Improving Retrievability of Patents in Prior-Art Search

Bashir, Shariq; Rauber, Andreas

doi:10.1007/978-3-642-12275-0_40

Cited by 63 publications

(54 citation statements)

References 18 publications

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“…While the studies performed by Wilkie and Azzopardi were conducted in the domain of ad hoc web and news search, Bashir and Rauber have performed studies investigating retrievability bias in the patent retrieval domain [3,5]. In these studies, the authors find a stronger link between recall and retrievability bias than what was observed by Wilkie and Azzopardi in ad-hoc search.…”

Section: Introductionmentioning

confidence: 93%

“…Experiment 4: Altering the Number of Documents for Expansion The final experiment follows the same method as Experiment 3 however, the number of documents that terms are extracted from are altered. 10 terms are extracted from a varying number from the top x documents (1,2,3,4,5,6,7,8,9,10,12,15,20,25,50). …”

Section: Experiments 3: Altering the Number Of Terms For Expansionmentioning

confidence: 99%

“…where q is a query from the large query set Q. k dq is the rank at which d is retrieved given q, therefore the utility function f (k dq , c) determines the score that document d attains for query q given the rank cutoff c. r(d) is calculated by summing over all queries q in query set Q. Theoretically, Q represents the universe of all possible queries, but in practice Q is very large set of queries [1,2,4,5,10]. The standard measure of retrievability used employs the utility function f (k dq , c), such that if a document, d, is retrieved in the top c documents given q, then f (k dq , c) = 1, otherwise f (k dq , c) = 0.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Initial Investigation of Query Expansion Bias

Wilkie

Azzopardi

2017

Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval

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Query expansion is a useful retrieval mechanism for creating more verbose queries from the users initial key word search. Query expansion generally have multiple parameters that allow the user to define how many terms and where those terms come from are introduced to the expanded query. However, the idea that query expansion may be introducing biases into the system by selecting terms from overly retrievable documents has never been formally evaluated. In this work, the relationship between performance and retrievability bias is explored when various query expansion methods are employed to aide retrieval. Several parameters are altered, independently, to identify those that have an impact on bias. Parameters altered include; Rocchio's beta, length normalisation parameters, the number of terms added and the number of documents those terms are extracted from. The evaluation performed here identifies a strong correlation between performance and retrievability bias, suggesting that performance is increased by making the system more biased thus more likely to pick terms from a set of overly retrievable documents.

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Section: Introductionmentioning

confidence: 93%

Section: Experiments 3: Altering the Number Of Terms For Expansionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Initial Investigation of Query Expansion Bias

Wilkie

Azzopardi

2017

Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval

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“…In the following, we discuss a few studies that used retrievability. Retrievability was applied in the patent search domain [8,11], which is recall-oriented, to quantify the retrieval bias of retrieval systems on the patent collection. The correlation between retrievability and the query set was considered in several studies.…”

Section: Related Workmentioning

confidence: 99%

Quantifying retrieval bias in Web archive search

et al. 2017

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A Web archive usually contains multiple versions of documents crawled from the Web at different points in time. One possible way for users to access a Web archive is through full-text search systems. However, previous studies have shown that these systems can induce a bias, known as the retrievability bias, on the accessibility of documents in community-collected collections (such as TREC collections). This bias can be measured by analyzing the distribution of the retrievability scores for each document in a collection, quantifying the likelihood of a document's retrieval. We investigate the suitability of retrievability scores in retrieval systems that consider every version of a document in a Web archive as an independent document. We show that the retrievability of documents can vary for different versions of the same document and that retrieval systems induce biases to different extents. We quantify this bias for a retrieval system which is adapted to handle multiple versions of the same document. The retrieval system indexes each version of a document independently, and we refine the search results using two techniques to aggregate similar versions. The first approach is to collapse similar versions of a document based on content similarity. The second approach is to collapse all versions of the same document based on their URLs. In both cases, we found that the degree of bias Universiteit Utrecht, Utrecht, The Netherlands is related to the aggregation level of versions of the same document. Finally, we study the effect of bias across time using the retrievability measure. Specifically, we investigate whether the number of documents crawled in a particular year correlates with the number of documents in the search results from that year. Assuming queries are not inherently temporal in nature, the analysis is based on the timestamps of documents in the search results returned using the retrieval model for all queries. The results show a relation between the number of documents per year and the number of documents retrieved by the retrieval system from that year. We further investigated the relation between the queries' timestamps and the documents' timestamps. First, we split the queries into different time frames using a 1-year granularity. Then, we issued the queries against the retrieval system. The results show that temporal queries indeed retrieve more documents from the assumed time frame. Thus, the documents from the same time frame were preferred by the retrieval system over documents from other time frames.

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“…The patent retrievability is increased in [2] by using the Prior -Art method. Patent queries are generated by using pseudo relevance feedback with query expansion.…”

Section: Related Workmentioning

confidence: 99%