Patent Retrieval

In this era of "big data", hundreds or even thousands of patent applications arrive every day to patent offices around the world. One of the first tasks of the professional analysts in patent offices is to assign classification codes to those patents based on their content. Such classification codes are usually organized in hierarchical structures of concepts. Traditionally the classification task has been done manually by professional experts. However, given the large amount of documents, the patent professionals are becoming overwhelmed. If we add that the hierarchical structures of classification are very complex (containing thousands of categories), reliable, fast and scalable methods and algorithms are needed to help the experts in patent classification tasks. This chapter describes, analyzes and reviews systems that, based on the textual content of patents, automatically classify such patents into a hierarchy of categories. This chapter focuses specially in the patent classification task applied for the International Patent Classification (IPC) hierarchy. The IPC is the most used classification structure to organize patents, it is worldwide recognized, and several other structures use or are based on it to ensure office inter-operability.

In response to growing needs for cross-lingual patent retrieval, we propose PRIME (Patent Retrieval In Multilingual Environment system), in which users can retrieve and browse patents in foreign languages only by their native language. PRIME translates a query in the user language into the target language, retrieves patents relevant to the query, and translates retrieved patents into the user language. To update a translation dictionary, PRIME automatically extracts new translations from parallel patent corpora. In the current implementation, trilingual (J/E/K) patent retrieval is available. We describe the system design and its evaluation.

This study explores the benefits of integrating knowledge representations in prior art patent retrieval. Key to the introduced approach is the utilization of human judgment available in the form of classifications assigned to patent documents. The paper first outlines in detail how a methodology for the extraction of knowledge from such an hierarchical classification system can be established. Further potential ways of integrating this knowledge with existing Information Retrieval paradigms in a scalable and flexible manner are investigated. Finally based on these integration strategies the effectiveness in terms of recall and precision is evaluated in the context of a prior art search task for European patents. As a result of this evaluation it can be established that in general the proposed knowledge expansion techniques are particularly beneficial to recall and, with respect to optimizing field retrieval settings, further result in significant precision gains.

Abstract. The combination of different search techniques can improve the results given by each one. In the ongoing R&D project PATExpert1, four different search techniques are combined to perform a patent search. These techniques are: metadata search, keyword-based search, semantic search and image search. In this paper we propose a general architecture based on web services where each tool works in its own domain and provides a set of basic functionalities to perform the retrieval. To be able to combine the results from ...

In response to growing needs for cross-lingual patent retrieval, we propose PRIME (Patent Retrieval In Multilingual Environment system), in which users can retrieve and browse patents in foreign languages only by their native language. PRIME translates a query in the user language into the target language, retrieves patents relevant to the query, and translates retrieved patents into the user language. To update a translation dictionary, PRIME automatically extracts new translations from parallel patent corpora. In the current implementation, trilingual (J/E/K) patent retrieval is available. We describe the system design and its evaluation.

This paper reports our experimental results at the NTCIR-6 English Patent Retrieval Subtask. Our previous participation at the patent retrieval Subtask revealed that the long length of the patent applications require less smoothing of the document model than general documents such as news paper articles. We setup the initial baseline retrieval system for U.S. patent applications and compare the difference from that of Japanese patent applications.

In this article, we present ongoing work on an advanced patent processing service PATExpert. The central assumption underlying PATExpert is that in order to meet the needs of the users of patent processing services, recourse must be made to the content of patent material. We introduce a content representation schema for patent documentation and sketch the design of techniques that facilitate the integration of this schema into the patent processing cycle. Two types of techniques are discussed. Techniques of the first type ...

The CLEF-IP track was launched in 2009 to investigate IR techniques for patent retrieval, as part of the CLEF 2009 evaluation campaign. We built a system in order to participate in the CLEF-IP track. Our system has three main components: a filtering module, an indexing module, and a search module. Because the process of indexing all of the 75 GB of input patent documents took almost one day, we decided to work in a peer-to-peer environment with four computers. The problems encountered were related to the identification of relevant fields to be used for indexing and in the search processes.

It has been noted before in this book that patent retrieval is different from, and more complicated than “standard” information retrieval. Evaluation of patent retrieval engines has also been shown to require specific attention. In this chapter, we continue making this point, but emphasize the efforts undertaken in a specific domain, namely chemistry. We approached this issue from two different perspectives. First, there is the issue of scalability. Largely similar to the CLEF-IP efforts, it targets the problem of having to handle a large number of documents and, potentially, a large number of queries. Second, there are the issues generated by the specific characteristics of chemistry documents. We describe here how we manually created a set of topics to reflect the kind of requests for information that a patent searcher, or a general researcher, might have. The results of the first year’s track are presented as well, together with directions and desiderata for the next years.

Abstract. The Clef–Ip track ran for the first time within Clef 2009. The purpose of the track was twofold: to encourage and facilitate re-search in the area of patent retrieval by providing a large clean data set for experimentation; to create a large test collection of patents in the three ...