Comparison of Automatic Clustering and Manual Categorization of Documents
Editors
Babak Akhgar
Meeting name
15th International Workshops on Conceptual Structures
Document Type
Conference Proceeding
Publication Date
2007
Abstract
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.
Keywords
Cluster analysis – Computer programs; Document clustering; Machine learning
Disciplines
Computer Engineering | Electrical and Computer Engineering | Theory and Algorithms
Permissions
Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.
Repository Citation
Taghva, K.,
Sharma, M.
(2007, January).
Comparison of Automatic Clustering and Manual Categorization of Documents.
Presentation at 15th International Workshops on Conceptual Structures,
Available at: https://digitalscholarship.unlv.edu/ece_presentations/26