CN101639840A - Method and device for identifying semantic structure of network information - Google Patents
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Abstract
The invention discloses a method and a device for identifying a semantic structure of network information. The semantic structure comprises a plurality of semantic comments of the network page information content related to the semantics, properties of the commented information, and relations among the semantic comments. The method comprises the following steps: storing into a semantic structure tree in the system by defining the semantic structure of a sample page; generating a semantic tree identification command and a semantic tree validity identification command; and storing a semantic structure description file, a semantic tree identification command file and a semantic tree validity identification file in an external storage after the semantic tree identification command and the semantic tree validity identification command are verified. The semantic structure of the network page information, which is defined and identified by the method and the device of the invention, can be used by various systems, such as an information extraction system, a full-text and semantic search system, a commercial information mining system, an information syndication system, a network knowledgebase system and the like.
Description
Technical field
The invention belongs to computer science and technology domain semantics network branches, be specifically related to a kind of semantic structure of network information recognition methods, be applicable to applications such as network information extraction, full-text search and semantic search, business intelligence excavation, information fusion, networked knowledge base foundation.
Background technology
Tremendous development along with Internet and Web, information on the network is explosive growth, people are except obtaining knowledge and information from traditional media, more and more get used on network, asking for help, the full-text search technology has realized the hope of people's retrieval network information, as long as import several key words, just can promptly obtain to contain the information of these several key words.Yet, even research tool has been arranged, people still experience oneself and lose one's bearings in network information ocean at leisure, find information and the knowledge oneself be concerned about to become more and more difficult, because disturbed by increasing incoherent noise information, these information comprise the key word of searching, but content is incoherent.People wish to occur a kind of intelligence tool, help people to get rid of noise according to user's wish, filter out the information of real needs.Since invention on computer, social productive forces improve greatly, it frees the mankind from numerous and diverse work that stylizes of dullness, make people be absorbed in creationary activity, network information search is also born by computing machine, therefore, people naturally expect improving computerized algorithm, make it become people's intelligent information assistant.
The research of artificial intelligence has long history, even before computing machine occurred, people were just attempting artificial intelligency activity.Helping people to seek target information on network with artificial intelligence is optimal method, and the people has only a brain to be used for thinking, if there have been a lot of artificial brains to think deeply on network and filter information, obviously efficient and usefulness double.Yet infer from academic and technical experimental result, realize that this desirable hope is also remoter.
In fact, computing machine is not limited to knowledge understanding to information processing, and for example, it is quite ripe that database technology develops into today, almost is applied in modern all activities in production.On the surface, database has quite high intelligence, for example, in database table, deposited string number, Database Systems know that this string numeral is a telephone number, and it just can not handled as date or commodity amount, seem that it has understood the digital implication of this string.Technology angle from profound level, it is to have obtained indication in the semantic structure information (being the Schema of database) from database, it is not according to semantic environment this string number comprehension to be become telephone number as the human thinking, but database Schema stipulates what it used like this.This shows the importance of semantic structure in field of information processing, can imagine if semantic structure information is arranged on the Webpage, even computing machine does not know that a string number can What for, search system can not thrust user's a pile commodity statistics quantity when the user search telephone number.
But the most information on the existing network are presented to people and are read, and the information that is sent on the user terminal is to use HTML to set type, and the inside overwhelming majority is composition information (with the relevant semanteme of setting type), rare semantic information about content.Just as the expert sums up: for contents semantic, the existing network information is structureless or weak structure.As seen, if the semantic structure of the related content of these information is discerned and extracted, existing Web has just become a googol according to the storehouse, and it can distinguish string number at least is telephone number or commodity amount.Yet, network is unlike a single business database, it provides service for human lives's every aspect, therefore, setting up semantic structure for the existing network information is not the thing of accomplishing in one move, a solution is that people define out with the semantic structure in interested field separately, be the isolated island that does not communicate between these domain semantics structures at the beginning, extension and growth along with semantic structure, isolated island will be got through gradually, form a so-called semantic network, ideally, this network of throwing the net has covered all semantic coverages of network information content.
