1	Web Information Seeking CS6210 survey presentation Guo Shuqiao Yang Hui 15 Oct 2003
2	Outline Introduction Review on Mental Model Study Current Research Trends Hyperlink Pattern Modeling Web Information Seeking and Other Research Areas Conclusion and Perspectives
3	Introduction Information seeking Berry Picking The process engaged in by humans to change their state of knowledge Web Information Seeking Web: The biggest digital library available ( > 2 billion pages) heterogeneous collection of information resources with minimal selection, organization, and retrieval standards Differ from Traditional Digital Library No real organization No control of Input No control of customer set
4	Outline Introduction Review on Mental Model Study Current Research Trends Hyperlink pattern modeling Web Information Seeking and Other Research Areas Conclusion and Perspectives
5	Study on Mental Models [Slone 02] examined the influences of user’s mental model and the impact on their searching behavior
6	Influencing Factors and Results User’s understanding of the Web User’s experience Mental model User’s expectation User’s Goal Situational goals Specific search goals Format goals
7	Outline Introduction Review on Mental Model Study Current Research Trends Hyperlink pattern modeling Web Information Seeking and Other Research Areas Conclusion and Perspectives
8	Current Research Trends Content-based approaches [Michael03] HTML body text Title and headings Anchor text, etc Link-based approaches Link structure infers information about pages Surfing behavior of users can be abstract into patterns
9	Link Pattern Modeling - I Markov chains model [Sarukkai 00] Create probability distribution about which of the previous links is ‘good predictors’ of the next link.
10	Link Pattern Modeling - I Markov chains model [Sarukkai 00] Markov chains and eigen-vector decomposition techniques A : matrix representing transition probabilities s(t): probability vector for all the states at time t
11	Link Pattern Modeling - II Longest Repeating Subsequence Model [Pitkow 99] Surfing paths can be represented as n-grams <X1, X2,…Xn> to indicate sequences of page clicks by a population of users visiting a web site Find Longest repeating subsequence E.g., 135 in 15135213544 Match the performance accuracy of the one-hop Markov model while reducing the complexity by nearly 33%
12	Link Pattern Modeling - III Application of Link Pattern Modeling Link prediction and Prefetching Agent Assisted Navigation Web Community Website Organization and Optimization Personalization Limitations Goodness of the models depends on the amount of training data available Dimensionality (Markov chain matrix is typically very large)
13	Outline Introduction Review on Mental Model Study Current Research Trends Hyperlink pattern modeling Web Information Seeking and Other Research Areas Conclusion and Perspectives
14	Related Research Areas Information Retrieval Search engines PageRank HITS Information Extraction Web Topic detection Data Mining Data warehousing Web log analysis
15	Outline Introduction Review on Mental Model Study Current Research Trends Hyperlink pattern modeling Web Information Seeking and Other Research Areas Conclusion and Perspectives
16	Conclusion and Perspectives Conclusion Quick Review of Web Information Seeking Mental Model Study Current Research Trends Relationship to Other Research Areas Perspectives Natural Language Processing Multimedia Interaction Digitalized Library Interview Life-long Assisted Education Persistence and Web Security
17	References Slone (02) The Influence of Mental Models and Goals on Search Patterns During Web Interaction, JASIST 53(13):1152-1169 (2002). CL: Z671 JASIT Sarukkai (00) Link prediction and path analysis using Markov chains, WWW 8. James Pitkow and Peter Pirolli (99) Mining Longest Repeating Subsequences to Predict WWW Surfing, USITS' 99.
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