Using longest common subsequence matching for Chinese information retrieval

Xiao Yun; Wing Pong Robert Luk; K. F. Wong; K. L. Kwok

Using longest common subsequence matching for Chinese information retrieval

Xiao Yun, Wing Pong Robert Luk, K. F. Wong, K. L. Kwok

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

This paper is about adopting the longest common subsequence (LCS) matching for Chinese information retrieval. We re-ranked the retrieved documents by a mixture of the original similarity score and the LCS score obtained by matching the document titles and the query. This LCS-based similarity score is also used in pseudo-relevance feedback in various ways (e.g., selecting terms and filtering documents with low LCS values). We evaluated the use of LCS in title re-ranking and PRF based on the NTCIR-4 test collection for Chinese ad hoc information retrieval. For title queries, our best MAP achieved is 26.7% evaluated using rigid relevance judgement and 30.2% evaluated using relax relevance judgement.

Original language	English
Title of host publication	Proceedings of the International Conference on Chinese Computing 2005, ICCC 2005
Publisher	Chinese and Oriental Languages Information Processing Society (COLIPS)
ISBN (Electronic)	9789810530075, 9810530072
Publication status	Published - 1 Jan 2005
Event	International Conference on Chinese Computing 2005, ICCC 2005 - Singapore, Singapore Duration: 21 Mar 2005 → 23 Mar 2005

Conference

Conference	International Conference on Chinese Computing 2005, ICCC 2005
Country/Territory	Singapore
City	Singapore
Period	21/03/05 → 23/03/05

ASJC Scopus subject areas

General Computer Science

Cite this

@inproceedings{3a46a4e3db9a432f860a83cd28e4a4eb,

title = "Using longest common subsequence matching for Chinese information retrieval",

abstract = "This paper is about adopting the longest common subsequence (LCS) matching for Chinese information retrieval. We re-ranked the retrieved documents by a mixture of the original similarity score and the LCS score obtained by matching the document titles and the query. This LCS-based similarity score is also used in pseudo-relevance feedback in various ways (e.g., selecting terms and filtering documents with low LCS values). We evaluated the use of LCS in title re-ranking and PRF based on the NTCIR-4 test collection for Chinese ad hoc information retrieval. For title queries, our best MAP achieved is 26.7% evaluated using rigid relevance judgement and 30.2% evaluated using relax relevance judgement.",

author = "Xiao Yun and Luk, {Wing Pong Robert} and Wong, {K. F.} and Kwok, {K. L.}",

year = "2005",

month = jan,

day = "1",

language = "English",

booktitle = "Proceedings of the International Conference on Chinese Computing 2005, ICCC 2005",

publisher = "Chinese and Oriental Languages Information Processing Society (COLIPS)",

note = "International Conference on Chinese Computing 2005, ICCC 2005 ; Conference date: 21-03-2005 Through 23-03-2005",

}

Yun, X, Luk, WPR, Wong, KF & Kwok, KL 2005, Using longest common subsequence matching for Chinese information retrieval. in Proceedings of the International Conference on Chinese Computing 2005, ICCC 2005. Chinese and Oriental Languages Information Processing Society (COLIPS), International Conference on Chinese Computing 2005, ICCC 2005, Singapore, Singapore, 21/03/05.

Using longest common subsequence matching for Chinese information retrieval. / Yun, Xiao; Luk, Wing Pong Robert; Wong, K. F. et al.
Proceedings of the International Conference on Chinese Computing 2005, ICCC 2005. Chinese and Oriental Languages Information Processing Society (COLIPS), 2005.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Using longest common subsequence matching for Chinese information retrieval

AU - Yun, Xiao

AU - Luk, Wing Pong Robert

AU - Wong, K. F.

AU - Kwok, K. L.

PY - 2005/1/1

Y1 - 2005/1/1

N2 - This paper is about adopting the longest common subsequence (LCS) matching for Chinese information retrieval. We re-ranked the retrieved documents by a mixture of the original similarity score and the LCS score obtained by matching the document titles and the query. This LCS-based similarity score is also used in pseudo-relevance feedback in various ways (e.g., selecting terms and filtering documents with low LCS values). We evaluated the use of LCS in title re-ranking and PRF based on the NTCIR-4 test collection for Chinese ad hoc information retrieval. For title queries, our best MAP achieved is 26.7% evaluated using rigid relevance judgement and 30.2% evaluated using relax relevance judgement.

AB - This paper is about adopting the longest common subsequence (LCS) matching for Chinese information retrieval. We re-ranked the retrieved documents by a mixture of the original similarity score and the LCS score obtained by matching the document titles and the query. This LCS-based similarity score is also used in pseudo-relevance feedback in various ways (e.g., selecting terms and filtering documents with low LCS values). We evaluated the use of LCS in title re-ranking and PRF based on the NTCIR-4 test collection for Chinese ad hoc information retrieval. For title queries, our best MAP achieved is 26.7% evaluated using rigid relevance judgement and 30.2% evaluated using relax relevance judgement.

UR - http://www.scopus.com/inward/record.url?scp=85026857577&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

BT - Proceedings of the International Conference on Chinese Computing 2005, ICCC 2005

PB - Chinese and Oriental Languages Information Processing Society (COLIPS)

T2 - International Conference on Chinese Computing 2005, ICCC 2005

Y2 - 21 March 2005 through 23 March 2005

ER -

Using longest common subsequence matching for Chinese information retrieval

Abstract

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ASJC Scopus subject areas

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