The invention discloses a kind of method and apparatus, the people that it can make all hanker after definition of network semantic structure and knowledge arrangement put into the construction of semantic network, the semantic structure of the Webpage information that the present invention defines and identifies can be used by systems such as information extraction, full-text search and semantic search, business intelligence excavation, information fusion, networked knowledge bases, for the user generates object information more accurately.
Summary of the invention
The invention discloses a kind of semantic structure of network information recognition methods and device, according to an aspect of the present invention, a kind of semantic structure of network information recognition methods is provided, described semantic structure comprises the attribute of the information that the relevant semantic annotation of a plurality of semantemes of the Webpage information content, quilt are explained, the relation between the semantic annotation, it is characterized in that, said method comprising the steps of:
(1) the described semantic structure of definition sample page is stored as the semantic structure tree in internal system;
(2) generative semantics tree recognition instruction and semantic tree legitimacy recognition instruction;
(3) validity of checking semantic tree recognition instruction and semantic tree legitimacy recognition instruction;
(4) with semantic structure description document and semantic tree recognition instruction file and semantic tree legitimacy identification file storage to external storage.
According to another aspect of the present invention, a kind of device of semantic structure of network information identification is provided, described semantic structure comprises the attribute of the information that the relevant semantic annotation of a plurality of semantemes of the Webpage information content, quilt are explained, the relation between the semantic annotation, it is characterized in that described device comprises:
The semantic structure edit cell is used for establishment and edits described semantic structure tree;
Sample semantic information piece pickup unit is used to choose the sample information piece on the sample page, for each sample semantic information piece is set up corresponding relation between the node in the information content and the described semantic structure tree;
Semantic structure recognition instruction generation unit is used to calculate the position of sample semantic information piece and reappear parameter, produces described semantic tree recognition instruction and described semantic tree legitimacy recognition instruction;
Semantic tree identification authentication unit is used to verify whether the semantic information piece that identifies meets the attribute specification of the shape facility and the described semantic tree node of described semantic tree;
Command file and semantic structure file read-write administrative unit are used for the described semantic tree recognition instruction of internal memory and described semantic tree legitimacy recognition instruction and described semantic structure tree are organized into file, store on the described external storage.
Description of drawings
Fig. 1 has showed the example of a semantic structure tree, and Figure 1A is a sample semantic information piece synoptic diagram, and Figure 1B is corresponding semantic structure tree
Fig. 2 is the process flow diagram of semantic structure of network information recognition methods according to an embodiment of the invention
Fig. 3 is the process flow diagram of the method for generative semantics tree recognition instruction according to an embodiment of the invention and semantic tree legitimacy recognition instruction
Fig. 4 is the exploded view of semantic structure of network information recognition device according to an embodiment of the invention
Embodiment
Below in conjunction with accompanying drawing the preferred embodiments of the present invention are described in detail.
The semantic structure of network information recognition methods
On Webpage, be full of a lot of and the incoherent information of page subject content, for example, and advertisement etc., Useful Information and knowledge only are present in some zone of the page, and hereinafter, we claim these zones to be the semantic information piece.A lot of semantic information pieces are generally arranged, and its semantic structure may be different, express different implications respectively on a page, Figure 1A for example, at one group of information representation bloger personal information in certain zone of blog page, it has semantic structure A; In the another one zone is a series of blog articles that the bloger delivers, n semantic information piece arranged, they have semantic structure B, the semantic information piece that the preferred embodiments of the present invention can accurately will meet semantic structure A and semantic structure B all sidedly identifies, and output semantic tree recognition instruction file and semantic tree legitimacy recognition instruction file, these files can instruct other system to extract the information of semantic structure.
