Article

Summarization as feature selection for text categorization

Authors:

Aleksander Kolcz,

Vidya Prabakarmurthi,

Jugal KalitaAuthors Info & Claims

CIKM '01: Proceedings of the tenth international conference on Information and knowledge management

Pages 365 - 370

https://doi.org/10.1145/502585.502647

Published: 05 October 2001 Publication History

Abstract

We address the problem of evaluating the effectiveness of summarization techniques for the task of document categorization. It is argued that for a large class of automatic categorization algorithms, extraction-based document categorization can be viewed as a particular form of feature selection performed on the full text of the document and, in this context, its impact can be compared with state-of-the-art feature selection techniques especially devised to provide good categorization performance. Such a framework provides for a better assessment of the expected performance of a categorizer if the compression rate of the summarizer is known.

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Cited By

Armano GGiuliani A(2018)Novel Text Summarization Techniques for Contextual AdvertisingInformation Retrieval and Management10.4018/978-1-5225-5191-1.ch038(883-903)Online publication date: 2018
https://doi.org/10.4018/978-1-5225-5191-1.ch038
Shen D(2018)Text CategorizationEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_414(4063-4067)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_414
Liu SChen KChen BWang HHsu W(2017)Leveraging manifold learning for extractive broadcast news summarization2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2017.7953269(5805-5809)Online publication date: Mar-2017
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Summarization as feature selection for text categorization

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Published In

cover image ACM Conferences

CIKM '01: Proceedings of the tenth international conference on Information and knowledge management

October 2001

616 pages

ISBN:1581134363

DOI:10.1145/502585

Editors:
Henrique Paques
Georgia Institute of Technology
,
Ling Liu
Georgia Institute of Technology
,
David Grossman
Illinois Institute of Technology
,
General Chair:
Calton Pu
Georgia Institute of Technology

Copyright © 2001 ACM.

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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Published: 05 October 2001

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October 5 - 10, 2001

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Cited By

Armano GGiuliani A(2018)Novel Text Summarization Techniques for Contextual AdvertisingInformation Retrieval and Management10.4018/978-1-5225-5191-1.ch038(883-903)Online publication date: 2018
https://doi.org/10.4018/978-1-5225-5191-1.ch038
Shen D(2018)Text CategorizationEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_414(4063-4067)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_414
Liu SChen KChen BWang HHsu W(2017)Leveraging manifold learning for extractive broadcast news summarization2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2017.7953269(5805-5809)Online publication date: Mar-2017
https://doi.org/10.1109/ICASSP.2017.7953269
Shen D(2017)Text CategorizationEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_414-2(1-4)Online publication date: 9-Jan-2017
https://doi.org/10.1007/978-1-4899-7993-3_414-2
Liu SChen KHsieh YChen BWang HYen HHsu W(2016)Exploiting graph regularized nonnegative matrix factorization for extractive speech summarization2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)10.1109/APSIPA.2016.7820883(1-7)Online publication date: Dec-2016
https://doi.org/10.1109/APSIPA.2016.7820883
Liu AXing CFeng YWang D(2016)Learning ordered word representations with γ-decay dropout2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)10.1109/APSIPA.2016.7820839(1-5)Online publication date: Dec-2016
https://doi.org/10.1109/APSIPA.2016.7820839
Liu JKang X(2016)Exposing heterogeneous chain of video recompression2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)10.1109/APSIPA.2016.7820694(1-6)Online publication date: Dec-2016
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Villatoro-Tello EAnguiano EMontes-y-Gómez MVillaseñor-Pineda LRamírez-de-la-Rosa G(2016)Enhancing Semi-supevised Text Classification Using Document SummariesAdvances in Artificial Intelligence - IBERAMIA 201610.1007/978-3-319-47955-2_10(115-126)Online publication date: 14-Oct-2016
https://doi.org/10.1007/978-3-319-47955-2_10
Liu SLee HHung HChen KChen BWang HYen HHsu W(2015)Incorporating proximity information in relevance language modeling for extractive speech summarization2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)10.1109/APSIPA.2015.7415303(401-407)Online publication date: Dec-2015
https://doi.org/10.1109/APSIPA.2015.7415303
Armano GGiuliani A(2014)Novel Text Summarization Techniques for Contextual AdvertisingInnovative Document Summarization Techniques10.4018/978-1-4666-5019-0.ch008(185-204)Online publication date: 2014
https://doi.org/10.4018/978-1-4666-5019-0.ch008
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