Conference
View in EDS

Comparison of Automatic Clustering and Manual Categorization of Documents

Bibliographic Details
Title: Comparison of Automatic Clustering and Manual Categorization of Documents
Authors: Taghva, Kazem, Sharma, Meghna
Contributors: Babak Akhgar
Source: Electrical and Computer Engineering Faculty Presentations
Publisher Information: UNLV's Repository for Research, Scholarship, and Creative Activity
Publication Year: 2007
Collection: University of Nevada, Las Vegas: Digital Scholarship@UNLV
Subject Terms: Cluster analysis – Computer programs, Document clustering, Machine learning, Computer Engineering, Electrical and Computer Engineering, Theory and Algorithms
Description: The fundamental goal of this research is to learn whether unsupervised learning can be used to cluster documents in the collection in a similar way that manual categories are. We report on our experiments with K-mean clustering algorithm to provide a partial answer to the above mentioned goal.
Document Type: conference object
Language: unknown
Relation: https://oasis.library.unlv.edu/ece_presentations/26
Availability: https://oasis.library.unlv.edu/ece_presentations/26
Accession Number: edsbas.BACA5D75
Database: BASE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://oasis.library.unlv.edu/ece_presentations/26#
    Name: EDS - BASE (ns324271)
    Category: fullText
    Text: View record from BASE
Header DbId: edsbas
DbLabel: BASE
An: edsbas.BACA5D75
RelevancyScore: 782
AccessLevel: 3
PubType: Conference
PubTypeId: conference
PreciseRelevancyScore: 782.334289550781
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Comparison of Automatic Clustering and Manual Categorization of Documents
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Taghva%2C+Kazem%22">Taghva, Kazem</searchLink><br /><searchLink fieldCode="AR" term="%22Sharma%2C+Meghna%22">Sharma, Meghna</searchLink>
– Name: Author
  Label: Contributors
  Group: Au
  Data: Babak Akhgar
– Name: TitleSource
  Label: Source
  Group: Src
  Data: Electrical and Computer Engineering Faculty Presentations
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: UNLV's Repository for Research, Scholarship, and Creative Activity
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2007
– Name: Subset
  Label: Collection
  Group: HoldingsInfo
  Data: University of Nevada, Las Vegas: Digital Scholarship@UNLV
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Cluster+analysis+–+Computer+programs%22">Cluster analysis – Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22Document+clustering%22">Document clustering</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Engineering%22">Computer Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Electrical+and+Computer+Engineering%22">Electrical and Computer Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Theory+and+Algorithms%22">Theory and Algorithms</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: The fundamental goal of this research is to learn whether unsupervised learning can be used to cluster documents in the collection in a similar way that manual categories are. We report on our experiments with K-mean clustering algorithm to provide a partial answer to the above mentioned goal.
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: conference object
– Name: Language
  Label: Language
  Group: Lang
  Data: unknown
– Name: NoteTitleSource
  Label: Relation
  Group: SrcInfo
  Data: https://oasis.library.unlv.edu/ece_presentations/26
– Name: URL
  Label: Availability
  Group: URL
  Data: https://oasis.library.unlv.edu/ece_presentations/26
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.BACA5D75
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.BACA5D75
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: unknown
    Subjects:
      – SubjectFull: Cluster analysis – Computer programs
        Type: general
      – SubjectFull: Document clustering
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Computer Engineering
        Type: general
      – SubjectFull: Electrical and Computer Engineering
        Type: general
      – SubjectFull: Theory and Algorithms
        Type: general
    Titles:
      – TitleFull: Comparison of Automatic Clustering and Manual Categorization of Documents
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Taghva, Kazem
      – PersonEntity:
          Name:
            NameFull: Sharma, Meghna
      – PersonEntity:
          Name:
            NameFull: Babak Akhgar
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2007
          Identifiers:
            – Type: issn-locals
              Value: edsbas
          Titles:
            – TitleFull: Electrical and Computer Engineering Faculty Presentations
              Type: main
ResultId 1