Integrated Question Classification based on Rules and Pattern Matching

In question answering, task of question classification has remained in sharp focus since long. This paper presents our research about question classification in higher education domain. The questions for the domain are divided into 9 coarse grained categories and 61 fine grained categories. In the proposed integrated classification method, rules are adopted to extract coarse grain categories and focus words while pattern matching is implemented to classify the questions in fine grained categories. Experimental result shows the efficiency of our method which achieves satisfactory performance with the state of the art in this field.

[1]  Tilman Becker,et al.  Question Answering by Searching Large Corpora With Linguistic Methods , 2004, TREC.

[2]  Beatrice Santorini,et al.  Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.

[3]  Martin M. Soubbotin Patterns of Potential Answer Expressions as Clues to the Right Answers , 2001, TREC.

[4]  Xiaoming Chang,et al.  A Rule-based Chinese Question Answering System for Reading Comprehension Tests , 2007, Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2007).

[5]  Dan Roth,et al.  Learning Question Classifiers , 2002, COLING.

[6]  Xiaohong Huang,et al.  Personalized Question Answering System Based on Ontology and Semantic Web , 2006, 2006 4th IEEE International Conference on Industrial Informatics.

[7]  Jimmy J. Lin,et al.  Data-Intensive Question Answering , 2001, TREC.

[8]  M VoorheesEllen The TREC question answering track , 2001 .

[9]  Yuan Wang,et al.  A Classification of Questions Using SVM and Semantic Similarity Analysis , 2012, 2012 Sixth International Conference on Internet Computing for Science and Engineering.

[10]  Ellen Riloff,et al.  A Rule-based Question Answering System for Reading Comprehension Tests , 2000 .

[11]  Eugene Agichtein,et al.  Factoid Question Answering over Unstructured and Structured Web Content , 2005, TREC.

[12]  Fuji Ren,et al.  Question Classification for Chinese Cuisine Question Answering System , 2009 .

[13]  Eduard H. Hovy,et al.  Learning surface text patterns for a Question Answering System , 2002, ACL.