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POLYPHONET: An advanced social network extraction system from the Web

by: Y. Matsuo, J. Mori, M. Hamasaki, T. Nishimura, H. Takeda, K. Hasida, and M. Ishizuka

In: Journal of Web Semantics, Vol. 5, Nr. 4 (2007) , p. 262--278.

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URL:	://000253453300005
DOI:	10.1016/j.websem.2007.09.002

Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We propose a social network extraction system called POLYPHONET, which employs several advanced techniques to extract relations of persons, to detect groups of persons, and to obtain keywords for a person. Search engines, especially Google, are used to measure co-occurrence of information and obtain Web documents. Several studies have used search engines to extract social networks from the Web, but our research advances the following points: first, we reduce the related methods into simple pseudocodes using Google so that we can build up integrated systems. Second, we develop several new algorithms for social network mining such as those to classify relations into categories, to make extraction scalable, and to obtain and utilize person-to-word relations. Third, every module is implemented in POLYPHONET, which has been used at four academic conferences, each with more than 500 participants. We overview that system. Finally, a novel architecture called Iterative Social Network Mining is proposed. It utilizes simple modules using Google and is characterized by scalability and relate-identify processes: identification of each entity and extraction of relations are repeated to obtain a more precise social network. C 2007 Elsevier B.V. All rights reserved.

Description

{266QY} Times Cited:0 Cited References Count:55

BibTeX record

@article{matsuo_polyphonet:advanced_2007,
  abstract = {Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We propose a social network extraction system called {POLYPHONET,} which employs several advanced techniques to extract relations of persons, to detect groups of persons, and to obtain keywords for a person. Search engines, especially Google, are used to measure co-occurrence of information and obtain Web documents. Several studies have used search engines to extract social networks from the Web, but our research advances the following points: first, we reduce the related methods into simple pseudocodes using Google so that we can build up integrated systems. Second, we develop several new algorithms for social network mining such as those to classify relations into categories, to make extraction scalable, and to obtain and utilize person-to-word relations. Third, every module is implemented in {POLYPHONET,} which has been used at four academic conferences, each with more than 500 participants. We overview that system. Finally, a novel architecture called Iterative Social Network Mining is proposed. It utilizes simple modules using Google and is characterized by scalability and relate-identify processes: identification of each entity and extraction of relations are repeated to obtain a more precise social network. {(C)} 2007 Elsevier {B.V.} All rights reserved.},
  added-at = {2009-06-04T20:46:11.000+0200},
  author = {Matsuo, Y. and Mori, J. and Hamasaki, M. and Nishimura, T. and Takeda, H. and Hasida, K. and Ishizuka, M.},
  biburl = {http://www.bibsonomy.org/bibtex/2d6f20c0e5deaa49f262051d1538d070c/quesada},
  description = {{266QY} Times Cited:0 Cited References Count:55},
  doi = {{DOI} 10.1016/j.websem.2007.09.002},
  interhash = {8321e11c0a9bcd9f11d0b8198433c461},
  intrahash = {d6f20c0e5deaa49f262051d1538d070c},
  issn = {1570-8268},
  journal = {Journal of Web Semantics},
  keywords = {searchengine,socialnetwork,webmining},
  number = 4,
  pages = {262--278},
  timestamp = {2009-06-04T20:46:11.000+0200},
  title = {{POLYPHONET:} An advanced social network extraction system from the Web},
  url = {://000253453300005},
  volume = 5,
  year = 2007
}

Endnote record

%0 Journal Article
%1 matsuo_polyphonet:advanced_2007
%A Matsuo, Y.
%A Mori, J.
%A Hamasaki, M.
%A Nishimura, T.
%A Takeda, H.
%A Hasida, K.
%A Ishizuka, M.
%D 2007
%J Journal of Web Semantics
%K 
%N 4
%P 262--278
%T {POLYPHONET:} An advanced social network extraction system from the Web
%R {DOI} 10.1016/j.websem.2007.09.002
%U ://000253453300005
%V 5
%X Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We propose a social network extraction system called {POLYPHONET,} which employs several advanced techniques to extract relations of persons, to detect groups of persons, and to obtain keywords for a person. Search engines, especially Google, are used to measure co-occurrence of information and obtain Web documents. Several studies have used search engines to extract social networks from the Web, but our research advances the following points: first, we reduce the related methods into simple pseudocodes using Google so that we can build up integrated systems. Second, we develop several new algorithms for social network mining such as those to classify relations into categories, to make extraction scalable, and to obtain and utilize person-to-word relations. Third, every module is implemented in {POLYPHONET,} which has been used at four academic conferences, each with more than 500 participants. We overview that system. Finally, a novel architecture called Iterative Social Network Mining is proposed. It utilizes simple modules using Google and is characterized by scalability and relate-identify processes: identification of each entity and extraction of relations are repeated to obtain a more precise social network. {(C)} 2007 Elsevier {B.V.} All rights reserved.