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Article

Integrating automatic genre analysis into digital libraries

Authors:

Andreas Rauber,

Alexander Müller-KöglerAuthors Info & Claims

JCDL '01: Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries

Pages 1 - 10

https://doi.org/10.1145/379437.379439

Published: 01 January 2001 Publication History

Abstract

With the number and types of documents in digital library systems incr easing, tools for automatically organizing and presenting the content have to be found. While many approaches focus on topic-based organization and structuring, hardly any system incorporates automatic structural analysis and representation. Yet, genre information (unconsciously) forms one of the most distinguishing features in conventional libraries and in information searches. In this paper we present an approach to automatically analyze the structure of documents and to integrate this information into an automatically created content-based organization. In the resulting visualization, documents on similar topics, yet representing different genres, are depicted as books in differing colors. This representation supports users intuitively in locating relevant information presented in a relevant form.

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Cited By

Onan A(2018)An ensemble scheme based on language function analysis and feature engineering for text genre classificationJournal of Information Science10.1177/016555151667791144:1(28-47)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1177/0165551516677911
(2017)Fine-grained opinion mining of product review using sentiment and semantic orientationInternational Journal of Business Information Systems10.1504/IJBIS.2017.08327425:1(1-17)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1504/IJBIS.2017.083274
Dubey GRana ARanjan J(2016)A research study of sentiment analysis and various techniques of sentiment classificationInternational Journal of Data Analysis Techniques and Strategies10.1504/IJDATS.2016.0774858:2(122-142)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1504/IJDATS.2016.077485
Show More Cited By

Index Terms

Integrating automatic genre analysis into digital libraries
1. Applied computing
  1. Computers in other domains
    1. Digital libraries and archives
2. Information systems
  1. Information systems applications
    1. Digital libraries and archives

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Published In

cover image ACM Conferences

JCDL '01: Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries

January 2001

481 pages

ISBN:1581133456

DOI:10.1145/379437

Chairmen:
Edward A. Fox
Virginia Tech
,
Christine L. Borgman
UCLA

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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Publication History

Published: 01 January 2001

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JCDL01

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JCDL01: 1st ACM/IEEE-CS Joint Conference on Digital Libraries

Virginia, Roanoke, USA

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JCDL '01 Paper Acceptance Rate 76 of 250 submissions, 30%;

Overall Acceptance Rate 415 of 1,482 submissions, 28%

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Cited By

Onan A(2018)An ensemble scheme based on language function analysis and feature engineering for text genre classificationJournal of Information Science10.1177/016555151667791144:1(28-47)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1177/0165551516677911
(2017)Fine-grained opinion mining of product review using sentiment and semantic orientationInternational Journal of Business Information Systems10.1504/IJBIS.2017.08327425:1(1-17)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1504/IJBIS.2017.083274
Dubey GRana ARanjan J(2016)A research study of sentiment analysis and various techniques of sentiment classificationInternational Journal of Data Analysis Techniques and Strategies10.1504/IJDATS.2016.0774858:2(122-142)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1504/IJDATS.2016.077485
Singh MKurian J(2014)Evolving Digital CommunicationTechnological Advancements and the Impact of Actor-Network Theory10.4018/978-1-4666-6126-4.ch013(222-237)Online publication date: 2014
https://doi.org/10.4018/978-1-4666-6126-4.ch013
Singh MDwivedi YHackney RPeszynski K(2012)Innovation in CommunicationInternational Journal of Actor-Network Theory and Technological Innovation10.4018/jantti.20120101044:1(39-51)Online publication date: 1-Jan-2012
https://doi.org/10.4018/jantti.2012010104
Singh MHackney RDwivedi YPeszynski K(2012)Determining Dimensions of Social WebsitesProceedings of the 2012 45th Hawaii International Conference on System Sciences10.1109/HICSS.2012.205(1728-1736)Online publication date: 4-Jan-2012
https://dl.acm.org/doi/10.1109/HICSS.2012.205
Chen FGirgensohn ACooper MLu YFilby G(2012)Genre identification for office document search and browsingInternational Journal on Document Analysis and Recognition10.1007/s10032-011-0163-715:3(167-182)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/s10032-011-0163-7
Braslavski P(2010)Marrying Relevance and Genre Rankings: An Exploratory StudyGenres on the Web10.1007/978-90-481-9178-9_9(191-208)Online publication date: 16-Aug-2010
https://doi.org/10.1007/978-90-481-9178-9_9
Stein BEissen SLipka N(2010)Web Genre Analysis: Use Cases, Retrieval Models, and Implementation IssuesGenres on the Web10.1007/978-90-481-9178-9_8(167-189)Online publication date: 16-Aug-2010
https://doi.org/10.1007/978-90-481-9178-9_8
Kim YRoss S(2010)Formulating Representative Features with Respect to Genre ClassificationGenres on the Web10.1007/978-90-481-9178-9_6(129-147)Online publication date: 16-Aug-2010
https://doi.org/10.1007/978-90-481-9178-9_6
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