Query expansion based on predictive algorithms for collaborative filtering

K. Hoashi; K. Matsumoto; N. Inoue; K. Hashimoto

doi:10.1145/383952.384063

Query expansion based on predictive algorithms for collaborative filtering

K. Hoashi^*, K. Matsumoto, N. Inoue, K. Hashimoto

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

6 Citations (Scopus)

Abstract

A novel query expansion method based on predictive algorithms used for collaborative filtering was proposed. Query-document was considered as a measure to select the relevant document set and as an element of term weight calculation to improve retrieval performance. Collaborative filtering was used to predict the votes of a particular user from a database of user votes of other users. The object of predictive algorithms for collaborative filtering was to predict the values of empty elements of the active user.

Original language	English
Pages (from-to)	414-415
Number of pages	2
Journal	SIGIR Forum (ACM Special Interest Group on Information Retrieval)
DOIs	https://doi.org/10.1145/383952.384063
Publication status	Published - 2001
Externally published	Yes
Event	24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval - New Orleans, LA, United States Duration: 2001 Sept 9 → 2001 Sept 13

ASJC Scopus subject areas

Management Information Systems
Hardware and Architecture

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10.1145/383952.384063

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title = "Query expansion based on predictive algorithms for collaborative filtering",

abstract = "A novel query expansion method based on predictive algorithms used for collaborative filtering was proposed. Query-document was considered as a measure to select the relevant document set and as an element of term weight calculation to improve retrieval performance. Collaborative filtering was used to predict the votes of a particular user from a database of user votes of other users. The object of predictive algorithms for collaborative filtering was to predict the values of empty elements of the active user.",

author = "K. Hoashi and K. Matsumoto and N. Inoue and K. Hashimoto",

year = "2001",

doi = "10.1145/383952.384063",

language = "English",

pages = "414--415",

journal = "SIGIR Forum (ACM Special Interest Group on Information Retrieval)",

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publisher = "Association for Computing Machinery (ACM)",

note = "24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval ; Conference date: 09-09-2001 Through 13-09-2001",

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AU - Hoashi, K.

AU - Matsumoto, K.

AU - Inoue, N.

AU - Hashimoto, K.

PY - 2001

Y1 - 2001

N2 - A novel query expansion method based on predictive algorithms used for collaborative filtering was proposed. Query-document was considered as a measure to select the relevant document set and as an element of term weight calculation to improve retrieval performance. Collaborative filtering was used to predict the votes of a particular user from a database of user votes of other users. The object of predictive algorithms for collaborative filtering was to predict the values of empty elements of the active user.

AB - A novel query expansion method based on predictive algorithms used for collaborative filtering was proposed. Query-document was considered as a measure to select the relevant document set and as an element of term weight calculation to improve retrieval performance. Collaborative filtering was used to predict the votes of a particular user from a database of user votes of other users. The object of predictive algorithms for collaborative filtering was to predict the values of empty elements of the active user.

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U2 - 10.1145/383952.384063

DO - 10.1145/383952.384063

M3 - Conference article

AN - SCOPUS:0034799975

SN - 0163-5840

SP - 414

EP - 415

JO - SIGIR Forum (ACM Special Interest Group on Information Retrieval)

JF - SIGIR Forum (ACM Special Interest Group on Information Retrieval)

T2 - 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Y2 - 9 September 2001 through 13 September 2001

ER -

Query expansion based on predictive algorithms for collaborative filtering

Abstract

ASJC Scopus subject areas

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