topics is inversely proportional to the second boundary cost;

The second result data selection module is configured to select the candidate space text object with the minimum second boundary cost and add it to the result set.

Optionally, the index building module includes:

A keyword occurrence count acquisition unit, configured to determine the keyword occurrence count of each of the spatial text objects;

A block structure acquisition unit, configured to set the space text object whose occurrence times of the keyword is less than a preset number of times as a block structure to obtain multiple block structures;

A tree structure acquiring unit, configured to set the space text objects whose keyword occurrence times are greater than or equal to the preset number of times as a tree structure to obtain multiple tree structures;

The index structure acquisition unit is configured to use all the block structures and all the tree structures as the index structures.

Optionally, the candidate set acquisition module includes:

The candidate set acquisition unit is configured to select a plurality of candidate spatial text objects from all the spatial text objects according to the obtained query object using the index structure according to a greedy algorithm to obtain the candidate set.

The application also provides a server, including:

memory for storing computer programs;

A processor, configured to implement the above method for selecting result data when executing the computer program.

The present application also provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the above method for selecting result data is realized.

A method for selecting result data based on spatial keyword search provided by the present application includes: performing an index structure establishment operation on multiple spatial text objects to obtain an index structure; using the index structure to select multiple candidates according to the obtained query object Spatial text object, obtain candidate set; Determine the distance of each described candidate spatial text object and described query object, obtain the distance coefficient of each described candidate spatial text object and described query object; Determine each described candidate space The subject quantity that text object comprises outside all subjects of initialization, obtains the first diversity subject number of each described candidate space text object; Determine according to all described distance coefficients and all described first diversity subject numbers The first boundary cost of each of the candidate spatial text objects; wherein, the distance coefficient is in direct proportion to the first boundary cost, and the first diversity topic number is inversely proportional to the first boundary cost ; Select the candidate space text object with the minimum cost of the first boundary and add it to the result set.

It can be seen that the diversity of the metric space text object is realized by the number of diverse topics first, and then the boundary cost of each candidate space text object is determined by the distance coefficient and the number of diversity topics, and the candidate space text object with the smallest boundary cost is selected into the result set , so that the distance between the object in the result set and the query object is short and the number of diverse topics is kept high, that is, the diversity of each search result is considered while selecting based on the distance coefficient, and the diversity of the result set is improved to meet Diversified search needs of users.

The present application also provides a device for selecting result data based on spatial keyword search, a server, and a computer-readable storage medium, which have the above-mentioned beneficial effects, and will not be repeated here.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only It is an embodiment of the present application, and those skilled in the art can also obtain other drawings according to the provided drawings without creative work.

Fig. 1 is a flow chart of a method for selecting result data based on spatial keyword search provided by an embodiment of the present application;

Fig. 2 is a flow chart of the subsequent selection process of the result data selection method based on spatial keyword search provided by the embodiment of the present application;

Fig. 3 is the flow chart of index establishment of the result data selection method based on spatial keyword search provided by the embodiment of the present application;

FIG. 4 is a schematic structural diagram of an apparatus for selecting result data based on spatial keyword search provided by an embodiment of the present application.

Detailed ways

The core of this application is to provide a method for selecting result data based on spatial keyword search, a device for selecting result data, a server, and a computer-readable storage medium, and determine the boundary cost of each candidate spatial text object through the distance coefficient and the number of diverse topics , select the candidate space text object with the smallest boundary cost to the result set, so that the distance between the object in the result set and the query object is relatively short and the number of diverse topics is kept high, that is, each search is considered while selecting based on the distance coefficient The diversity of results improves the diversity of result sets and meets the diverse search needs of users.

In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

Please refer to FIG. 1 , which is a flow chart of a method for selecting result data based on spatial keyword search provided by an embodiment of the present application.

