With the development of the techniques of Event Detection and Tracking, it is feasible to gather text information from many sources and structure it into events which are constructed online automatically and updated temporally. There are always diversified versions to describe an event and users usually are eager to know all the versions. With the huge quantity of documents, it is almost imposs...

Automatic text categorization is a problem of automatically assigning text documents to predefined categories. In order to classify text documents, we must extract good features from them. In previous research, a text document is commonly represented by the term frequency and the inverted document frequency of each feature. Since there is a difference between important sentences and unimportant...

Social media has become one of the most popular sources information. People communicate with each other and share their ideas, commenting on global issues events in a multilingual environment. While social been for several years, recently, it given an exponential rise online data volumes because increasing popularity local languages web. This allows researchers NLP community to exploit richness...

Previous researches on advanced representations for document retrieval have shown that statistical state-of-the-art models are not improved by a variety of different linguistic representations. Phrases, word senses and syntactic relations derived by Natural Language Processing (NLP) techniques were observed ineffective to increase retrieval accuracy. For Text Categorization (TC) are available f...

The huge amounts of data on the Internet often make difficult the user’s search for relevant information. For this reason, systems that are able to support users in this task could be a valuable help in this activity. Unfortunately, being able to catch user interests and represent them in a structured form is in general a problematic activity. Our research deals with the application of supervis...