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Enhancing Web Search by Promoting Multiple Search Engine Use

Enhancing Web Search by Promoting Multiple Search Engine Use. Ryen W. W., Matthew R. Mikhail B. (Microsoft Research) Allison P. H (Rice University) S IGIR 2008 Presented by Jae-won Lee. Introduction. Users are generally loyal to one search engine

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Enhancing Web Search by Promoting Multiple Search Engine Use

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  1. Enhancing Web Search by Promoting Multiple Search Engine Use Ryen W. W., Matthew R. Mikhail B. (Microsoft Research) Allison P. H (Rice University) SIGIR 2008 Presented by Jae-won Lee

  2. Introduction • Users are generally loyal to one search engine • Even though it may not satisfy their needs • A given search engine performs well for some queries and poorly for others • Excessive loyalty can hinder search effectiveness • Our Goal • Support engine switching by recommending the most effective search engine for a given query Center for E-Business Technology

  3. Related Work • Meta search engines such as Clusty and Dogpile • Merge search results • Switching search engine is more attractive • Strong brand loyalty may discourage users from migrating to meta search engine • Meta search engine eliminates the benefits of interface feature of each engine • Hurts source engine brand awareness • We lets users keep their default engine • Suggest an alternative engine if it performs better for the current query Center for E-Business Technology

  4. Does Switching Help Users? • Potential Benefits of Switching • We quantify the benefits of multiple engine use • Normalized Discounted Cumulative Gain (NDCG) • Measure a topical relevance of results to a given query • Click-through rate for search results • Reasonable estimation of search result utility • NDCG • A measure to evaluate the Web search engine performance • Where Ni : a constant for normalization • r(i) : relevance score of the ith result, 0 (bad) ~ 5 (perfect) Center for E-Business Technology

  5. Does Switching Help Users? • Potential Benefits of Switching (cont’d) • X, Y, and Z are anonymous notations of Google, Yahoo, and Live Search Number of queries for which engine performs best • Engine choice for particular query is important Center for E-Business Technology

  6. Switching as Classification - Query Processing Query Search Engines Result sets Feature Extractor Classifier (offline Training) Features Recommend a Search Engine Center for E-Business Technology

  7. Classifier Features • Classifier must recommend an engine in real-time • Derive features from result pages, a query and query-result matching • Features • Features from result pages • Features from the query • Features from the query-result page match Center for E-Business Technology

  8. Classifier Features Center for E-Business Technology

  9. Classifier • Notation • q : query • R : result page of original engine • R’ : result page of target engine • R* = {(d1,s1), …, (dk,sk)} : Human-judged result set - dk(result page), sk(score) • Utility of each engine : U(R) = NDCGR*(R) , U(R’) = NDCGR*(R’) • Training • Each training instance D = {(x, y)} • x = f(q, R, R’) ; comprised of features derived from the query and result page • y = 1 iff NDCGR*(R’) >= NDCGR*(R) + margin • Switching engine if utility is higher by at least some margin Center for E-Business Technology

  10. Experiments • Evaluate accuracy of switching support to determine its viability • Data Set • From Google, Yahoo, Live Search logs Center for E-Business Technology

  11. Precision – Recall Results • The proposed method can achieve high accuracy • Therefore, the method can be used for providing useful search engine suggestions to users Center for E-Business Technology

  12. Avoiding Querying the Alternative Engine • Evaluating the utility of target engine is undesirable to some users due to the network traffic • So, only use the features from the current engine’s result pages Center for E-Business Technology

  13. Contribution of Features • All sets of features contribute to accuracy • Features obtained from result pages seems to provide the most benefit Center for E-Business Technology

  14. Conclusion • Demonstrated potential benefit of switching • Described a method for automatically determining when to switch engines for a given query • Evaluated the method and illustrated good performance, especially at usable recall Center for E-Business Technology

  15. Pros. & Cons. • Pros. • Propose a new research area of IR by switching support • Good explanation for user behavior • Cons. • Poor explanation for equations • No analysis for the experiment results Center for E-Business Technology

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