This chapter gives an overview over the state-of-the-art in natural language processing for
ontology learning. It presents two main NLP techniques for knowledge extraction from text …

Natural Language Processing (NLP) is a scientific discipline which is found at the
intersection of fields such as Artificial Intelligence, Linguistics, and Cognitive Psychology …

Term weighting is one of the most commonly used approaches, which works by assigning
weights to terms, that aims to improve the performance of information retrieval or text …

Text classification (aka text categorisation) is an effective and efficient technology for
information organisation and management. With the explosion of information resources on …

Term dependence is a natural consequence of language use. Its successful representation
has been a long standing goal for Information Retrieval research. We present a …

Modeling users' preferences and needs is one of the most important personalization tasks in
information retrieval domain. In this paper a model for user profile tuning in document …

The availability of an abundance of knowledge sources has spurred a large amount of effort
in the development and enhancement of Information Retrieval techniques. Users' …

In the last decade, many data mining techniques have been proposed for fulfilling various
knowledge discovery tasks in order to achieve the goal of retrieving useful information for …

Terim ağırlıklandırma, metin sınıflandırmada sonuçlar üzerinde doğrudan etkili olan önemli
bir adımdır. Ancak, bir metin sınıflandırma problemi olarak ele alınan duygu analizinde farklı …

Adaptive information filtering is a challenging and fascinating problem. It requires the
adaptation of a representation of a user's multiple interests to various changes in them. We …