Introduction to Information Retrieval

Class-tested and coherent, this groundbreaking new textbook teaches web-era information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. Written from a computer science perspective by three leading experts in the field, 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. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.

• Information Retrieval: Implementing and Evaluating Search Engines (The MIT Press)
• Foundations of Statistical Natural Language Processing
• Programming Pearls (2nd Edition)
• Relevant Search: With applications for Solr and Elasticsearch
• Speech and Language Processing, 2nd Edition
• Introduction to Algorithms, 3rd Edition (The MIT Press)
• Deep Learning (Adaptive Computation and Machine Learning)
• Pattern Recognition and Machine Learning (Information Science and Statistics)
• Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit
• The Algorithm Design Manual