Question Classification using Multiple Classifiers
نویسندگان
چکیده
The Open-domain Question Answering system (QA) has been attached great attention for its capacity of providing compact and precise results for sers. The question classification is an essential part in the system, affecting the accuracy of it. The paper studies question classification through machine learning approaches, namely, different classifiers and multiple classifier combination method. By using compositive statistic and rule classifiers, and by introducing dependency structure from Minipar and linguistic knowledge from Wordnet into question representation, the research shows high accuracy in question classification.
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دستهبندی پرسشها با استفاده از ترکیب دستهبندها
Question answering systems are produced and developed to provide exact answers to the question posted in natural language. One of the most important parts of question answering systems is question classification. The purpose of question classification is predicting the kind of answer needed for the question in natural language. The literature works can be categorized as rule-based and learning...
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