This embodiment provides a method for selecting result data based on spatial keyword search, which can improve the diversity of searches, and may include:

S101. Execute an index structure building operation on multiple spatial text objects to obtain an index structure;

This step aims to perform an index structure building operation on multiple spatial text objects to obtain corresponding index structures, that is, to build index structures for all spatial text objects. When performing corresponding queries according to the query conditions, an index structure must be established first to realize the search for spatial text objects. Specifically, the establishment method of the index structure is not limited here, as long as the establishment method that can realize the search for the spatial text object can be the establishment method used in this embodiment.

Furthermore, an appropriate index structure can be established according to different search environments and query characteristics, which is conducive to speeding up the search, simplifying the index structure, and reducing the cost of maintaining and updating the index structure.

Wherein, the spatial text object is obtained by formally expressing the searched spatial text data. The specific formalization process is explained in the following paragraphs.

S102, using an index structure to select a plurality of candidate spatial text objects according to the obtained query object to obtain a candidate set;

On the basis of step S101, this step aims to select and obtain multiple candidate spatial text objects according to the obtained index structure and query object, and obtain a candidate set. The purpose of this step is to select all spatial text objects through the query object, that is, to select the candidate spatial text object through the index result, the purpose is to make the candidate spatial text object conform to the restriction of the query object, so in this step through The query object selects multiple candidate spatial text objects and obtains a candidate set.

Among them, the query object is similar to the spatial text object in the previous step, and is obtained by formalizing the data, and the specific formalization process is explained in the following paragraphs.

S103, determine the distance between each candidate spatial text object and the query object, and obtain the distance coefficient between each candidate spatial text object and the query object;

On the basis of step S102, this step aims to determine the distance between each candidate spatial text object and the query object, and obtain the corresponding distance coefficient. The calculation method for determining the distance in this step can be the same as the general spatial distance calculation method, and its main purpose is to obtain the distance between the object and the query object in the space search, so that the subsequent query process can obtain the optimal distance through distance screening. search result.

Of course, the method for determining the distance in this step can also be changed according to the difference between the formalized expressions of the candidate spatial text object and the query object. The specific change form and method should be selected according to the actual application environment, and are not limited here.

S104, determine the number of topics included in each candidate space text object besides all the topics initialized, and obtain the first diversity topic number of each candidate space text object;

On the basis of step S102, this step aims to determine the number of topics included in each candidate spatial text object besides all the initialized topics, and obtain the first diversity topic number corresponding to the candidate spatial text object.

Because in the general spatial keyword search, the selection process only considers the distance between the candidate spatial text object and the query object, that is, the final result data is composed of the shortest candidate spatial text object with the query object, which will make the result data and the query object shortest. Query objects are very similar. However, the results obtained in this way cannot meet the diverse needs of users for the query process, that is, under a certain degree of similarity of the query objects, the query results are required to be as diverse as possible, that is to say, the result data includes keywords related to a certain keyword topic. Various types of points of interest.

Further, in this step, the number of diverse topics of a candidate spatial text object is determined by the number of topics included in the candidate spatial text object other than all the topics initialized. Among them, topic is an attribute shared by the candidate spatial text object and the query object, and it is also a general attribute used in spatial text search.

Among them, all the topics initialized are the topics included in all spatial text objects in the result set currently initialized. Further, the topic diversity of a candidate spatial text object can be measured by the number of topics outside the scope of all the topics. sex. Specifically, in actual use, the search result data can be selected according to the diversity topic number during the search process of the spatial text object, so as to increase the diversity of the search results so that the result data meet the diverse needs of users.

Therefore, the above result set is obtained by performing initialization processing in this embodiment, and the data added in the result set is obtained by continuously cyclically selecting data in the candidate set. If it is the first cycle at this time, then the result set obtained by the initialization process may not have a space text object, and there will be no corresponding subject range. The initialization process can also be to add a certain amount of result data to the result set through other search methods, and then add more spatial text objects through the method of this embodiment. At this time, the result set obtained by the initialization process also has a certain theme range, according to the topic range, the first diversity topic number of the candidate spatial text object can be determined.

It is conceivable that the initialization process in this embodiment can also be another spatial keyword search process, that is, this implementation can be applied after other spatial keyword search processes to improve the diversity of the spatial keyword search. sex. Further, other search methods may be used after the spatial keyword search process in this embodiment to select more suitable search results.

