Directory of By Content Resources

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Classical IR Ranking based on document's content

Resources in This Category

• A Case Study in Web Search Using TREC Algorithms

  http://www10.org/cdrom/papers/317/
  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.

• Document Ranking and the Vector-Space Model.

  http://www.cs.ust.hk/~dlee/Papers/ir/ieee-sw-rank.ps.gz
  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]

• Exploring the Similarity Space

  http://goanna.cs.rmit.edu.au/~jz/fulltext/sigirforum98.pdf
  Evaluation of many combinations of term frequency statistics, document frequency statistics and document length normalization.

• Information Retrieval Tutorial

  http://isp.imm.dtu.dk/thor/projects/multimedia/textmining/
  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.

• Latent Semantic Indexing: a Probabilistic Analysis

  http://www.cs.berkeley.edu/~christos/ir.ps
  Formal introduction to latent semantic indexing. [PS format]

• Probabilistic Models in Information Retrieval

  http://www.is.informatik.uni-duisburg.de/bib/docs/Fuhr_92.html
  Introduction to probabilistic models.

• Probabilistic Retrieval

  http://www.dcs.gla.ac.uk/Keith/Chapter.6/Ch.6.html
  A Chapter in a book which introduces probabilistic retrieval.

• Ranking Algorithms

  http://www.dcc.uchile.cl/~rbaeza/iradsbook/irbook.html
  "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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