A new suffix tree similarity measure for document clustering

Hung Chim; Xiaotie Deng

doi:10.1145/1242572.1242590

A new suffix tree similarity measure for document clustering

Hung Chim
, Xiaotie Deng

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

90 Citations (Scopus)

Abstract

In this paper, we propose a new similarity measure to compute the pairwise similarity of text-based documents based on suffix tree document model. By applying the new suffix tree similarity measure in Group-average Agglomerative Hierarchical Clustering (GAHC) algorithm, we developed a new suffix tree document clustering algorithm (NSTC). Experimental results on two standard document clustering benchmark corpus OHSUMED and RCV1 indicate that the new clustering algorithm is a very effective document clustering algorithm. Comparing with the results of traditional word term weight tf-idf similarity measure in the same GAHC algorithm, NSTC achieved an improvement of 51% on the average of F-measure score. Furthermore, we apply the new clustering algorithm in analyzing the Web documents in online forum communities. A topic oriented clustering algorithm is developed to help people in assessing, classifying and searching the the Web documents in a large forum community.
Copyright is held by the International World Wide Web Conference Committee (IW3C2).

Original language	English
Title of host publication	16th International World Wide Web Conference, WWW2007
Pages	121-130
DOIs	https://doi.org/10.1145/1242572.1242590
Publication status	Published - 2007
Event	16th International World Wide Web Conference, WWW2007 - Banff, AB, Canada Duration: 8 May 2007 → 12 May 2007

Publication series

Name	16th International World Wide Web Conference, WWW2007

Conference

Conference	16th International World Wide Web Conference, WWW2007
Place	Canada
City	Banff, AB
Period	8/05/07 → 12/05/07

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

The research work described in this paper is partially supported by a City University TDF grant [Project No. 6980080] and a SRG grant of City University of Hong Kong [Project No. 7001975].

Research Keywords

Document model
Similarity measure
Suffix tree

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10.1145/1242572.1242590

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title = "A new suffix tree similarity measure for document clustering",

abstract = "In this paper, we propose a new similarity measure to compute the pairwise similarity of text-based documents based on suffix tree document model. By applying the new suffix tree similarity measure in Group-average Agglomerative Hierarchical Clustering (GAHC) algorithm, we developed a new suffix tree document clustering algorithm (NSTC). Experimental results on two standard document clustering benchmark corpus OHSUMED and RCV1 indicate that the new clustering algorithm is a very effective document clustering algorithm. Comparing with the results of traditional word term weight tf-idf similarity measure in the same GAHC algorithm, NSTC achieved an improvement of 51\% on the average of F-measure score. Furthermore, we apply the new clustering algorithm in analyzing the Web documents in online forum communities. A topic oriented clustering algorithm is developed to help people in assessing, classifying and searching the the Web documents in a large forum community. Copyright is held by the International World Wide Web Conference Committee (IW3C2).",

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note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].; 16th International World Wide Web Conference, WWW2007 ; Conference date: 08-05-2007 Through 12-05-2007",

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A new suffix tree similarity measure for document clustering. / Chim, Hung; Deng, Xiaotie.
16th International World Wide Web Conference, WWW2007. 2007. p. 121-130 (16th International World Wide Web Conference, WWW2007).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - Chim, Hung

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PY - 2007

Y1 - 2007

N2 - In this paper, we propose a new similarity measure to compute the pairwise similarity of text-based documents based on suffix tree document model. By applying the new suffix tree similarity measure in Group-average Agglomerative Hierarchical Clustering (GAHC) algorithm, we developed a new suffix tree document clustering algorithm (NSTC). Experimental results on two standard document clustering benchmark corpus OHSUMED and RCV1 indicate that the new clustering algorithm is a very effective document clustering algorithm. Comparing with the results of traditional word term weight tf-idf similarity measure in the same GAHC algorithm, NSTC achieved an improvement of 51% on the average of F-measure score. Furthermore, we apply the new clustering algorithm in analyzing the Web documents in online forum communities. A topic oriented clustering algorithm is developed to help people in assessing, classifying and searching the the Web documents in a large forum community. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

AB - In this paper, we propose a new similarity measure to compute the pairwise similarity of text-based documents based on suffix tree document model. By applying the new suffix tree similarity measure in Group-average Agglomerative Hierarchical Clustering (GAHC) algorithm, we developed a new suffix tree document clustering algorithm (NSTC). Experimental results on two standard document clustering benchmark corpus OHSUMED and RCV1 indicate that the new clustering algorithm is a very effective document clustering algorithm. Comparing with the results of traditional word term weight tf-idf similarity measure in the same GAHC algorithm, NSTC achieved an improvement of 51% on the average of F-measure score. Furthermore, we apply the new clustering algorithm in analyzing the Web documents in online forum communities. A topic oriented clustering algorithm is developed to help people in assessing, classifying and searching the the Web documents in a large forum community. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

KW - Document model

KW - Similarity measure

KW - Suffix tree

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ER -

A new suffix tree similarity measure for document clustering

Abstract

Publication series

Conference

Bibliographical note

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Research Keywords

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