By Content

Sites 8

• 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.