Question classification with semantic tree kernel

ABSTRACT

Question Classification plays an important role in most Question Answering systems. In this paper, we exploit semantic features in Support Vector Machines (SVMs) for Question Classification. We propose a semantic tree kernel to incorporate semantic similarity information. A diverse set of semantic features is evaluated. Experimental results show that SVMs with semantic features, especially semantic classes, can significantly outperform the state-of-the-art systems.

REFERENCES

• 1: M. Collins and N. Duffy. Convolution Kernels for Natural Language. In Proceedings of Neural Information Processing Systems (NIPS14), 2001
• 2: Xin Li , Dan Roth, Learning question classifiers, Proceedings of the 19th international conference on Computational linguistics, p.1-7, August 24-September 01, 2002, Taipei, Taiwan [doi>10.3115/1072228.1072378]
• 3: Dell Zhang , Wee Sun Lee, Question classification using support vector machines, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, July 28-August 01, 2003, Toronto, Canada [doi>10.1145/860435.860443]
• 4: Xin Li , Dan Roth, Learning question classifiers: the role of semantic information, Natural Language Engineering, v.12 n.3, p.229-249, September 2006 [doi>10.1017/S1351324905003955]
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• 6: Phil Blunsom , Krystle Kocik , James R. Curran, Question classification with log-linear models, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, August 06-11, 2006, Seattle, Washington, USA [doi>10.1145/1148170.1148282]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

General Terms:
Algorithms, Experimentation

Keywords:
machine learning, question answering, question classification, semantic class, support vector machines, tree kernel