lecture18-learning-ranking-handouts-6-per

G the characters in the query 2 53011

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

This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview:   URL contains “~”?  Page edit recency?  Page length?    Well compute a score in [0,1] for each doc d and for  each query q using a linear combina)on of sT and sB    Major web search engines publicly state that they use  “hundreds” of such features – and they keep changing  Introduc)on to Informa)on Retrieval Sec. 6.1.2  Thus our scores are all 0, g, 1‐g or 1.    g is a parameter to be learned from examples Introduc)on to Informa)on Retrieval Sec. 6.1.2  We are given examples  Least square errors    Created by human judges    For each human‐judged example, we compute its  squared error:    Then we can compute a total error of    We quan)ze the human relevance judgments to be 1  or 0 respec)vely, for Relevant and Non‐relevant    We will pick g to minimize this total error.    The scores we compute will be 0, g, 1‐g or 1 ...
View Full Document

Ask a homework question - tutors are online