In ontology learning from texts, we have ontology-rich domains where we have large structured domain knowledge repositories or we have large general corpora with large general str...
Francesca Fallucchi, Maria Teresa Pazienza, Fabio ...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...