PATATRAS: Retrieval Model Combination and Regression Models for Prior Art Search

Lopez, Patrice; Romary, Laurent

doi:10.1007/978-3-642-15754-7_51

Cited by 17 publications

(8 citation statements)

References 7 publications

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“…Dictionary-based: semantic-based methods perform QRE by expanding the query to include other terms that have similar meanings to the original query terms. The first category of these methods are the dictionary-based techniques which use either generic Jones (2011), technical Lopez andRomary (2009), or patent-specific dictionaries Tannebaum and Rauber (2012b, 2013, 2015; ; Wajda and Zadrozny (2016); Mahdabi and Crestani (2014b) for QRE. Generic dictionaries could be existing lexical databases such as WordNet Fellbaum (1998), while patent-specific dictionaries are lexical databases generated from patent-related data such as examiner's query logs.…”

Section: Semantic-based Methodsmentioning

confidence: 99%

Patent retrieval: a literature review

Shalaby¹,

Zadrozny²

2019

Knowl Inf Syst

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With the ever increasing number of filed patent applications every year, the need for effective and efficient systems for managing such tremendous amounts of data becomes inevitably important. Patent Retrieval (PR) is considered the pillar of almost all patent analysis tasks. PR is a subfield of Information Retrieval (IR) which is concerned with developing techniques and methods that effectively and efficiently retrieve relevant patent documents in response to a given search request. In this paper we present a comprehensive review on PR methods and approaches. It is clear that, recent successes and maturity in IR applications such as Web search cannot be transferred directly to PR without deliberate domain adaptation and customization. Furthermore, state-of-the-art performance in automatic PR is still around average in terms of recall. These observations motivate the need for interactive search tools which provide cognitive assistance to patent professionals with minimal effort. These tools must also be developed in hand with patent professionals considering their practices and expectations. We additionally touch on related tasks to PR such as patent valuation, litigation, licensing, and highlight potential opportunities and open directions for computational scientists in these domains.

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Section: Semantic-based Methodsmentioning

confidence: 99%

Patent retrieval: a literature review

Shalaby¹,

Zadrozny²

2019

Knowl Inf Syst

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“…However, we have access to the citations of all other documents apart from the query topics in the collection. A recent work [Lopez and Romary 2009] used a Web service offered by the European Patent Office 9 to retrieve the bibliographical attributes of documents in the collection. We also used this Web service to extract all the citations of the documents in the collection with the exception of the query documents.…”

Section: Query-specific Citation Graphmentioning

confidence: 99%

Patent Query Formulation by Synthesizing Multiple Sources of Relevance Evidence

Mahdabi

Crestani

2014

ACM Trans. Inf. Syst.

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Patent prior art search is a task in patent retrieval with the goal of finding documents which describe prior art work related to a query patent. A query patent is a full patent application composed of hundreds of terms which does not represent a single focused information need. Fortunately, other relevance evidence sources (i.e., classification tags and bibliographical data) provide additional details about the underlying information need. In this article, we propose a unified framework that integrates multiple relevance evidence components for query formulation. We first build a query model from the textual fields of a query patent. To overcome the term mismatch, we expand this initial query model with the term distribution of documents in the citation graph, modeling old and recent domain terminology. We build an IPC lexicon and perform query expansion using this lexicon incorporating proximity information. We performed an empirical evaluation on two patent datasets. Our results show that employing the temporal features of documents has a precision enhancing effect, while query expansion using IPC lexicon improves the recall of the final rank list. ACM Reference Format:Parvaz Mahdabi and Fabio Crestani. 2014. Patent query formulation by synthesizing multiple sources of relevance evidence.

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“…A recent work tried to extract these citations with regular expressions but the reported accuracy was low. Another previous work (Lopez and Romary 2009) used a web service offered by the European Patent Office (EPO) 4 to retrieve the citations of documents in the collection. We used this web service to extract all the citations of the documents in the collection with the exception of the query documents.…”

Section: Query-specific Citation Graphmentioning

confidence: 99%

The effect of citation analysis on query expansion for patent retrieval

Mahdabi

Crestani

2013

Inf Retrieval

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Patent prior art search is a type of search in the patent domain where documents are searched for that describe the work previously carried out related to a patent application. The goal of this search is to check whether the idea in the patent application is novel. Vocabulary mismatch is one of the main problems of patent retrieval which results in low retrievability of similar documents for a given patent application. In this paper we show how the term distribution of the cited documents in an initially retrieved ranked list can be used to address the vocabulary mismatch. We propose a method for query modeling estimation which utilizes the citation links in a pseudo relevance feedback set. We first build a topic dependent citation graph, starting from the initially retrieved set of feedback documents and utilizing citation links of feedback documents to expand the set. We identify the important documents in the topic dependent citation graph using a citation analysis measure. We then use the term distribution of the documents in the citation graph to estimate a query model by identifying the distinguishing terms and their respective weights. We then use these terms to expand our original query. We use CLEF-IP 2011 collection to evaluate the effectiveness of our query modeling approach for prior art search. We also study the influence of different parameters on the performance of the proposed method. The experimental results demonstrate that the proposed approach significantly improves the recall over a state-of-the-art baseline which uses the link-based structure of the citation graph but not the term distribution of the cited documents.

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PATATRAS: Retrieval Model Combination and Regression Models for Prior Art Search

Cited by 17 publications

References 7 publications

Patent retrieval: a literature review

Patent retrieval: a literature review

Patent Query Formulation by Synthesizing Multiple Sources of Relevance Evidence

The effect of citation analysis on query expansion for patent retrieval

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