The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …

Introduction to Information Retrieval is the first textbook with a coherent treatment of classical
and web information retrieval, including web search and the related areas of text …

Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

A novel probabilistic retrieval model is presented. It forms a basis to interpret the TF-IDF term
weights as making relevance decisions. It simulates the local relevance decision-making for …

This paper reviews state-of-the-art techniques and methods for enhancing effectiveness of
cross-language information retrieval (CLIR). The following research issues are covered:(1) …

Statistical language modeling has been successfully used for speech recognition, part-of-
speech tagging, and syntactic parsing. Recently, it has also been applied to information …

This paper describes a brief history of the research and development of information retrieval
systems starting with the creation of electromechanical searching devices, through to the …

Jackson, Peter, 1948-Natural language processing for online applications: text retrieval,
extraction and categorization/Peter Jackson and Isabelle Moulinier.--2nd rev. ed. p. cm …

Because of the world wide web, information retrieval systems are now used by millions of
untrained users all over the world. The search engines that perform the information retrieval …

Ranking in information retrieval has been traditionally approached as a pursuit of relevant
information, under the assumption that the users' information needs are unambiguously …