Presentation | 2012-06-29 Clustering of Text Documents with Time Series Features Reiko HAMADA, Shin'ichi SATOH, |
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Abstract(in English) | Most traditional text clustering methods are based on "bag of words" representation. However, since topics in closed captions are very short, it is difficult to supply enough "bag of words" information. In this paper, we present a new approach for topic clustering on closed captions. First, we clustered one-year closed captions manually, and discovered that topics categorized into "accidents" or "disasters" shows particular cluster- and time- distributions. Therefore we proposed tin-supervised clustering method using temporal information adding to conventional word vector distance. Furthermore, the accuracy was improved by changing the linkage criteria as the clustering process progresses. Our experimental results show the effectiveness of combination of time and word information. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Text Processing / Clustering / Temporal Information |
Paper # | NLC2012-2,PRMU2012-22 |
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Committee | NLC |
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Conference Date | 2012/6/22(1days) |
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Registration To | Natural Language Understanding and Models of Communication (NLC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Clustering of Text Documents with Time Series Features |
Sub Title (in English) | |
Keyword(1) | Text Processing |
Keyword(2) | Clustering |
Keyword(3) | Temporal Information |
1st Author's Name | Reiko HAMADA |
1st Author's Affiliation | National Institute of Informatics() |
2nd Author's Name | Shin'ichi SATOH |
2nd Author's Affiliation | National Institute of Informatics |
Date | 2012-06-29 |
Paper # | NLC2012-2,PRMU2012-22 |
Volume (vol) | vol.112 |
Number (no) | 110 |
Page | pp.pp.- |
#Pages | 6 |
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