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• Introduction to  Information Retrieval - The primary textbook for the course; by Christopher D. Manning, Prabhakar Raghavan and Hinrich Schutze, Cambridge University Press. 2008.

• General Resources
  • Information Retrieval Resources - Resource page for the Manning et al. IR Text book.
  • IR Resources (university of Glasgow)
  • Information Retrieval (Online book by van Rijsbergen)
  • Search Engine Watch
  • ACM SIGIR
  • TREC Home Page
  • Web IR Resources
• Tools and Software
  • Google API
  - use Google's indexing & search services to build your own application.
  • Apache Lucene - a  full-featured text search engine library in Java
  • Nutch - Apache's open-source web crawler based on Java.
  • BeautifulSoup: A general parsing library for Python particularly useful for parsing html and xml.
  • NLTK: Natural Language Toolkit for Python, including tools for text preprocessing, tokenization, and vectorization (you may  also be interested in an online book that shows how NLTK is used).
  • Apache OpenNLP: A Java-based library for the processing of natural language tex with components such as sentence detector, tokenizer, name finder, document categorizer, part-of-speech tagger, etc.
  • Mallet: MAchine Learning for LanguagE Toolkit is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
  • Stanford CoreNLP: CoreNLP is a one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 8 languages: Arabic, Chinese, English, French, German, Hungarian, Italian, and Spanish.
• WordNet
• MySQL full text search
• Text to Matrix Generator, a MATLAB toolbox for indexing, retrieval and other text processing tasks.
• scikit-learn: a robust machine learning library building on top of NumPy, SciPy and matplotlib. Includes of a wide variety of modeling techniques.
• Pandas (python data analysis library): data structures and tools for common data analysis tasks, including an efficient data frame implementation (similar to R).
• Other Related and Useful Links
  • Common IR Test Collections
  • A Small Stop List (Recommended for Projects)
  • Porter's Stemming Algorithm
  • A Big Stop List