Title

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

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.

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.

Identifier

DOI: 10.1007/978-1-84628-992-7_26