Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

This book provides a simple but precise framework for describing complex predicates and related constructions, and applies it principally to the analysis of complex predicates in Romance, and certain serial verb constructions in Tariana and Miskitu. The authors argue for replacing the projection architecture of LFG with a notion of differential information spreading within a unified feature structure. Another important feature is the use of the conception of argument-structure in Chris Manning's Ergativity to facilitate the description of how complex predicates are assembled. In both of these aspects the result is a framework that preserves the descriptive parsimony of LFG while taking on key ideas from HPSG.

情報検索の基礎を扱った網羅的で最先端の入門書

統計的自然言語処理について基礎となる統計学、情報理論、言語学から、中心的な問題や応用まで丁寧に積み上げた解説がされている。