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Ipoll: Automatic polling using online search

Nguyen, Thin, Phung, Dinh, Luo, Wei, Tran, Truyen and Venkatesh, Svetha 2014, Ipoll: Automatic polling using online search. In Benatallah,B, Bestavros,A, Manolopoulos,Y, Vakali,A and Zhang,Y (ed), Web information system engineering - WISE 2014, Springer, Berlin, Germany, pp.266-275.

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Title Ipoll: Automatic polling using online search
Author(s) Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Luo, WeiORCID iD for Luo, Wei orcid.org/0000-0002-4711-7543
Tran, TruyenORCID iD for Tran, Truyen orcid.org/0000-0001-6531-8907
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Title of book Web information system engineering - WISE 2014
Editor(s) Benatallah,B
Bestavros,A
Manolopoulos,Y
Vakali,A
Zhang,Y
Publication date 2014
Series Lecture Notes in Computer Science
Chapter number 21
Total chapters 40
Start page 266
End page 275
Total pages 10
Publisher Springer
Place of Publication Berlin, Germany
Keyword(s) Information extraction
Opinion polls
Web search
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Software Engineering
Computer Science, Theory & Methods
Computer Science
TRENDS
WEB
Summary For years, opinion polls rely on data collected through telephone or person-to-person surveys. The process is costly, inconvenient, and slow. Recently online search data has emerged as potential proxies for the survey data. However considerable human involvement is still needed for the selection of search indices, a task that requires knowledge of both the target issue and how search terms are used by the online community. The robustness of such manually selected search indices can be questionable. In this paper, we propose an automatic polling system through a novel application of machine learning. In this system, the needs for examining, comparing, and selecting search indices have been eliminated through automatic generation of candidate search indices and intelligent combination of the indices. The results include a publicly accessible web application that provides real-time, robust, and accurate measurements of public opinions on several subjects of general interest.
ISBN 9783319117485
ISSN 0302-9743
1611-3349
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category B1 Book chapter
ERA Research output type B Book chapter
Copyright notice ©2014, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30072491

Document type: Book Chapter
Collection: Centre for Pattern Recognition and Data Analytics
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