Existing approaches to classifying documents by sentiment include machine learning with features created from n-grams and part of speech. This paper explores a different approach ...
With a growing number of works utilizing link information in enhancing document clustering, it becomes necessary to make a comparative evaluation of the impacts of different link ...
Malware clustering and classification are important tools that enable analysts to prioritize their malware analysis efforts. The recent emergence of fully automated methods for ma...
We formulate three intuitive semantic properties for topk queries in probabilistic databases, and propose GlobalTopk query semantics which satisfies all of them. We provide a dyn...
Abstract. This paper examines a conflation method based on the N-grams approach and evaluates its performance relative to the results achieved by other techniques such as Porter a...