This paper addresses the problem of categorizing terms or lexical entities into a predefined set of semantic domains exploiting the knowledge available on-line in the Web. The prop...
Leonardo Rigutini, Ernesto Di Iorio, Marco Ernande...
Background: Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of f...
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Biomedical researchers rely on keyword-based search engines to retrieve superficially relevant documents, from which they must filter out irrelevant information manually. Hence, t...
Richard Tzong-Han Tsai, Hong-Jie Dai, Hsi-Chuan Hu...
This paper describes our first participation in the Indian language sub-task of the main Adhoc monolingual and bilingual track in CLEF1 competition. In this track, the task is to...