Open Access
A Multiple-Document Summarization System Introducing User Interaction for Reflecting User's Summarization Need
Hiroyuki Sakai,Shigeru Masuyama +1 more
- 01 Jan 2004
TL;DR: A multiple-document summarization system with user interaction that summarizes more than one document to a document and showsk best keywords with respect to scoring by the system to a user on the screen.
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Abstract: We propose a multiple-document summarization system with user interaction that summarizes more than one document to a document. Our system extracts keywords from sets of documents to be summarized and showsk best keywords with respect to scoring by our system to a user on the screen. From the shown keywords, the user selects those reflecting the user’s summarization need. Our system controls the produced summary by using these selected keywords. For evaluation of our method, we participated in TSC3 of NTCIR4 workshop by letting our system select allk
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Citations
What Makes a Good Summary
Qunhua Zhao,Eugene Santos,Hien Nguyen,Ahmed A. Mohamed +3 more
- 01 Jan 2009
TL;DR: An experimental study on the sensitivity of users to the quality and content of multi-document summarization and a new metric based on document graphs that can distinguish between the two types of document sets are presented.
3
Information Extraction from Heterogenous Web Sites Using Additional Search of Related Contents Based on a User's Instantiated Example
Yuki Mitsui,Hironori Oka,Masanori Akiyoshi,Norihisa Komoda +3 more
- 01 Jan 2010
TL;DR: This work addressed a generation method of table-style data from heterogeneous Webpages that reflects a user’s intention and applies this method to shopping sites and the experimental result shows it improves recall rate.
1
Analyse d'évaluations en résumé automatique : proposition d'une terminologie française, description des paramètres expérimentaux et recommandations
Marie-Josée Goulet
- 01 Jan 2008
TL;DR: In this article, the authors define a set of terms, e.g., summary, abstract, and electronic abstract, which can be used to distinguish between a summary and an abstract.
1
A generation method of table-style data from Web retrieval results based on a user's instantiated example
Junya Shimada,Kyosuke Itoh,Hironori Oka,Masanori Akiyoshi +3 more
- 13 Jul 2010
TL;DR: This paper addresses a generation method of table-style data from heterogeneous Web pages that reflects a user's intention and applies it to travel tour pages.
1
Information Extraction from Heterogeneous Web Sites Using Clue Complement Process Based on a User’s Instantiated Example
Junya Shimada,Hironori Oka,Masanori Akiyoshi,Norihisa Komoda +3 more
- 01 Jan 2010
TL;DR: This paper addresses a generation method of table-style data from heterogeneous Web pages that reflects a user’s intention and applies this method to 57 pages with 27 travel agencies to see whether the proposed method is effective or not.
1
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Ricardo Baeza-Yates,Berthier Ribeiro-Neto +1 more
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TL;DR: In this article, the authors present a rigorous and complete textbook for a first course on information retrieval from the computer science (as opposed to a user-centred) perspective, which provides an up-to-date student oriented treatment of the subject.
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Information Fusion in the Context of Multi-Document Summarization
Regina Barzilay,Kathleen R. McKeown,Michael Elhadad +2 more
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TL;DR: This approach is unique in its usage of language generation to reformulate the wording of the summary by identifying and synthesizing similar elements across related text from a set of multiple documents.
Multi-document summarization by sentence extraction
Jade Goldstein,Vibhu Mittal,Jaime G. Carbonell,Mark Kantrowitz +3 more
- 30 Apr 2000
TL;DR: This paper discusses a text extraction approach to multi- document summarization that builds on single-document summarization methods by using additional, available information about the document set as a whole and the relationships between the documents.