Partial coordination. I. The best of pre-coordination and post-coordination

Bodoff, David; Kambil, Ajit

doi:10.1002/(sici)1097-4571(1998)49:14<1254::aid-asi4>3.0.co;2-o

Cited by 9 publications

(7 citation statements)

References 36 publications

(37 reference statements)

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“…There may be several types of out-of-context matches causing false drops. In [Bodoff and Kambil 1998], for instance, five types were identified: polysemy, ordered relationships among terms (e.g., 'wars due to crises' versus 'crises due to wars'), out of phrase terms (i.e., when a query or document phrase is not treated as a single unit), secondary topic keyword (e.g., 'siamese cats' versus 'cats') and non-categorical terms (e.g., 'tiger' is simultaneously an instance of 'mammal' and of 'operating system').…”

Section: Why and When Aqe Workmentioning

confidence: 99%

A Survey of Automatic Query Expansion in Information Retrieval

2012

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The relative ineffectiveness of information retrieval systems is largely caused by the inaccuracy with which a query formed by a few keywords models the actual user information need. One well known method to overcome this limitation is automatic query expansion (AQE), whereby the user's original query is augmented by new features with a similar meaning. AQE has a long history in the information retrieval community but it is only in the last years that it has reached a level of scientific and experimental maturity, especially in laboratory settings such as TREC. This survey presents a unified view of a large number of recent approaches to AQE that leverage various data sources and employ very different principles and techniques. The following questions are addressed: Why is query expansion so important to improve search effectiveness? What are the main steps involved in the design and implementation of an AQE component? What approaches to AQE are available and how do they compare? Which issues must still be resolved before AQE becomes a standard component of large operational information retrieval systems (e.g., search engines)?

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Section: Why and When Aqe Workmentioning

confidence: 99%

A Survey of Automatic Query Expansion in Information Retrieval

2012

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“…Another method of enrichment would be adding tables of contents to the bibliographic record-in effect adding more keywords (Bodoff and Kambil 1998). But this method does not direct the user toward controlled vocabulary.…”

Section: (3) Lrtsmentioning

confidence: 99%

“Garbage” In, “Refuse and Refuse Disposal” Out

Horn¹

2002

Library Resources &Amp; Technical Services

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“…2 To deal with this problem we may use contextual information on the query terms. Bodoff and Kambil [3], for instance, suggested using cataloger-provided dependencies between the subject terms of the documents being searched. Another way of obtaining contextual information is to have the user express Boolean constraints over the set of query terms to indicate which terms cover which aspects of the query, e.g., the constraint (A OR B) AND (C OR D) specifies two aspects of the query, each represented by two keywords [11].…”

Section: Exact Matching Retrievalmentioning

confidence: 99%

“…The documents were thus ranked according to the order chosen by the user to select the views. 3 Documents contained in more views were ranked based on the earliest view in which they occurred. In this way we obtained a partly-ordered retrieval output; we further ranked the (equally-ranked) documents within each view by using the ranking produced by AltaVista for those documents.…”

Section: Implementation Of Ranking Systemsmentioning

confidence: 99%

Effectiveness of Keyword-Based Display and Selection of Retrieval Results for Interactive Searches

Berenci

Carpineto

Giannini

et al. 1999

Research and Advanced Technology for Digital Libraries

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Abstract. We present an approach to increasing the effectiveness of rankedoutput retrieval systems that relies on graphical display and user manipulation of "views" of retrieval results, where a view is the subset of retrieved documents that contain a specified subset of query terms. This approach has been implemented in a system named VIEWER (VIEwing WEb Results), acting as an interface to available search engines. An experimental evaluation of the performance of VIEWER in contrast to AltaVista is the major focus of the paper. We first report the results of an experiment on single, short query searches where VIEWER, used as an interactive ranking system, markedly outperformed AltaVista. We then concentrate on a more realistic searching scenario, involving free query formulation, unconstrained selection of retrieval results, and possibility of query reformulation. We report the results of an experiment where the use of VIEWER, compared to AltaVista, seemed to shift the user effort from inspection to evaluation of results, increasing retrieval effectiveness and user satisfaction. In particular, we found that the VIEWER users retrieved half as many nonrelevant documents as the AltaVista users while retrieving a comparable number of relevant documents.

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Partial coordination. I. The best of pre-coordination and post-coordination

Cited by 9 publications

References 36 publications

A Survey of Automatic Query Expansion in Information Retrieval

A Survey of Automatic Query Expansion in Information Retrieval

“Garbage” In, “Refuse and Refuse Disposal” Out

Effectiveness of Keyword-Based Display and Selection of Retrieval Results for Interactive Searches

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