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Using Encyclopedic Knowledge to Understand Queries
| Content Provider | ACM Digital Library |
|---|---|
| Author | Wang, Zhongyuan Meng, Xiaofeng Li, Hehan Zhao, Kejun |
| Abstract | Query understanding is a challenging but beneficial task. In this paper, we propose a context-aware method to use the encyclopedic knowledge to aid in query understanding. Given a query, we first use a dictionary constructed from the encyclopedic knowledge bases to detect the possible entities and their associated categories. Then, we use a topic based ethod to derive semantic information from the query. By comparing the topical similarity between various candidate phrases, we get the most likely entities and their related categories. Experimental results show that our method has achieved a great improvement over previous approaches and the efficiency is acceptable for online search. |
| Starting Page | 17 |
| Ending Page | 22 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450337892 |
| DOI | 10.1145/2810355.2810358 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-10-22 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Query understanding Named entity recognition and categorization Knowledge base Topic model |
| Content Type | Text |
| Resource Type | Article |
