Query expansion using associated queries

Billerbeck, Bodo; Scholer, Falk; Williams, Hugh E.; Zobel, Justin

doi:10.1145/956863.956866

Cited by 85 publications

(35 citation statements)

References 15 publications

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“…Though, their systems failed to offer a satisfactory evaluation to score and rank the retrieved information constantly. • (iii) As discussed by Lin et al (2006), Billerbeck et al (2003) and Kim et al (2001), query expansion afforded system users with relevant results from online users) feedback. However, highlighted below are the major flaws:…”

Section: Issues To Be Resolved By the Conceptmentioning

confidence: 99%

A Novel Document Ranking Algorithm That Supports Mobile Healthcare Information Access Effectiveness

Agbele¹,

Adesina²,

Azeez³

et al. 2011

Research J. of Information Technology

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This study presented DROPT; an acronym for Document ranking Optmization algorithm approach, a new idea for the effectiveness of meaningful retrieval results from the information source. Proposed method extracted the frequency of query keyword terms that appears within the user context of Frequently Asked Questions (FAQ) systems on HIV/AIDS content relateddocuments. The SMS messages were analyzed and then classified, with the aim of constructing a corpus of SMS related to HIV/AIDS. This study presented a novel framework of Information Retrieval Systems (IRS) based on the proposed algorithm. The developed DROPT procedure was used as an evaluation measure. This "Term Frequency-Inverse Document Frequency (TFIDF)" method was applied to obtain the experimental result that was found promising in ranking documents not only the order in which the relevant documents were retrieved, but also both the terms of the relevant documents in feedback and the terms of the irrelevant documents in feedback might be useful for relevance feedback, especially to define its fitness function (mean weight).

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Section: Issues To Be Resolved By the Conceptmentioning

confidence: 99%

A Novel Document Ranking Algorithm That Supports Mobile Healthcare Information Access Effectiveness

Agbele¹,

Adesina²,

Azeez³

et al. 2011

Research J. of Information Technology

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show abstract

“…During recent years several techniques that formulate queries from the user context have been proposed [7,21]. Other methods support the query expansion and refinement process through a query or browsing interface requiring explicit user intervention [35,4]. Limited work, however, has been done on methods that simultaneously take advantage of the user context and results returned from a corpus to refine queries.…”

Section: Query Refinement and Context-based Retrievalmentioning

confidence: 99%

Evolving Disjunctive and Conjunctive Topical Queries based on Multi-objective Optimization Criteria

Cecchini¹,

Lorenzetti²,

Maguitman³

2010

Int. Artif.

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In this work we propose techniques based on single-and multi-objective evolutionary algorithms to automatically evolve a population of topical queries. The developed techniques can be applied in the implementation of a topical search system. We report on the results of different strategies that attempt to evolve conjunctive and disjunctive queries. Our analysis reveals the limitations of the single-objective approach and highlights the advantages of applying multi-objective evolutionary algorithms for the problem at hand. In addition, we observe that disjunctive queries have the potential to achieve better retrieval performance than conjunctive queries. Finally, we show that the multi-objective evolutionary approach results in better performance than a baseline and other state-of-the-art techniques for query refinement.

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“…This approach has been shown to be effective on some collections, but results on large collections of web data have been mixed. The work in [8] chooses expansion terms from past user queries directly, rather than using them to construct sets of full text documents from which terms are then selected. The method consists of three phases: ranking the original query against the collection of documents; extracting additional query terms from the highly ranked items; then ranking the new query against the collection.…”

Section: Related Workmentioning

confidence: 99%

Ontology Driven Query Expansion for Better Image Retrieval

Gulati¹,

Sharma²

2010

IJCA

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As more information becomes available on the Web it is more difficult to provide effective search services for Internet users. Since, it is assumed that users do not always formulate search queries using the best terms. So, search engines invoke query expansion to increase the quality of user search results. Query expansion is useful in reducing query/document mismatch by expanding the query using words or phrases with a similar meaning or some other statistical relation to the set of relevant documents. This paper proposes an approach for ontology driven query expansion for better image retrieval. In this work the association rules; generated by mining web logs and WorldNet have been used for query expansion process. Further, an algorithm has been proposed and the performance has been measured.

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Query expansion using associated queries

Cited by 85 publications

References 15 publications

A Novel Document Ranking Algorithm That Supports Mobile Healthcare Information Access Effectiveness

A Novel Document Ranking Algorithm That Supports Mobile Healthcare Information Access Effectiveness

Evolving Disjunctive and Conjunctive Topical Queries based on Multi-objective Optimization Criteria

Ontology Driven Query Expansion for Better Image Retrieval

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