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Link Prediction and Path Analysis using Markov Chains (R. R. Sarukkai) Presentation by H.Perrin, S.Jaffer, S.Lambert & W.Lewis 1.

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Presentation on theme: "Link Prediction and Path Analysis using Markov Chains (R. R. Sarukkai) Presentation by H.Perrin, S.Jaffer, S.Lambert & W.Lewis 1."— Presentation transcript:

1 Link Prediction and Path Analysis using Markov Chains (R. R. Sarukkai) Presentation by H.Perrin, S.Jaffer, S.Lambert & W.Lewis 1

2 Link Prediction & Path Analysis Volume of pages makes efficient WWW navigation difficult Aim: To analyse users' navigation history to generate tools that increase navigational efficiency – ie. Predictive server prefetching Provides tools for other work previously done.

3 The Author: Ramesh R. Sarukkai Researches Internet technologies Member of W3C committee Now works for Yahoo!

4 The Theory Proposed 4

5 Background: Markov Chains

6 The Theory (INCLUDING MATHS?)

7 The System

8 Applications 8

9 HTTP Request Prediction In server or proxy Allows pre-fetching of most likely pages first Connection latency is minimsed Server efficiency increases

10 Link Suggestion (Adaptive Web Navigation) Link prediction used to offer links to users based on previous navigation history Similar technique has been applied (ie. Amazon) – But not necessarily using Markov Chains Can be client or server side

11 Tour Generation Given a start URL, user guided along path of links Appropriate to user's interests Sequentially pick the next most popular link Non-cyclic

12 Hub/Authority Identification Kleinberg proposed Web 'Hub/Authorities' – Hub: Web site that is a good starting point for finding identification – Authority: Web site that contains useful information on a particular topic. Hub/Authority weighting given in Markov transitional weighting

13 Experimental Results


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