It should be noted that there is no sequence relationship between this step and step S103 in execution sequence.

S105, determine the first boundary cost of each candidate space text object according to all distance coefficients and all first diversity topics; wherein, the distance coefficient is directly proportional to the first boundary cost, and the first diversity topic number is related to the first - Boundary cost is an inverse relationship;

On the basis of steps S103 and S104, this step aims to determine the first boundary cost of the candidate spatial text object according to the obtained distance coefficient and the first number of diverse topics. That is, on the basis of the distance coefficient and the number of first diversity topics obtained in step S103 and step S104, the boundary cost is derived as a unified measurement method for measuring object similarity and diversity. And the distance coefficient is directly proportional to the first boundary cost, and the first diversity topic number is inversely proportional to the first boundary cost, that is, the smaller the boundary cost, the smaller the distance coefficient and the larger the first diversity topic number .

S106. Select the candidate space text object with the smallest first boundary cost and add it to the result set.

On the basis of step S105, this step aims to select the candidate space text object with the smallest first boundary cost and add it to the result set. That is, the candidate spatial text object with the best distance coefficient and first diversity topic number in the candidate set is selected as one of the result data, which improves the diversity of the result data and meets the diversity needs of users.

To sum up, in this embodiment, the boundary cost of each candidate spatial text object is determined by the distance coefficient and the number of diverse topics, and the candidate spatial text object with the smallest boundary cost is selected into the result set, so that the distance between the object in the result set and the query object is relatively short and The number of diverse topics is kept at a high level, that is, the diversity of each search result is considered while selecting based on the distance coefficient, so as to increase the diversity of the result set and meet the diverse search needs of users.

Optionally, in this embodiment, according to the obtained query object, multiple candidate spatial text objects may be selected from all spatial text objects using an index structure according to a greedy algorithm to obtain a candidate set.

The main purpose of this option is to select candidate spatial text objects from all spatial text objects to obtain a candidate set, in particular to select suitable candidate spatial text objects through a greedy algorithm. Mainly because the result data selection method based on the boundary cost in the above embodiment cannot guarantee that the diversity and distance of the result data meet certain requirements at the same time, so in order to improve the quality of the query results, this option uses a greedy algorithm to select multiple Candidate space text object to get the candidate set.

The core idea of this optional scheme is to stratify them into different layers according to the spatial distance between the spatial text objects and the query object, and then select a specific number of spatial text objects in each layer, so that the spatial text objects owned by these spatial text objects Covers more topics than other spatial text objects on the same layer.

Specifically, given a set of spatial objects D, for a spatial keyword query q, it is assumed that k spatial objects can be found on D that meet the diverse requirements at the same time, that is, cover enough topics and minimize the distance function, and they are far from the query The sum of the spatial distances of q is M. We assume that the value of M may be very small, so we can start searching from within a circular range with a small radius centered on the position of the query q. If the results found within this range cannot cover enough topics, then expand M in Search on a larger scale. For each circular search range, objects within the range are divided into different layers according to their distance from the query point, and then appropriate objects are selected in each layer.

Further, the greedy algorithm used in the alternative scheme can also be used for corresponding searches after obtaining the result data, that is, the result set obtained in this embodiment is re-screened by the greedy algorithm, which can improve the accuracy of the original result set. rate, even if the result set is closer to the query object.

Based on the above embodiments, the spatial text objects, query objects, etc. described therein can be formally expressed in the following forms.

1) Formal expression of spatial text objects

Use a point o={loc,term,topic} with location coordinates and text description in 2D space to represent a spatial text object. Among them, loc is composed of latitude and longitude, indicating the location of the object o; term is a set of keywords used to describe the object o; topic indicates the collection of topics covered by the object o.

For example, in a map application environment, a spatial keyword corresponds to a point of interest, that is, a business or institution, and the system records its location and text description. The topics covered by this point of interest can be marked manually or through natural language processing technology. Get it by analyzing its comment information. For convenience, a spatial text object may also be referred to as a spatial object.

