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Belkin, N.J.; Croft, W.B.: Retrieval techniques (1987) 0.02

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Source: Annual review of information science and technology. 22(1987), S.109-145

Allan, J.; Callan, J.P.; Croft, W.B.; Ballesteros, L.; Broglio, J.; Xu, J.; Shu, H.: INQUERY at TREC-5 (1997) 0.01

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Date: 27. 2.1999 20:55:22

Croft, W.B.: Advances in information retrieval : Recent research from the Center for Intelligent Information Retrieval (2000) 0.01
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Content

Enthält die Beiträge: CROFT, W.B.: Combining approaches to information retrieval; GREIFF, W.R.: The use of exploratory data analysis in information retrieval research; PONTE, J.M.: Language models for relevance feedback; PAPKA, R. u. J. ALLAN: Topic detection and tracking: event clustering as a basis for first story detection; CALLAN, J.: Distributed information retrieval; XU, J. u. W.B. CROFT: Topic-based language models for ditributed retrieval; LU, Z. u. K.S. McKINLEY: The effect of collection organization and query locality on information retrieval system performance; BALLESTEROS, L.A.: Cross-language retrieval via transitive translation; SANDERSON, M. u. D. LAWRIE: Building, testing, and applying concept hierarchies; RAVELA, S. u. C. LUO: Appearance-based global similarity retrieval of images

Type

m

Croft, W.B.; Metzler, D.; Strohman, T.: Search engines : information retrieval in practice (2010) 0.00

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Type: m

Tavakoli, L.; Zamani, H.; Scholer, F.; Croft, W.B.; Sanderson, M.: Analyzing clarification in asynchronous information-seeking conversations (2022) 0.00

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Kim, Y.; Seo, J.; Croft, W.B.; Smith, D.A.: Automatic suggestion of phrasal-concept queries for literature search (2014) 0.00
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Abstract

Both general and domain-specific search engines have adopted query suggestion techniques to help users formulate effective queries. In the specific domain of literature search (e.g., finding academic papers), the initial queries are usually based on a draft paper or abstract, rather than short lists of keywords. In this paper, we investigate phrasal-concept query suggestions for literature search. These suggestions explicitly specify important phrasal concepts related to an initial detailed query. The merits of phrasal-concept query suggestions for this domain are their readability and retrieval effectiveness: (1) phrasal concepts are natural for academic authors because of their frequent use of terminology and subject-specific phrases and (2) academic papers describe their key ideas via these subject-specific phrases, and thus phrasal concepts can be used effectively to find those papers. We propose a novel phrasal-concept query suggestion technique that generates queries by identifying key phrasal-concepts from pseudo-labeled documents and combines them with related phrases. Our proposed technique is evaluated in terms of both user preference and retrieval effectiveness. We conduct user experiments to verify a preference for our approach, in comparison to baseline query suggestion methods, and demonstrate the effectiveness of the technique with retrieval experiments.

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