Feature ranking is a fundamental machine learning task with various applications, including feature selection and decision tree learning. We describe and analyze a new feature ran...
Maximizing only the relevance between queries and documents will not satisfy users if they want the top search results to present a wide coverage of topics by a few representative...
Yi Liu, Benyu Zhang, Zheng Chen, Michael R. Lyu, W...
In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in hig...
Finding a small set of representative instances for large datasets can bring various benefits to data mining practitioners so they can (1) build a learner superior to the one cons...
In word sense disambiguation, choosing the most frequent sense for an ambiguous word is a powerful heuristic. However, its usefulness is restricted by the availability of sense-an...