Based on the above definition, we use D to represent the collection of all spatial text objects in the database, namely:

2) Formal expression of spatial keyword query

The spatial keyword query is formalized as q={loc, term}, and q is the query object. Among them, loc is the query point, that is, the location of the user, which is represented by latitude and longitude coordinates in two-dimensional space; term is a set of keywords entered by the user, such as "Chinese restaurant", which is used to describe the user's query intention.

For a given query object q, the search engine selects the k most similar spatial text objects that best match q from the data set D as the returned result data. Among them, the result data is a collection of a group of spatial text objects with close distance, high text correlation and high diversification among results.

3) Formal expression of the candidate set

Given a spatial text object database D, a spatial keyword query object q={loc, term} and a threshold Thre, a subset S of D (ie ) is called the candidate set. If and only if two conditions are met:

keyword restriction, each spatial text object o in S contains all query keywords, namely

Diversification requires that the sum of the number of different topics covered by all spatial text objects in S is not less than Thre, that is

4) Formal expression of the distance function of the spatial text object

Given a spatial text object database D, a spatial keyword query object q={loc,term}, for a subset of D whose number of elements is k We define the distance function between sets R and q as:

Where Dist(q,o) represents the distance between the spatial text object o and the query object q, and Dist _max represents the farthest distance between the spatial text object in the dataset D and the query object. As shown above, the distance between the query object and the spatial text object set is normalized, that is, the value is in the interval [0,1].

5) Formal definition of the search problem

Given a dataset D of spatial text objects, a spatial keyword query q = {loc, term}, a distance function f and a threshold Thre, consider the spatial distance between the spatial text object and the query query, the text threshold, and the topic coverage , intends to return k spatial text objects satisfying the following two similarity measurement conditions:

1. These k spatial text objects form a candidate set R, namely and

2. f(q, R) obtains the minimum value.

Please refer to FIG. 2 , which is a flow chart of the subsequent selection process of the method for selecting result data based on spatial keyword search provided by the embodiment of the present application.

Based on the previous embodiment, this embodiment is mainly aimed at an extended description of the candidate space text object with the smallest boundary cost in the previous embodiment after it is added to the result set. The foregoing part is substantially the same as the previous embodiment. Reference may be made to the previous embodiment, and details are not repeated here.

This embodiment can include:

S201, when selecting the candidate space text object with the minimum first boundary cost to add to the result set, determine the number of topics included in each candidate space text object after the addition of the candidate space text object with the minimum first boundary cost, Obtain the second diversity theme number of each candidate space text object;

This step aims to add the candidate spatial text object with the smallest boundary cost to the result set in the previous embodiment. At this time, it is equivalent to changing the spatial text object in the result set, that is, the subject range contained in the result set Corresponding changes have taken place. In order to continue to improve the diversity of candidate spatial text objects selected from the candidate set, it is necessary to determine the number of topics included in each candidate spatial text object after the candidate spatial text object with the smallest boundary cost is added. The number of topics, to get the number of topics in the second diversity.

Since the candidate space text data selected in the first embodiment is added to the result set, the subject range included in the corresponding result set has also changed, that is, the subject range of measurement has also changed, so the purpose of this step Mainly, the number of diversity topics of all candidate spatial text objects is recalculated on the basis of the second result set, that is, the second number of diversity topics.

S202. Determine the second boundary cost of the corresponding candidate space text object according to all distance coefficients and all second diversity topic numbers; wherein, the distance coefficient is directly proportional to the second boundary cost, and the second diversity topic number is related to the first The two boundary costs are inversely proportional;

On the basis of step S202, this step aims to determine the second boundary cost according to the distance coefficient and the second number of diverse topics in the previous embodiment. The specific content is substantially the same as that of the previous embodiment, and reference may be made to the embodiment of the upper garment, so details are not repeated here.

S203. Select the candidate space text object with the smallest second boundary cost and add it to the result set.

On the basis of step S202, this step aims to add the candidate space text object with the smallest second boundary cost to the result set.