Figure 1B is two semantic structure trees of creating at this sample page, semantic tree is many fork multilayer trees, each node attaches one group of property value, semanteme to the node representative is modified, the preferred embodiments of the present invention can be modified value type, span, the semantic type of node, and mutual relationship has been represented on the limit between the node.Because bloger's data has only a semantic information piece, use this unique semantic information piece to set up the corresponding relation of setting with semantic structure, and blog article has a plurality of semantic information pieces, need to select at least two sample information pieces, concrete selection is several, need to consider the layout of target pages, relevant with the dimension that the semantic information piece distributes.
Fig. 2 is the process flow diagram of semantic structure of network information recognition methods according to a preferred embodiment of the invention.At first in step 201, the user uses browser embedded in the preferred embodiments of the present invention to load the network of samples page, be content of pages definition semantic structure, comprise the attribute of the semantic annotation of the Webpage information content, the information explained, the relation between the semantic annotation.Semantic structure represents with tree structure, and the semantic annotation of tree node representative information content is named to semantic annotation with a character string, and semantic relation is represented on the limit between the tree node, and the semantic structure tree is stored in (208) in the internal memory.
Then in step 202, the user selects sample semantic information piece on sample page, the quantity of the sample information piece of selecting is relevant with the dimension that the semantic information piece distributes, for example, if have only a hurdle on the page, the order discharging from top to bottom of semantic information piece then has only a dimension, select two neighbouring semantic information pieces to get final product, the distribution of the semantic information piece of the blog article shown in Figure 1A just belongs to this situation; If multicolumn is laterally arranged on the page, the semantic information piece then has two dimensions by the order discharging from top to bottom of identical rule in each hurdle, selects three semantic information pieces, and is neighbouring in twos adjacent with the left and right sides.
Then in step 203, the web page contents pick tool that the user uses the preferred embodiments of the present invention to provide is set up the corresponding relation that the information content of being picked up and the semantic structure that defines are set each node.
Then in step 204, extract location parameter, the parameters for shape characteristic of sample information tree, produce the identification computing formula of described semantic structure tree, and convert semantic tree recognition instruction and semantic tree legitimacy recognition instruction to, be stored in (209) in the internal memory, the detailed method step as shown in Figure 3.
Then in step 205, the semantic tree recognition instruction and the semantic tree legitimacy recognition instruction that use step 204 to generate are discerned the message block that meets the semantic structure that defines on target pages, the validity of checking recognition instruction.At first the XSLT engine of the built-in standard of using system is at sample page operation XSLT semantic tree recognition instruction, whether the semantic information piece that check identifies has covered all semantic information pieces of the semantic structure that meets definition on the target pages, check the semantic information content in each semantic information piece that identifies whether accurate simultaneously, whether with the irrelevant information extraction on the page come out, perhaps whether the semantic information content of needs has been omitted; The built-in XML engine of using system moves semantic tree legitimacy recognition instruction at the semantic structure tree example that identifies then, whether check meets the described semantic structure of definition, the preferred embodiment of the present invention will check the semantic information content in the semantic information piece whether to meet the nodal community requirement of the semantic tree structure of definition, whether have identical tree shape.If do not cover all semantic information pieces fully, perhaps do not meet the definition of semantic tree nodal community from the semantic information content of extracting, the message block that perhaps identifies does not conform to the semantic tree shape, will point out the user to reselect sample semantic information piece, turns back to step 202; If the recognition instruction empirical tests is effectively, carry out next step.
Then in step 207, the semantic tree recognition instruction in the internal memory and semantic tree legitimacy recognition instruction and semantic structure are organized into file, store in the external storage.
