Reading Notes - Unit 7

IIR Chapter 9

• Relevance feedback and query expansion
• Relevance feedback pseudo relevance feedback
• The Rocchio algorithm for relevance feedback
• classic algorithm for implementing feedback
• models feedback into vector space model
• Probabilistic relevance feedback
• Naive Bayes probabilistic model
• When does it work?
• relies on assumptions
• user must have enough knowledge 
• On the web
• Excite tried full relevance feedback but it was dropped
• Evaluation of relevance feedback strategies
• 1-2 rounds of feedback
• Pseudo relevance feedback
• method for automatic local analysis
• Indirect relevance feedback
• also called implicit
• DirectHit used this
• Global method for query reformulation
• Vocab tools
• stemming
• thesaurus
• Query Expansion
• Users give feedback
• Automatic thesaurus generation
• analyze documents automatically

Relevance Feedback Revisited

     This study showed the that relevance feedback worked.  Specifically it showed that by using query expansion and query reweighing you could show improvements of 100%.  It also showed that the more the merrier when it came to rounds of relevance feedback.

A Study of Methods for Negative Relevance Feedback

     All about negative relevance feedback models.  They look at a bunch of models. They found that the language model were more effective than those.

Improving the Effectiveness of Information Retrieval with Local Context Analysis

     This paper is about local context analysis,  a new model that they proposed.  It worked with both English AND non-English collections. They found it worked better than any other model. They say they are going to continue on this work and look into when to expand queries.