Since the range of subjects included in each addition of result data in the spatial keyword search has a corresponding change, this embodiment aims to explain how to add result data subsequently, so as to maintain the diversity of result data. Therefore, the steps described in this implementation can be extended to multiple times, and it is only necessary to make adaptive modifications on the basis of this embodiment, and details will not be repeated here.

Please refer to FIG. 3 . FIG. 3 is a flow chart of index building in the method for selecting result data based on spatial keyword search provided by the embodiment of the present application.

Based on the previous embodiment, this embodiment is mainly a specific description of how to create an index result in the previous embodiment, other parts can refer to the previous embodiment, and will not be repeated here.

This embodiment can include:

S301. Determine the keyword occurrence times of each spatial text object;

S302, setting the space text object whose occurrence frequency of the keyword is less than the preset number of times as a block structure to obtain multiple block structures;

S303, setting the spatial text objects whose keyword occurrence times are greater than or equal to the preset number of times as a tree structure to obtain multiple tree structures;

S304. Use all block structures and all tree structures as index structures.

In the existing spatial keyword query, the index results can be divided into three categories: the index structure with space priority, the index structure with text priority and the index structure with the two closely combined. The space-first index structure can be further divided into index structures based on R-trees, grids, and space-filling curves; the text-first index structure is mainly based on inverted files and bitmaps; the index structure combined with space and text is closely combined with these structures to be more effective Filter some spatial text objects that do not meet the requirements of the query object. However, as the amount of data increases, these index structures become extremely large, which makes the space occupied by the index skyrocket, and the update speed slows down, which affects the experience in practical applications.

Therefore, in this embodiment, different index structures are set for each spatial text object through the keyword occurrence times of the object, that is, the index structure of the spatial text object is hierarchically processed, and objects with lower frequency of keyword occurrence are set as blocks Structure, used to store a large amount of object data. Objects with high frequency of keywords are set in a tree structure, which is convenient for finding related objects when searching.

And in the process of searching objects, you can search different tree structures and block structures to complete the corresponding search operations. For a tree structure that meets the query object condition, the object nodes in it can be accessed in the increasing order of the minimum boundary cost, where the minimum boundary cost can be defined as:

Among them, N represents the node of the tree structure, Dist(q,N.mbr) is the spatial distance between the minimum bounding rectangle of N and the query, |Occur _i = 1| is the number of occurrences in the index structure of N (that is, the topics covered by N number).

The embodiment of the present application provides a method for selecting result data based on spatial keyword search, which can determine the boundary cost of each candidate spatial text object through the distance coefficient and the number of diverse topics, and select the candidate spatial text object with the smallest boundary cost to the result Concentration, so that the distance between the object in the result set and the query object is short and the number of diverse topics is kept high, that is, the diversity of each search result is considered while selecting based on the distance coefficient, and the diversity of the result set is improved. Meet the diverse search needs of users.

The following is an introduction to a result data selection device based on spatial keyword search provided by the embodiment of the present application. The result data selection device based on spatial keyword search described below is the same as the one described above based on spatial keyword search. The result data selection methods can be referred to each other.

Please refer to FIG. 4 , which is a schematic structural diagram of an apparatus for selecting result data based on spatial keyword search provided by an embodiment of the present application.

This embodiment provides a device for selecting result data based on spatial keyword search, which may include:

An index building module 100, configured to perform an index structure building operation on multiple spatial text objects to obtain an index structure;

The candidate set acquisition module 200 is used to select a plurality of candidate space text objects using an index structure according to the obtained query object to obtain a candidate set;

The distance coefficient acquisition module 300 is used to determine the distance between each candidate space text object and the query object, and obtain the distance coefficient between each candidate space text object and the query object;

The first diversity topic number acquisition module 400 is used to determine the number of topics that each candidate space text object includes outside all the topics initialized, and obtain the first diversity topic number of each candidate space text object;

The first boundary cost acquisition module 500 is used to determine the first boundary cost of each candidate space text object according to all distance coefficients and all first diversity topic numbers; wherein, the distance coefficient is proportional to the first boundary cost, and the first boundary cost The number of diverse topics is inversely proportional to the first boundary cost;

The first result data selection module 600 is configured to select the candidate space text object with the smallest first boundary cost and add it to the result set.