Fig. 3 be according to a preferred embodiment of the invention generative semantics tree recognition instruction and the process flow diagram of the method for semantic tree legitimacy recognition instruction, be the detailed decomposition of the step 204 of Fig. 2.The semantic structure identifying operation carries out at Webpage DOM data structure.DOM is writing a Chinese character in simplified form of DOM Document Object Model (Document Object Model), Webpage is when presenting to the user and read, the Webpage content stores is in the DOM data structure, it is a tree structure, the preferred embodiments of the present invention read the DOM structure, obtain various information, comprise the content of DOM node, characteristic and the father and son between the node and the brotherhood etc. of node.The sample semantic information piece that the preferred embodiments of the present invention are chosen is a DOM subtree, described sample information tree is that sample information piece subtree is pruned setting with the identical information stores of defined semantic structure tree shape of back generation, also comprises the metadata about the tree feature simultaneously.
At first,, the information stores tree of each sample semantic information piece is pruned according to the defined semantic structure tree of step 201 in step 301, remove irrelevant information, keep the information that meets the semantic structure that defines, produce the sample information tree, all sample information trees are stored in the set.In a preferred embodiment of the invention, sample information is set the metadata about the tree feature that comprises has:
1. the access path of each semantic information node is used through the XPath expression formula of transforming and is represented
2. whether each semantic information node is shared by a plurality of sample information trees
3. the trunk of sample information tree, that is, the part of first branch front of sample information tree is a trunk part.
Then in step 302, fundamental purpose is to calculate the change in location parameter that sample information is set each node, uses these parameters on target pages each node to be identified, and the change in location parameter of node comprises:
1. the DOM node that has identical access path in the DOM of full page data structure is formed a sequence node, the reference position of sample information tree node in this sequence
2. in this sequence node, the cycle that the sample information tree node repeats
Then, elect a sample information tree branch as reference in step 303.In step 302, the node location running parameter is all independently calculated each node, do not consider semantic tree shape and the relativeness in semantic tree, so, will inevitably extract a lot of incoherent contents iff adopting this node location running parameter to extract the network information.After electing sample information tree reference branch, the location parameter of other node of sample information tree will carry out conversion with respect to reference branch.
Then in step 304, the location parameter of the node of sample information tree is carried out conversion with respect to reference branch, obtain the relative position parameter, be exactly father and son and the brotherhood of node with respect to the leaf node of reference branch, can be used for determining the position of node in the sample information tree, just determine the shape of sample information tree; Positional information calculation according to the reference branch of different sample informations tree goes out the location parameter of whole tree then.
Then in step 305, produce semantic structure identification formula, mainly contain two class formula: other semantic structure node is with respect to the ranging formula of reference branch in the identification formula of reference branch and the semantic structure tree.The identification formula of reference branch integrated semantic structure tree location parameter and form parameter and with nodal community as filtercondition.
Follow in step 306 generative semantics structure recognition instruction and semantic structure legitimacy recognition instruction.The identification formula of step 305 generation is converted to the XSLT instruction generative semantics structure recognition instruction of standard, this instruction can be explained by the XSLT engine of standard and carry out, the semantic information piece that will meet semantic structure from the Webpage identifies, semantic content in the semantic information piece is extracted, according to the XSLT instruction storage in the extraction destination file of XML file layout.Semantic structure legitimacy recognition instruction is to produce according to the location parameter of semantic structure tree and form parameter especially the attribute structure of semantic structure tree node, it is the XML form, can be explained by the XML engine of special use and carry out, the semantic content that extracts is checked.
