Article

Graph-based text database for knowledge discovery

Authors:

Junji Tomita,

Hidekazu Nakawatase,

Megumi IshiiAuthors Info & Claims

WWW Alt. '04: Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters

Pages 454 - 455

https://doi.org/10.1145/1013367.1013522

Published: 19 May 2004 Publication History

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Abstract

While we expect to discover knowledge in the texts available on the Web, such discovery usually requires many complex analysis steps, most of which require different text handling operations such as similar text search or text clustering. Drawing an analogy from the relational data model, we propose a text representation model that simplifies the steps. The model represents texts in a formal manner, Subject Graphs, described herein, provides text handling operations whose inputs and outputs are identical in form, i.e. a set of subject graphs. We develop a graph-based text database, which is based on the model, and an interactive knowledge discovery system. Trials of the system show that it allows the user to interactively and intuitively discover knowledge in Web pages by combining text handling operations defined on subject graphs in various orders.

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Cited By

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Nguyen TDo P(2018)Topic Discovery Using Frequent Subgraph Mining ApproachComputational Science and Technology10.1007/978-981-10-8276-4_41(432-442)Online publication date: 24-Feb-2018
https://doi.org/10.1007/978-981-10-8276-4_41
Nguyen THoang K(2009)Frequent Subgraph-Based Approach for Classifying Vietnamese Text DocumentsEnterprise Information Systems10.1007/978-3-642-01347-8_25(299-308)Online publication date: 2009
https://doi.org/10.1007/978-3-642-01347-8_25
Phuc DHung M(2008)Using SOM based graph clustering for extracting main ideas from documents2008 IEEE International Conference on Research, Innovation and Vision for the Future in Computing and Communication Technologies10.1109/RIVF.2008.4586357(209-214)Online publication date: Jul-2008
https://doi.org/10.1109/RIVF.2008.4586357
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Index Terms

Graph-based text database for knowledge discovery
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing
    2. Retrieval models and ranking

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Published In

WWW Alt. '04: Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters

May 2004

532 pages

ISBN:1581139128

DOI:10.1145/1013367

Conference Chairs:
Stuart Feldman
IBM Research
,
Mike Uretsky
New York University
,
Program Chairs:
Marc Najork
Microsoft Research
,
Craig Wills
Worcester Polytechnic Institute

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 19 May 2004

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WWW04: The 2004 World Wide Web Conference ( in conjunction with ACM Conference on Electronic Commerce [EC'04])

May 19 - 21, 2004

NY, New York, USA

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Nguyen TDo P(2018)Topic Discovery Using Frequent Subgraph Mining ApproachComputational Science and Technology10.1007/978-981-10-8276-4_41(432-442)Online publication date: 24-Feb-2018
https://doi.org/10.1007/978-981-10-8276-4_41
Nguyen THoang K(2009)Frequent Subgraph-Based Approach for Classifying Vietnamese Text DocumentsEnterprise Information Systems10.1007/978-3-642-01347-8_25(299-308)Online publication date: 2009
https://doi.org/10.1007/978-3-642-01347-8_25
Phuc DHung M(2008)Using SOM based graph clustering for extracting main ideas from documents2008 IEEE International Conference on Research, Innovation and Vision for the Future in Computing and Communication Technologies10.1109/RIVF.2008.4586357(209-214)Online publication date: Jul-2008
https://doi.org/10.1109/RIVF.2008.4586357
Tomita JNakawatase HIshii MGrossman DGravano LZhai CHerzog OEvans D(2004)Calculating similarity between texts using graph-based text representation modelProceedings of the thirteenth ACM international conference on Information and knowledge management10.1145/1031171.1031226(248-249)Online publication date: 13-Nov-2004
https://dl.acm.org/doi/10.1145/1031171.1031226

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Graph-based text representation and knowledge discovery

Optimization of knowledge discovery process using domain knowledge

Knowledge discovery of frequent itemsets with low utility for revenue analysis

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