Based on the foregoing embodiments, it may also include:

The second diversity topic number acquisition module is used to determine that each candidate space text object is added after the candidate space text object with the minimum first boundary cost is added when selecting the candidate space text object with the minimum first boundary cost to add to the result set The number of topics included in all the topics of , get the second diversity topic number of each candidate space text object;

The second boundary cost acquisition module is used to determine the second boundary cost of the corresponding candidate space text object according to all distance coefficients and all second diversity topics; wherein, the distance coefficient is proportional to the second boundary cost, and the second The number of diverse topics is inversely proportional to the second boundary cost;

The second result data selection module is used to select the candidate space text object with the smallest second boundary cost and add it to the result set.

Wherein, the index building module 100 may include:

A keyword occurrence number acquisition unit is used to determine the keyword occurrence number of each space text object;

A block structure acquiring unit, configured to set a space text object whose keyword occurrence times are less than a preset number of times as a block structure to obtain multiple block structures;

A tree structure acquisition unit, configured to set the spatial text object whose occurrence times of keywords is greater than or equal to the preset number of times as a tree structure to obtain multiple tree structures;

The index structure acquisition unit is used to use all block structures and all tree structures as index structures.

Wherein, the candidate set obtaining module 200 may include:

The candidate set acquisition unit is used to select a plurality of candidate spatial text objects from all spatial text objects according to the obtained query object using an index structure according to a greedy algorithm to obtain a candidate set.

The embodiment of the present application also provides a server, including:

memory for storing computer programs;

The processor is configured to implement the method for selecting result data in the above-mentioned embodiments when executing the computer program.

The embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for selecting result data as in the above-mentioned embodiment is implemented.

Each embodiment in the description is described in a progressive manner, each embodiment focuses on the difference from other embodiments, and the same and similar parts of each embodiment can be referred to each other. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and for the related information, please refer to the description of the method part.

Professionals can further realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software or a combination of the two. In order to clearly illustrate the possible For interchangeability, in the above description, the composition and steps of each example have been generally described according to their functions. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present application.

The steps of the methods or algorithms described in connection with the embodiments disclosed herein may be directly implemented by hardware, software modules executed by a processor, or a combination of both. Software modules can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other Any other known storage medium.

A method for selecting result data based on spatial keyword search, a device for selecting result data, a server, and a computer-readable storage medium provided by the present application have been described above in detail. In this paper, specific examples are used to illustrate the principles and implementation methods of the present application, and the descriptions of the above embodiments are only used to help understand the methods and core ideas of the present application. It should be pointed out that those skilled in the art can make some improvements and modifications to the application without departing from the principles of the application, and these improvements and modifications also fall within the protection scope of the claims of the application.

Claims (10)

1. a kind of result data choosing method based on spatial key search, which is characterized in that including：

Index structure is executed to multiple space text objects and establishes operation, obtains index structure；

Multiple candidate spatial text objects are chosen using the index structure according to obtained query object, obtain Candidate Set；

The distance for determining each the candidate spatial text object and the query object, obtains each candidate spatial text The distance coefficient of object and the query object；

It determines the theme quantity that each candidate spatial text object includes except all themes of initialization, obtains each First diversity number of topics of the candidate spatial text object；

Each candidate spatial text pair is determined according to all distance coefficients and all first diversity numbers of topics The first boundary cost of elephant；Wherein, the distance coefficient and first boundary cost are proportional relation, first diversity Number of topics is inverse relation with first boundary cost；

The candidate spatial text object for choosing the first boundary cost minimum is added to result set.

2. result data choosing method according to claim 1, which is characterized in that further include：

When the candidate spatial text object for choosing the first boundary cost minimum is added to result set, each time is determined Select the outsourcing of all themes of the space text object after the candidate spatial text object of the first boundary cost minimum is added The theme quantity included obtains the second diversity number of topics of each candidate spatial text object；

The corresponding candidate spatial text is determined according to all distance coefficients and all second diversity numbers of topics The second boundary cost of object；Wherein, the distance coefficient and the second boundary cost are proportional relation, and described second is various Sexual Themes number is inverse relation with the second boundary cost；

The candidate spatial text object for choosing the second boundary cost minimization is added to the result set.

