lecture6-tfidf-handout-6-per

Instead rank more relevant documents higher than less

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: duc)on to Informa)on Retrieval S ec. 6.3 Binary → count → weight matrix ! Hamlet Othello Macbeth 0 0 0 0.35 1.21 6.1 0 1 0 0 8.59 2.54 0 1.51 0.25 0 Calpurnia 0 1.54 0 0 0 0 Cleopatra 2.85 0 0 0 0 0 mercy   How o is computed (with/without logs)   Whether the terms in the query are also weighted   … The Tempest 3.18 Brutus   There are many variants Julius Caesar 5.25 Caesar t "q#d Antony and Cleopatra Antony tf.idft ,d 1.51 0 1.9 0.12 5.25 0.88 worser 1.37 0 0.11 4.15 0.25 1.95 Each document is now represented by a real-valued vector of tf-idf weights ∈ R|V| 25 Introduc)on to Informa)on Retrieval Sec. 6.3 Introduc)on to Informa)on Retrieval Sec. 6.3 Documents as vectors Queries as vectors So we have a |V| ­dimensional vector space Terms are axes of the space Documents are points or vectors in this space Very high ­dimensional: tens of millions of dimensions when you apply this to a web search engine   These are very sparse vectors  ­ most entries are zero.   Key idea 1: Do the same for queries: represent them as vectors in the space   Key idea 2: Rank documents according to their proximity to the query in this space   proximity = similarity of vectors   proximity ≈ inverse of distance   Recall: We do this because we want to get away from the you re ­either ­in ­or ­out Boolean model.   Instead: rank more relevant documents higher than less relevant documents         Introduc)on to Informa)on Retrieval Sec. 6.3 Formalizing vector space proximity   First cut: distance between two points   ( = distance between the end points of the two vectors)   Euclidean distance?   Euclidean distance is a bad idea . . .   . . . because Euclidean distance is large f...
View Full Document

This document was uploaded on 02/26/2014.

Ask a homework question - tutors are online