CS404 Artifical Intelligence (NUIM)

Identify the top quality documents in a database that relate to some query:

• Query Dependent: Evaluate document quality in relation to some given query
• Query Independent (Page Rank): Evaluate document quality before (& independent of) any query terms. All ranking is done before any query arrives 

Precision: the number of relevant documents retrieved, divided by the total number of documents retrieved. (=sind möglichst viele die ich bekomme relevant?)

 \(Precision = \frac{\#RelevantRetrieved}{\#TotalDocuments}\)

Recall: the number of relevant documents retrieved divided by the total number of relevant documents in the long-term memory (=bekomme ich möglichst alle relevanten?)

\(Recall = \frac{\#RelevantRetrieved}{\#TotalRelevant}\)

• For a database of Hyperlinked documents
• Citations confer quality
• Citations from highly referenced documents are even better
• "Citation Ranking" of academic documents:
  • Google Scholar
  • Citeseer
  • Academic research microsoft

• H-index metric for Academic productivity and quality
• h-index = h if you have published h papers, each of which has at least h citations

• out-link = backlink
• Hyperlinks on a page are outlinks pointing to other pages on the web
• An inlink to one page is an outlink from another page 
• Link from A to B is an out-link from A but an in-link from B

• Consider sombody randomly following links across the web (occasionally restarting at a random page)
• He will frequently visit pages with many in-coming links (Pages with no in-link only get visited if hey actually starts at that page)
• The summation of many random walks gives a likelihood of visiting that page \(\rightarrow\) This is the Google PageRank score!
• Rank is based on theoretical visitors - not the number of people who actually visit a webpage

The PageRank of a page is the chance that a random surfer will lond on that page

\(PR(p) = (1-d) + d \cdot \sum_{(q,p) \in E} \frac{PR(q)}{outdegree(q)}\)

where PR = PageRank, d = 0.85, outdegree(q) = number of out-links contained on page q

• Iterative Calculation of the true PageRank value: Begin by assuming all pages PR(x) = 0.15
• Random iterative application of PageRank rule gradually "converges" to the final solution
• Average Page Rank alue is 1, a few highly ranked pages, and vast numbers of poorly linked pages near 0.15