By Content Ranking Information Retrieval
By Content Ranking Information Retrieval
By Content
Classical IR Ranking based on document's content
Top: Computers: Software: Information Retrieval: Ranking: By Content:
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- A survey of probabilistic models in information retrieval. [PDF format]
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- 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.
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- 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]
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- A Chapter in a book which introduces probabilistic retrieval.
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- Formal introduction to latent semantic indexing. [PS format]
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- Introduction to probabilistic models.
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- 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.
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- Evaluation of many combinations of term frequency statistics, document frequency statistics and document length normalization. [PDF format]
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- "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.
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