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By Christopher D. Manning
By Prabhakar Raghavan
By Hinrich Schütze
Publisher: Cambridge University Press
Print Publication Year: 2008
Online Publication Date:June 2012
Chapter DOI: http://dx.doi.org/10.1017/CBO9780511809071.007
Thus far, we have dealt with indexes that support Boolean queries: A document either matches or does not match a query. In the case of large document collections, the resulting number of matching documents can far exceed the number a human user could possibly sift through. Accordingly, it is essential for a search engine to rank-order the documents matching a query. To do this, the search engine computes, for each matching document, a score with respect to the query at hand. In this chapter, we initiate the study of assigning a score to a (query, document) pair. This chapter consists of three main ideas.
Section 6.4 develops several variants of term-weighting for the vector space model. Chapter 7 develops computational aspects of vector space scoring and related topics.