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Improving the Classification of Unknown Documents by Concept Graph

نویسنده (ها)
  • Morteza Mohaqeqi
  • Reza Soltanpoor
  • Azadeh Shakery
مربوط به کنفرانس چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
چکیده Concept graph is a graph that represents the relationships between language concepts. In this structure the relationship between any two words is demonstrated by a weighted edge such that the value of this weight is interpreted as the degree of the relevance of two words. Having this graph, we can obtain most relevant words to a special term. In this paper, we propose a method for improving the classification of documents from unknown sources by means of concept graph. In our method, initially some features are selected from a training set by a well-known feature selection algorithm. Then, by extracting most relevant words for each class from the concept graph, a more effective feature set is produced. Our experimental results identify an improvement of 1% and 8% in precision and recall measures, respectively.
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