The semantic structure of network information recognition device
Fig. 4 is the exploded view of semantic structure of network information recognition device according to a preferred embodiment of the invention, visit between the sequence number representative unit that marks among the figure and accessed relation.As shown in Figure 4, the user uses the semantic structure edit cell to create the attribute of semantic structure tree, definition semantic structure tree node, describe semantic relation, and the semantic structure tree is stored in (401) in the internal memory; The user is loaded into sample page on the embedded Web browser of system, uses sample semantic information piece pickup unit to set up corresponding relation (402) between the node of the information content in setting with semantic structure for each sample semantic information piece; Corresponding relation is input to semantic structure recognition instruction generation unit (403), the semantic structure descriptor (404) that utilization is obtained from internal memory, semantic structure recognition instruction generation unit calculates location parameter, the parameters for shape characteristic of sample information tree, produce semantic information tree identification computing formula, convert semantic tree recognition instruction that meets the XSLT standard and the semantic tree legitimacy recognition instruction that meets the XML document format standard to, be stored in (405) in the internal memory; Semantic tree identification authentication unit obtains semantic tree recognition instruction and semantic tree legitimacy recognition instruction from internal memory, apply on the sample page and test, if the user is dissatisfied, use the semantic structure edit cell to revise the corresponding relation of semantic structure or use sample semantic information piece pickup unit modification content of pages and semantic structure, repeat above-mentioned steps, till satisfaction; Semantic tree identification that meets the demands and legitimacy recognition instruction and semantic structure are input to command file and semantic structure file read-write administrative unit (408,409), generation meets the semantic tree recognition instruction file of XSLT standard and meets the semantic tree legitimacy recognition instruction file and the semantic structure description document of XML document format standard, store into (410,411) on the external storage.Some arrow is two-way among the figure, expression in the external storage original semantic tree identification and legitimacy recognition instruction file and semantic structure description document be read into present embodiment, it is made amendment or additional.
Claims (8)
1, a kind of recognition methods of semantic structure of network information, described semantic structure comprises the attribute of the information that the relevant semantic annotation of a plurality of semantemes of the Webpage information content, quilt are explained, the relation between the semantic annotation, it is characterized in that, said method comprising the steps of:
(1) the described semantic structure of definition sample page is stored as the semantic structure tree in internal system;
(2) generative semantics tree recognition instruction and semantic tree legitimacy recognition instruction;
(3) validity of checking semantic tree recognition instruction and semantic tree legitimacy recognition instruction
(4) with semantic structure description document and semantic tree recognition instruction file and semantic tree legitimacy identification file storage to external storage
2, the recognition methods of semantic structure of network information according to claim 1 is characterized in that, described semantic structure tree comprises:
The semantic structure tree node is represented the semantic annotation of the Webpage information content, names semantic annotation with text string;
The attribute of semantic structure tree node is modified semantic annotation;
Relation between the semantic structure tree node is represented with the limit between the node.
3, the recognition methods of semantic structure of network information according to claim 1 is characterized in that, described semantic structure description document is an XML file, is used for the user-defined described semantic structure of storage on external storage.
4, the recognition methods of semantic structure of network information according to claim 1 is characterized in that, the XSLT instruction that described semantic tree recognition instruction is a standard, and the form with semantic tree recognition instruction file on external storage is stored.
5, the recognition methods of semantic structure of network information according to claim 1, it is characterized in that described semantic tree legitimacy recognition instruction is the instruction that meets the XML document format standard, the form with semantic tree legitimacy recognition instruction file on external storage is stored.
6, the recognition methods of semantic structure of network information according to claim 1, it is characterized in that, the described method that stores external storage into is behind generative semantics structure description file, semantic tree recognition instruction file and the semantic tree legitimacy recognition instruction file, to export the local external storage and the webserver stores device that store local hard drive and other type in calculator memory.
7, the recognition methods of semantic structure of network information according to claim 1 is characterized in that, the method for described generative semantics tree recognition instruction and semantic tree legitimacy recognition instruction may further comprise the steps:
(21) user selects sample semantic information piece respectively for each described semantic structure on target pages, if there is the polylith information of identical described semantic structure on the target pages, select a plurality of sample semantic information pieces, otherwise, for each described semantic structure is only selected a sample semantic information piece;
(22) set up corresponding relation between the information content and the described semantic structure node in setting for each sample semantic information piece;
(23) position of calculating sample semantic information piece and reproduction parameter produce semantic tree recognition instruction that meets the XSLT standard and the semantic tree legitimacy recognition instruction that meets the XML document format standard.
