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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lili Jiang Jianyong Wang Ning An Shengyuan Wang Jian Zhan Lian Li |
| Copyright Year | 2009 |
| Abstract | Finding information about people using search engines is one of the most common activities on the Web. However, search engines usually return a long list of Web pages, which may be relevant to many namesakes, especially given the explosive growth of Web data. To address the challenge caused by name ambiguity in Web people search, this paper proposes a novel graph-based framework, GRAPE (abbr. a Graph-based fRamework for disAmbiguating People appEarances in Web search). In GRAPE, people tag information (e.g., people name, organization, and email address) surrounding the queried people name is extracted from the search results, a graph-based unsupervised algorithm is then developed to cluster the extracted tags, where a new method, Cohesion, is introduced to measure the importance of a tag for clustering, and each final cluster of tags represents a unique people entity. Experimental results show that our proposed framework outperforms the state-of-the-art Web people name disambiguation approaches. |
| Starting Page | 199 |
| Ending Page | 208 |
| File Size | 314652 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781424452422 |
| ISSN | 15504786 |
| DOI | 10.1109/ICDM.2009.25 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-12-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pipelines Web search Search engines Data mining Web pages Clustering algorithms Open source software Computer science education Information science Computer science Clustering People Name Disambiguation Named Entity Tag Extraction |
| Content Type | Text |
| Resource Type | Article |
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