3. result data choosing method according to claim 2, which is characterized in that execute rope to multiple space text objects Guiding structure establishes operation, obtains index structure, including：

Determine the keyword occurrence number of each space text object；

The space text object that the keyword occurrence number is less than to preset times is set as block structure, obtains multiple agllutinations Structure；

The space text object that the keyword occurrence number is more than or equal to the preset times is set as tree construction, obtains more A tree construction；

Using all block structures and all tree constructions as the index structure.

4. result data choosing method according to claim 3, which is characterized in that use institute according to obtained query object It states index structure and chooses multiple candidate spatial text objects, obtain Candidate Set, including：

It is selected from all space text objects according to greedy algorithm using the index structure according to obtained query object Multiple candidate spatial text objects are taken, the Candidate Set is obtained.

5. a kind of result data selecting device based on spatial key search, which is characterized in that including：

Index establishes module, establishes operation for executing index structure to multiple space text objects, obtains index structure；

Candidate Set acquisition module, for choosing multiple candidate spatial texts using the index structure according to obtained query object Object obtains Candidate Set；

Distance coefficient acquisition module, the distance for determining each the candidate spatial text object and the query object, obtains To the distance coefficient of each the candidate spatial text object and the query object；

First diversity number of topics acquisition module, for determining that each the candidate spatial text object is in all masters of initialization The theme quantity for including except topic obtains the first diversity number of topics of each candidate spatial text object；

First boundary cost acquisition module, for true according to all distance coefficients and all first diversity numbers of topics First boundary cost of fixed each candidate spatial text object；Wherein, the distance coefficient and first boundary cost For proportional relation, the first diversity number of topics is inverse relation with first boundary cost；

First result data chooses module, and the candidate spatial text object for choosing the first boundary cost minimum is added to Result set.

6. result data selecting device according to claim 5, which is characterized in that further include：

Second diversity number of topics acquisition module, for when the candidate spatial text object for choosing the first boundary cost minimum When being added to result set, determine that each candidate spatial text object is literary in the candidate spatial of the first boundary cost minimum The theme quantity for including except all themes after the addition of this object, obtains more than the second of each candidate spatial text object Sample Sexual Themes number；

The second boundary cost acquisition module, for true according to all distance coefficients and all second diversity numbers of topics The second boundary cost of the fixed corresponding candidate spatial text object；Wherein, the distance coefficient and the second boundary at This is proportional relation, and the second diversity number of topics is inverse relation with the second boundary cost；

Second result data chooses module, and the candidate spatial text object for choosing the second boundary cost minimization is added to The result set.

7. result data selecting device according to claim 6, which is characterized in that the index establishes module, including：

Keyword occurrence number acquiring unit, the keyword occurrence number for determining each space text object；

Block structure acquiring unit, the space text object for the keyword occurrence number to be less than to preset times are set as block Structure obtains multiple block structures；

Tree construction acquiring unit, the space text object for the keyword occurrence number to be more than or equal to the preset times It is set as tree construction, obtains multiple tree constructions；

Index structure acquiring unit, for using all block structures and all tree constructions as the index structure.

8. result data selecting device according to claim 7, which is characterized in that the Candidate Set acquisition module, including：

Candidate Set acquiring unit, for according to obtained query object using the index structure according to greedy algorithm from all institutes It states and chooses multiple candidate spatial text objects in the text object of space, obtain the Candidate Set.

9. a kind of server, which is characterized in that including：

Memory, for storing computer program；

Processor realizes that Claims 1-4 any one of them result data such as is chosen when for executing the computer program Method.

10. a kind of computer readable storage medium, which is characterized in that be stored with computer on the computer readable storage medium Program realizes such as Claims 1-4 any one of them result data selection side when the computer program is executed by processor Method.