| Presentation | 2013-03-15 Calculating Word Similarity for Context Aware Web Service Clustering Hiroki Ohashi, Incheon Paik, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Web service discovery is becoming a challenging and time consuming task due to large number of Web services available on the Internet. Organizing the Web services into functionally similar clusters is one of a very efficient approach for reducing the search space. To cluster Web services, we first extract the features (e.g., service name)to measure the similarities from service descriptions from Web or registry. The services usually consist of complex terms, from which we can get service features in some contexts. Current works for service clustering have not considered the context. To make clustering of web services by domain context, we need calculation of terms similarity under a specific context. In this paper, we suggest a novel method to measure terms similarity consider the specific domain context using machine learning. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Web Service / Word Similarity / Clustering |
| Paper # | SC2012-22 |
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| Conference Information | |
| Committee | SC |
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| Conference Date | 2013/3/8(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Services Computing (SC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Calculating Word Similarity for Context Aware Web Service Clustering |
| Sub Title (in English) | |
| Keyword(1) | Web Service |
| Keyword(2) | Word Similarity |
| Keyword(3) | Clustering |
| 1st Author's Name | Hiroki Ohashi |
| 1st Author's Affiliation | Graduate School of Computer Science and Engineering, University of Aizu() |
| 2nd Author's Name | Incheon Paik |
| 2nd Author's Affiliation | Graduate School of Computer Science and Engineering, University of Aizu |
| Date | 2013-03-15 |
| Paper # | SC2012-22 |
| Volume (vol) | vol.112 |
| Number (no) | 497 |
| Page | pp.pp.- |
| #Pages | 3 |
| Date of Issue | |