A key component extraction method based on HMM and dependency parsing
| Autor: | Jian Dong, Jianchu Kang, Bowen Du, Jian Huang, Songsong Pang |
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| Rok vydání: | 2012 |
| Předmět: |
Point of interest
business.industry Computer science Computer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing) Pattern recognition computer.software_genre Rule-based machine translation Dependency grammar Segmentation S-attributed grammar Artificial intelligence business Hidden Markov model computer Classifier (UML) Natural language processing Sentence |
| Zdroj: | 2012 6th International Conference on Application of Information and Communication Technologies (AICT). |
| DOI: | 10.1109/icaict.2012.6398516 |
| Popis: | Increasing attention has been paid for POI (Point of Interest) data query for travel information service. The correct extraction of key components in question is crucial for improving the accuracy of query results. The paper proposes a key component extraction method based on HMM (Hidden Markov Model) and dependency parsing. Firstly, the sentence pattern classifier is established by HMM. And then, questions are classified by classifier. Finally, combination of sentence pattern's structure, the four key components are extracted by dependency parsing. The results show that the F1-Measure is 0.83, which well proves the effectiveness of the method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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