Using Subjectivity Analysis to Improve the Precision of Information Extraction System – A Review
نویسندگان
چکیده
“Information Extraction” systems, face a crucial problem of false hits because of a number of reasons, observations show that a large number of these false hits are due to the presence of subjectivity in the text. This observation motivates the exploration of the notion of using subjectivity analysis to decrease the number of false hits by the Information Extraction systems. “Subjectivity Analysis” system is the one which identifies and extracts information related to opinions, attitudes and sentiments from the text. This paper presents a review on the method of subjectivity analysis, and then using its results to improve precision of information extraction system. Keywords— Subjectivity Analysis, Information Extraction, Natural Language Processing.
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Exploiting Subjectivity Classification to Improve Information Extraction
Information extraction (IE) systems are prone to false hits for a variety of reasons and we observed that many of these false hits occur in sentences that contain subjective language (e.g., opinions, emotions, and sentiments). Motivated by these observations, we explore the idea of using subjectivity analysis to improve the precision of information extraction systems. In this paper, we describe...
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