DocumentCode
2727480
Title
Blogosonomy : Autotagging Any Text Using Bloggers´ Knowledge
Author
Fujimura, Shigeru ; Fujimura, Ko ; Okuda, Hidenori
Author_Institution
NTT Corp., Yokohama
fYear
2007
fDate
2-5 Nov. 2007
Firstpage
205
Lastpage
212
Abstract
There are at least three barriers to utilizing blog tags in classification or navigation: 40% of entries are not (from our observations) tagged, there are many orthographic or synonymous tag variations, and not all tags are informative. We propose a method of multi-autotagging, based on k-NN, which is a case-based classification method. Our method also has the functions of merging tags with the same meaning and identifying informative tags. For realizing these functions, we propose the term weighting method named residual document frequency(RDF); it can score the similarity between tags. Experiments show the effectiveness of our methods. Our autotagging system is generic and can assign tag(s) to any text as well as blog entries although the training data is collected from the blogosophere.
Keywords
Internet; classification; text analysis; blogger knowledge; blogosonomy; case-based classification; k-NN classification; multiautotagging; residual document frequency; Frequency; Information services; Internet; Merging; Navigation; Training data; Web sites;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence, IEEE/WIC/ACM International Conference on
Conference_Location
Fremont, CA
Print_ISBN
978-0-7695-3026-0
Type
conf
DOI
10.1109/WI.2007.85
Filename
4427089
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