8, a kind of device of identification of semantic structure of network information, described semantic structure comprise the attribute of the information that the relevant semantic annotation of a plurality of semantemes of the Webpage information content, quilt are explained, the relation between the semantic annotation, it is characterized in that described device comprises:
The semantic structure edit cell is used for establishment and edits described semantic structure tree;
Sample semantic information piece pickup unit is used to choose the sample information piece on the sample page, for each sample semantic information piece is set up corresponding relation between the node in the information content and the described semantic structure tree
Semantic structure recognition instruction generation unit is used to calculate the position of sample semantic information piece and reappear parameter, produces described semantic structure tree recognition instruction and described semantic structure tree legitimacy recognition instruction
Semantic tree identification authentication unit is used to verify whether the semantic information piece that identifies meets the attribute specification of the shape facility and the described semantic tree node of described semantic tree
Command file and semantic structure file read-write administrative unit are used for the described semantic tree recognition instruction of internal memory and described semantic tree legitimacy recognition instruction and described semantic structure tree are organized into file, store on the described external storage.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104281693A (en) * | 2014-10-13 | 2015-01-14 | 安徽华贞信息科技有限公司 | Semantic search method and semantic search system |
| CN104408639A (en) * | 2014-10-22 | 2015-03-11 | 百度在线网络技术（北京）有限公司 | Multi-round conversation interaction method and system |
| CN105431839A (en) * | 2013-03-15 | 2016-03-23 | 罗伯特·哈多克 | Intelligent internet system with adaptive user interface providing one-step access to knowledge |
| CN105843960A (en) * | 2016-04-18 | 2016-08-10 | 上海泥娃通信科技有限公司 | Semantic tree based indexing method and system |
| CN106776564A (en) * | 2016-12-21 | 2017-05-31 | 张永成 | The method for recognizing semantics and system of a kind of knowledge based collection of illustrative plates |
| CN109634660A (en) * | 2018-10-16 | 2019-04-16 | 深圳壹账通智能科技有限公司 | Program structure method for visualizing, equipment, storage medium and device |
| CN111488741A (en) * | 2020-04-14 | 2020-08-04 | 税友软件集团股份有限公司 | Tax knowledge data semantic annotation method and related device |
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| CN105431839A (en) * | 2013-03-15 | 2016-03-23 | 罗伯特·哈多克 | Intelligent internet system with adaptive user interface providing one-step access to knowledge |
| CN104281693A (en) * | 2014-10-13 | 2015-01-14 | 安徽华贞信息科技有限公司 | Semantic search method and semantic search system |
| CN104408639A (en) * | 2014-10-22 | 2015-03-11 | 百度在线网络技术（北京）有限公司 | Multi-round conversation interaction method and system |
| CN105843960A (en) * | 2016-04-18 | 2016-08-10 | 上海泥娃通信科技有限公司 | Semantic tree based indexing method and system |
| CN105843960B (en) * | 2016-04-18 | 2019-12-06 | 上海泥娃通信科技有限公司 | Indexing method and system based on semantic tree |
| CN106776564A (en) * | 2016-12-21 | 2017-05-31 | 张永成 | The method for recognizing semantics and system of a kind of knowledge based collection of illustrative plates |
| CN112955961A (en) * | 2018-08-28 | 2021-06-11 | 皇家飞利浦有限公司 | Method and system for normalization of gene names in medical texts |
| CN112955961B (en) * | 2018-08-28 | 2024-06-11 | 皇家飞利浦有限公司 | Method and system for standardizing gene names in medical texts |
| CN109634660A (en) * | 2018-10-16 | 2019-04-16 | 深圳壹账通智能科技有限公司 | Program structure method for visualizing, equipment, storage medium and device |
| CN111488741A (en) * | 2020-04-14 | 2020-08-04 | 税友软件集团股份有限公司 | Tax knowledge data semantic annotation method and related device |
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