Large scale text mining approaches for information retrieval and extraction

The issues for Natural Language Processing and Information Retrieval have been studied for long time but the recent availability of very large resources (Web pages, digital documents.) and the development of statistical machine learning methods exploiting annotated texts (manual encoding by crowdsourcing is a new major way) have transformed these fields. This allows not limiting these approaches to highly specialized domains and reducing the cost of their implementation. For this chapter, our aim is to present some popular text-mining statistical approaches for information retrieval and information extraction and to discuss the practical limits of actual systems that introduce challenges for future. ??? 2014 Springer International Publishing Switzerland.Author is greatly indebted to Prof. Colette Faucher for the valuable comments and suggestions which immensely improve the quality and readability of the paper. Author also wishes to acknowledge Prof. Mikhail Moshkov and Dr. Igor Chikalov for continuous help and support in theoretical and computational aspects of the ongoing research at KAUST