Improving the Classification of Unknown Documents by Concept Graph
Publish place: 14th annual International CSI Computer Conference
Publish Year: 1388
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CSICC14_095
تاریخ نمایه سازی: 24 خرداد 1388
Abstract:
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.
Authors
Morteza Mohaqeqi
ECE Department, University of Tehran, Tehran, Iran
Reza Soltanpoor
Computer Department, Islamic Azad University of Tehran North branch, Tehran, Iran
Azadeh Shakery
ECE Department, University of Tehran, Tehran, Iran