Ranking Link-based Ranking (2° generation) Reading 21.

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Presentation transcript:

Ranking Link-based Ranking (2° generation) Reading 21

Query-independent ordering First generation: using link counts as simple measures of popularity. Undirected popularity: Each page gets a score given by the number of in-links plus the number of out-links (es. 3+2=5). Directed popularity: Score of a page = number of its in-links (es. 3). Easy to SPAM

Second generation: PageRank Each link has its own importance!! PageRank is independent of the query many interpretations…

Basic Intuition… What about nodes with no in/out links?

Google’s Pagerank B(i) : set of pages linking to i. #out(j) : number of outgoing links from j. e : vector of components 1/sqrt{N}. Random jump Principal eigenvector r = [   T + (1-  ) e e T ] × r

Three different interpretations Graph (intuitive interpretation) Co-citation Matrix (easy for computation) Eigenvector computation or a linear system solution Markov Chain (useful to prove convergence) a sort of Usage Simulation Any node  Neighbors  “In the steady state” each page has a long-term visit rate - use this as the page’s score.

Pagerank: use in Search Engines Preprocessing: Given graph, build matrix Compute its principal eigenvector r r[i] is the pagerank of page i We are interested in the relative order Query processing: Retrieve pages containing query terms Rank them by their Pagerank The final order is query-independent   T + (1-  ) e e T

HITS: Hypertext Induced Topic Search

Calculating HITS It is query-dependent Produces two scores per page: Authority score: a good authority page for a topic is pointed to by many good hubs for that topic. Hub score: A good hub page for a topic points to many authoritative pages for that topic.

Authority and Hub scores a(1) = h(2) + h(3) + h(4) h(1) = a(5) + a(6) + a(7)

HITS: Link Analysis Computation Where a: Vector of Authority’s scores h: Vector of Hub’s scores. A: Adjacency matrix in which a i,j = 1 if i  j Thus, h is an eigenvector of AA t a is an eigenvector of A t A Symmetric matrices

Weighting links Weight more if the query occurs in the neighborhood of the link (e.g. anchor text).