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search
...Interactive search formulation A user confronted with an automatic retrieval system is unlikely to be able to express his information need in one go
...1 the frequency of occurrence in the data base of his search terms;2 the number of documents likely to be retrieved by his query;3 alternative and related terms to be the ones used in his search;4 a small sample of the citations likely to be retrieved;and 5 the terms used to index the citations in 4
...All this can be conveniently provided to a user during his search session by an interactive retrieval system
...The sample of citations and their indexing will give him some idea of what kind of documents are likely to be retrieved and thus some idea of how effective his search terms have been in expressing his information need
...Examples,both operational and experimental,of systems providing mechanisms of this kind are MEDLINE [11]...We now look at a mathematical approach to the use of feedback where the system automatically modifies the query
...Feedback The word feedback is normally used to describe the mechanism by whicha system can improve its performance on a task by taking |
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of presenting the basic theory;I have chosen to present it in such a way that connections with other fields such as pattern recognition are easily made
...The fundamental mathematical tool for this chapter is Bayes Theorem:most of the equations derive directly from it
...This was recognised by Maron in his The Logic Behind a Probabilistic Interpretation as early as 1964 [4]...Remember that the basic instrument we have for trying to separate the relevant from the non relevant documents is a matching function,whether it be that we are in a clustered environment or an unstructured one
...It will be assumed in the sequel that the documents are described by binary state attributes,that is,absence or presence of index terms
...Estimation or calculation of relevance When we search a document collection,we attempt to retrieve relevant documents without retrieving non relevant ones
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