poster

Keyword extraction for social snippets

Authors:

Zhenhui Li,

Ding Zhou,

Yun-Fang Juan,

Jiawei HanAuthors Info & Claims

WWW '10: Proceedings of the 19th international conference on World wide web

Pages 1143 - 1144

https://doi.org/10.1145/1772690.1772845

Published: 26 April 2010 Publication History

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Abstract

Today, a huge amount of text is being generated for social purposes on social networking services on the Web. Unlike traditional documents, such text is usually extremely short and tends to be informal. Analysis of such text benefit many applications such as advertising, search, and content filtering. In this work, we study one traditional text mining task on such new form of text, that is extraction of meaningful keywords. We propose several intuitive yet useful features and experiment with various classification models. Evaluation is conducted on Facebook data. Performances of various features and models are reported and compared.

References

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J. Friedman. Greedy function approximation: A gradient boosting machine. In Annals of Statistics 29(5), 2001.

Crossref

Google Scholar

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W. tau Yih, J. Goodman, and V. R. Carvalho. Finding advertising keywords on web pages. In WWW, 2006.

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P. D. Turney. Learning algorithms for keyphrase extraction. Information Retrieval, 2000.

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Cited By

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Zengeya TFonou Dombeu JGwetu M(2024)A Centrality-Weighted Bidirectional Encoder Representation from Transformers Model for Enhanced Sequence Labeling in Key Phrase Extraction from Scientific TextsBig Data and Cognitive Computing10.3390/bdcc81201828:12(182)Online publication date: 4-Dec-2024
https://doi.org/10.3390/bdcc8120182
Chen JHou HGao J(2020)Inside Importance Factors of Graph-Based Keyword Extraction on Chinese Short TextACM Transactions on Asian and Low-Resource Language Information Processing10.1145/338897119:5(1-15)Online publication date: 21-Jun-2020
https://dl.acm.org/doi/10.1145/3388971
Showrov MAl Awal MSazzad S(2019)Identification of Users Feature Based on Facebook Snippets2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)10.1109/ICACCE46606.2019.9079976(1-5)Online publication date: Apr-2019
https://doi.org/10.1109/ICACCE46606.2019.9079976
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Index Terms

Keyword extraction for social snippets
1. Information systems
  1. Information retrieval
    1. Document representation
  2. Information systems applications
2. Theory of computation
  1. Semantics and reasoning
    1. Program reasoning
      1. Abstraction

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Information

Published In

WWW '10: Proceedings of the 19th international conference on World wide web

April 2010

1407 pages

ISBN:9781605587998

DOI:10.1145/1772690

General Chairs:
Michael Rappa
North Carolina State University, USA
,
Paul Jones
University of North Carolina at Chapel Hill, USA
,
Program Chairs:
Juliana Freire
University of Utah, USA
,
Soumen Chakrabarti
Indian Institute of Technology, India

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2010

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WWW '10

WWW '10: The 19th International World Wide Web Conference

April 26 - 30, 2010

North Carolina, Raleigh, USA

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Zengeya TFonou Dombeu JGwetu M(2024)A Centrality-Weighted Bidirectional Encoder Representation from Transformers Model for Enhanced Sequence Labeling in Key Phrase Extraction from Scientific TextsBig Data and Cognitive Computing10.3390/bdcc81201828:12(182)Online publication date: 4-Dec-2024
https://doi.org/10.3390/bdcc8120182
Chen JHou HGao J(2020)Inside Importance Factors of Graph-Based Keyword Extraction on Chinese Short TextACM Transactions on Asian and Low-Resource Language Information Processing10.1145/338897119:5(1-15)Online publication date: 21-Jun-2020
https://dl.acm.org/doi/10.1145/3388971
Showrov MAl Awal MSazzad S(2019)Identification of Users Feature Based on Facebook Snippets2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)10.1109/ICACCE46606.2019.9079976(1-5)Online publication date: Apr-2019
https://doi.org/10.1109/ICACCE46606.2019.9079976
Figueiredo FJorge A(2019)Identifying topic relevant hashtags in Twitter streamsInformation Sciences: an International Journal10.1016/j.ins.2019.07.062505:C(65-83)Online publication date: 1-Dec-2019
https://dl.acm.org/doi/10.1016/j.ins.2019.07.062
Li LLiu JSun YXu GYuan JZhong L(2018)Unsupervised keyword extraction from microblog posts via hashtagsJournal of Web Engineering10.5555/3370048.337005317:1-2(93-120)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.5555/3370048.3370053
Gollapalli SLi XYang PSingh SMarkovitch S(2017)Incorporating expert knowledge into keyphrase extractionProceedings of the Thirty-First AAAI Conference on Artificial Intelligence10.5555/3298023.3298031(3180-3187)Online publication date: 4-Feb-2017
https://dl.acm.org/doi/10.5555/3298023.3298031
Sarna GBhatia MSubrahmanian VRokne JKumar RCaverlee JTong H(2016)A probalistic approach to automatically extract new words from social mediaProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.5555/3192424.3192560(719-725)Online publication date: 18-Aug-2016
https://dl.acm.org/doi/10.5555/3192424.3192560
Deb SMohan SVenkatraman PBindu PThilagam P(2016)Deriving temporal trends in user preferences through short message strings2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)10.1109/ICEEOT.2016.7755656(4915-4920)Online publication date: Mar-2016
https://doi.org/10.1109/ICEEOT.2016.7755656
Sarna GBhatia M(2016)A probalistic approach to automatically extract new words from social media2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)10.1109/ASONAM.2016.7752316(719-725)Online publication date: Aug-2016
https://doi.org/10.1109/ASONAM.2016.7752316
LAHIRI SMIHALCEA RLAI P(2016)Keyword extraction from emailsNatural Language Engineering10.1017/S135132491600023123:02(295-317)Online publication date: 9-Sep-2016
https://doi.org/10.1017/S1351324916000231
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