A study of query reformulation for patent prior art search with partial patent applications

Bouadjenek, Mohamed Reda; Sanner, Scott; Ferraro, Gabriela

doi:10.1145/2746090.2746092

Cited by 13 publications

(13 citation statements)

References 19 publications

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“…In the implementation, each section of a patent such as title, abstract, claims, IPC and description is indexed in a separate field. However, when a query is processed, all indexed fields are targeted as this generally offers best retrieval performance [33]. The relevance assessment is provided for the topic set (queries) which are patents and have title, abstract, IPC, description, and claims sections.…”

Section: A Testing Collections and Pre-processingmentioning

confidence: 99%

Effect of Technical Domains and Patent Structure on Patent Information Retrieval

Khode¹,

Jambhorkar²

2019

IJEAT

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Patents are critical intellectual assets for any competitive business. With ever increasing patent filings, effective patent prior art search has become an inevitably important task in patent retrieval which is a subfield of information retrieval (IR). The goal of the prior art search is to find and rank documents related to a query patent. Query formulation is a key step in prior art search in which patent structure is exploited to generate queries using various fields available in patent text. As patent encodes multiple technical domains, this work argues that technical domains and patent structure have their combined effect on the effectiveness of patent retrieval. The study uses international patent classification codes (IPC) to categorize query patents in eight technical domains and also explores eighteen different combination of patent fields to generate search queries. A total of 144 extensive retrieval experiments have been carried out using BM25 ranking algorithm. Retrieval performance is evaluated in terms of recall score of top 1000 records. Empirical results support our assumption. A two-way analysis of variance is also conducted to validate the hypotheses. The findings of this work may be helpful for patent information retrieval professionals to develop domain specific patent retrieval systems exploiting the patent structure.

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Section: A Testing Collections and Pre-processingmentioning

confidence: 99%

Effect of Technical Domains and Patent Structure on Patent Information Retrieval

Khode¹,

Jambhorkar²

2019

IJEAT

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“…While it is known that query length in operational interactive IR systems (in particular Web search engines) is rather short, typically between two and three terms long ( 31 , 32 ), in other IR contexts queries may be longer, ranging from ten to thousands of terms ( 33 , 34 ). Therefore, several researchers have investigated strategies for query length reduction, for the purpose of removing ambiguous and noisy terms.…”

Section: Related Workmentioning

confidence: 99%

“…Then, the query is reduced by removing the least similar segments to the query. In ( 33 ), the authors proposed to study several query reduction techniques and their impact on the task of patent prior art search. They have shown that while query reduction techniques have a mitigated impact on mid-length queries, they are very effective on long queries such as an extended abstract or a description.…”

Section: Related Workmentioning

confidence: 99%

Multi-field query expansion is effective for biomedical dataset retrieval

Bouadjenek

Verspoor

2017

Database

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In the context of the bioCADDIE challenge addressing information retrieval of biomedical datasets, we propose a method for retrieval of biomedical data sets with heterogenous schemas through query reformulation. In particular, the method proposed transforms the initial query into a multi-field query that is then enriched with terms that are likely to occur in the relevant datasets. We compare and evaluate two query expansion strategies, one based on the Rocchio method and another based on a biomedical lexicon. We then perform a comprehensive comparative evaluation of our method on the bioCADDIE dataset collection for biomedical retrieval. We demonstrate the effectiveness of our multi-field query method compared to two baselines, with MAP improved from 0.2171 and 0.2669 to 0.2996. We also show the benefits of query expansion, where the Rocchio expanstion method improves the MAP for our two baselines from 0.2171 and 0.2669 to 0.335. We show that the Rocchio query expansion method slightly outperforms the one based on the biomedical lexicon as a source of terms, with an improvement of roughly 3% for MAP. However, the query expansion method based on the biomedical lexicon is much less resource intensive since it does not require computation of any relevance feedback set or any initial execution of the query. Hence, in term of trade-off between efficiency, execution time and retrieval accuracy, we argue that the query expansion method based on the biomedical lexicon offers the best performance for a prototype biomedical data search engine intended to be used at a large scale. In the official bioCADDIE challenge results, although our approach is ranked seventh in terms of the infNDCG evaluation metric, it ranks second in term of P@10 and NDCG. Hence, the method proposed here provides overall good retrieval performance in relation to the approaches of other competitors. Consequently, the observations made in this paper should benefit the development of a Data Discovery Index prototype or the improvement of the existing one.

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“…We developed a baseline IR system for patent prior art search on the top of the Lucene search engine and LM (Dirichlet smoothing, and Jelinek-Mercer smoothing) scoring functions based on [2]. We used Lucene to index the English subset of the CLEF-IP 2010 dataset 1 that contains 2.6 million patent documents and a subset of 1281 topics (queries) in the English test set where we determined at least one valid, relevant English document was available.…”

Section: Baseline Ir Frameworkmentioning

confidence: 99%

“…Kim et al [6] provided diverse query suggestion using aspect identification from a patent query to increase the chance of retrieving relevant documents. Magdy et al [9] and Bouadjenek et al [2] studied different query expansion and reduction techniques for patent search on CLEF-IP 2010, and reported little improvement with automatic methods. Magdy et al [10] further compare the best two systems in CLEF-IP 2010.…”

Section: Related Workmentioning

confidence: 99%

On Term Selection Techniques for Patent Prior Art Search

Far

Sanner

Bouadjenek

et al. 2015

Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval

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In this paper, we investigate the influence of term selection on retrieval performance on the CLEF-IP prior art test collection, using the Description section of the patent query with Language Model (LM) and BM25 scoring functions. We find that an oracular relevance feedback system that extracts terms from the judged relevant documents far outperforms the baseline and performs twice as well on MAP as the best competitor in CLEF-IP 2010. We find a very clear term selection value threshold for use when choosing terms. We also noticed that most of the useful feedback terms are actually present in the original query and hypothesized that the baseline system could be substantially improved by removing negative query terms. We tried four simple automated approaches to identify negative terms for query reduction but we were unable to notably improve on the baseline performance with any of them. However, we show that a simple, minimal interactive relevance feedback approach where terms are selected from only the first retrieved relevant document outperforms the best result from CLEF-IP 2010 suggesting the promise of interactive methods for term selection in patent prior art search.

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A study of query reformulation for patent prior art search with partial patent applications

Cited by 13 publications

References 19 publications

Effect of Technical Domains and Patent Structure on Patent Information Retrieval

Effect of Technical Domains and Patent Structure on Patent Information Retrieval

Multi-field query expansion is effective for biomedical dataset retrieval

On Term Selection Techniques for Patent Prior Art Search

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