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Knowledge discovery in virtual community texts: Clustering virtual communities.

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  • Additional Information
    • Author-Supplied Keywords:
      clustering
      knowledge discovery in text
      latent semantic indexing
      virtual community
      web portal
    • NAICS/Industry Codes:
      517919 All Other Telecommunications
      517910 Other telecommunications
      517110 Wired Telecommunications Carriers
    • Abstract:
      Automatic knowledge discovery from texts (KDT) is proving to be a promising method for businesses today to deal with the overload of textual information. In this paper, we first explore the possibilities for KDT to enhance communication in virtual communities, and then we present a practical case study with real-life Internet data. The problem in the case study is to manage the very successful virtual communities known as 'clubs' of the largest Dutch Internet Service Provider. It is possible for anyone to start a club about any subject, resulting in over 10,000 active clubs today. At the beginning, the founder assigns the club to a predefined category. This often results in illogical or inconsistent placements, which means that interesting clubs may be hard to locate for potential new members. The ISP therefore is looking for an automated way to categorize clubs in a logical and consistent manner. The method used is the so-called bag-of-words approach, previously applied mostly to scientific texts and structured documents. Each club is described by a vector of word occurrences of all communications within that club. Latent Semantic Indexing (LSI) is applied to reduce the dimensionality problem prior to clustering. Clustering is done by the Within Groups Clustering method using a cosine distance measure appropriate for texts. The results show that KDT and the LSI method can successfully be applied for clustering the very volatile and unstructured textual communication on the Internet. [ABSTRACT FROM AUTHOR]
    • Abstract:
      Copyright of Journal of Intelligent & Fuzzy Systems is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
    • Author Affiliations:
      1KPN Mobile, P.O. Box 30139, 2500 GC The Hague, The Netherlands
      2ECCOO, Broerstraat 4, 9712 CP Groningen, The Netherlands
      3CWI, P.O.Box 94079, 1090 GB Amsterdam, The Netherlands
      4Lund University, Department of Information Technology, P.O. Box 118, 22100 Lund, Sweden
    • ISSN:
      1064-1246
    • Accession Number:
      11280923
  • Citations
    • ABNT:
      OUDSHOFF, A. M. et al. Knowledge discovery in virtual community texts: Clustering virtual communities. Journal of Intelligent & Fuzzy Systems, [s. l.], v. 14, n. 1, p. 13–24, 2003. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=11280923&custid=s8280428. Acesso em: 6 ago. 2020.
    • AMA:
      Oudshoff AM, Bosloper IE, Klos TB, Spaanenburg L. Knowledge discovery in virtual community texts: Clustering virtual communities. Journal of Intelligent & Fuzzy Systems. 2003;14(1):13-24. http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=11280923&custid=s8280428. Accessed August 6, 2020.
    • AMA11:
      Oudshoff AM, Bosloper IE, Klos TB, Spaanenburg L. Knowledge discovery in virtual community texts: Clustering virtual communities. Journal of Intelligent & Fuzzy Systems. 2003;14(1):13-24. Accessed August 6, 2020. http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=11280923&custid=s8280428
    • APA:
      Oudshoff, A. M., Bosloper, I. E., Klos, T. B., & Spaanenburg, L. (2003). Knowledge discovery in virtual community texts: Clustering virtual communities. Journal of Intelligent & Fuzzy Systems, 14(1), 13–24.
    • Chicago/Turabian: Author-Date:
      Oudshoff, A.M., I.E. Bosloper, T.B. Klos, and L. Spaanenburg. 2003. “Knowledge Discovery in Virtual Community Texts: Clustering Virtual Communities.” Journal of Intelligent & Fuzzy Systems 14 (1): 13–24. http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=11280923&custid=s8280428.
    • Harvard:
      Oudshoff, A. M. et al. (2003) ‘Knowledge discovery in virtual community texts: Clustering virtual communities’, Journal of Intelligent & Fuzzy Systems, 14(1), pp. 13–24. Available at: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=11280923&custid=s8280428 (Accessed: 6 August 2020).
    • Harvard: Australian:
      Oudshoff, AM, Bosloper, IE, Klos, TB & Spaanenburg, L 2003, ‘Knowledge discovery in virtual community texts: Clustering virtual communities’, Journal of Intelligent & Fuzzy Systems, vol. 14, no. 1, pp. 13–24, viewed 6 August 2020, .
    • MLA:
      Oudshoff, A. M., et al. “Knowledge Discovery in Virtual Community Texts: Clustering Virtual Communities.” Journal of Intelligent & Fuzzy Systems, vol. 14, no. 1, Feb. 2003, pp. 13–24. EBSCOhost, search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=11280923&custid=s8280428.
    • Chicago/Turabian: Humanities:
      Oudshoff, A.M., I.E. Bosloper, T.B. Klos, and L. Spaanenburg. “Knowledge Discovery in Virtual Community Texts: Clustering Virtual Communities.” Journal of Intelligent & Fuzzy Systems 14, no. 1 (February 2003): 13–24. http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=11280923&custid=s8280428.
    • Vancouver/ICMJE:
      Oudshoff AM, Bosloper IE, Klos TB, Spaanenburg L. Knowledge discovery in virtual community texts: Clustering virtual communities. Journal of Intelligent & Fuzzy Systems [Internet]. 2003 Feb [cited 2020 Aug 6];14(1):13–24. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=11280923&custid=s8280428