| Presentation | 2009-05-22 Unsupervised extraction of content-related annotations Tomoharu IWATA, Takeshi YAMADA, Naonori UEDA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose a topic model for extracting content-related annotations. In social annotation services, some annotations do not relate to their contents since users can attach annotations freely. The extraction of content-related annotations can improve the information retrieval performance or can be used as a preprocessing step in machine learning tasks such as text classification and image recognition. The proposed model is a generative model for content and annotations, and the inference and parameter estimation are carried out based on a stochastic EM algorithm. We demonstrate the effectiveness of the proposed method by using synthetic data and real social annotation data for text and images. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Topic model / Social annotation / Folksonomy |
| Paper # | AI2009-3 |
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| Conference Information | |
| Committee | AI |
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| Conference Date | 2009/5/15(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Unsupervised extraction of content-related annotations |
| Sub Title (in English) | |
| Keyword(1) | Topic model |
| Keyword(2) | Social annotation |
| Keyword(3) | Folksonomy |
| 1st Author's Name | Tomoharu IWATA |
| 1st Author's Affiliation | NTT Communication Science Laboratories() |
| 2nd Author's Name | Takeshi YAMADA |
| 2nd Author's Affiliation | NTT Communication Science Laboratories |
| 3rd Author's Name | Naonori UEDA |
| 3rd Author's Affiliation | NTT Communication Science Laboratories |
| Date | 2009-05-22 |
| Paper # | AI2009-3 |
| Volume (vol) | vol.109 |
| Number (no) | 51 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |