IR-part2

3 0 0 1 1 1 052 0 best 1 1 50000 13 13 034 0 0 0 0 0

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Unformatted text preview: maximal similarity. §༊  Key idea: Rank documents according to angle with query. Introduc)on to Informa)on Retrieval Sec. 6.3 From angles to cosines §༊  The following two no*ons are equivalent. §༊  Rank documents in decreasing order of the angle between query and document §༊  Rank documents in increasing order of cosine(query,document) §༊  Cosine is a monotonically decreasing func*on for the interval [0o, 180o] Introduc)on to Informa)on Retrieval Sec. 6.3 From angles to cosines §༊  But how – and why – should we be compu*ng cosines? Introduc)on to Informa)on Retrieval Sec. 6.3 Length normaliza*on §༊  A vector can be (length- ) normalized by dividing each of its components by its length – for this we use the L2 norm: 2 x2= ∑x ii §༊  Dividing a vector by its L2 norm makes it a unit (length) vector (on surface of unit hypersphere) §༊  Effect on the two documents d and dʹȃ (d appended to itself) from earlier slide: they have iden*c...
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