Extracting Professional Preferences of Users from Natural Language Essays
نویسنده
چکیده
This paper presents an unsupervised sentiment analysis approach for extracting professional preferences of users from natural language essays in a career recommendation scenario. Our system first extracts terms facilitating career recommendation such as objects, activities, hobbies, and places from the essays. Then, it applies a lexicon-based sentiment analysis approach to assign polarities representing user preferences.
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تاریخ انتشار 2009