A Case Study in Web Search Using TREC Algorithms - This study evaluates the performance of a state-of-the-art keyword-based document ranking algorithm (coming out of TREC) on a popular web search task. Information Retrieval Tutorial - Description of boolean retrieval, vector space model, probabilistic retrieval, latent semantic indexing and other IR topics. An introduction to various classical ranking methods is also provided. Document Ranking and the Vector-Space Model. - It describes key issues in document ranking techniques based on the vector­ space model. Several TF*IDF variants are discussed. The cosine measure, recall and precision are introduced. [PS format] Latent Semantic Indexing: a Probabilistic Analysis - Formal introduction to latent semantic indexing. [PS format] Probabilistic Retrieval - A Chapter in a book which introduces probabilistic retrieval. Ranking Algorithms - "Ranking Algorithms" is chapter 14 in the Frakes and Baeza-Yates book. It gives a good discussion of the tradeoffs and choices among different term-weighting strategies. Exploring the Similarity Space - Evaluation of many combinations of term frequency statistics, document frequency statistics and document length normalization. Probabilistic Models in Information Retrieval - Introduction to probabilistic models.