1. Searching for the Best Engine 2007. 12. 07 Presented by Gong GI Hyun, IDS Lab., Seoul National University

2. Copyright  2007 by CEBT Search Engine  1 st generation (X) 1995, Digital Equipment Corp figured out how to store the words on Web pages as an index that lent itself to lightning-fast searches.  2 nd generation ( △ ) Google's innovation was to further rank a Web page by the other pages that link to it, on the somewhat shaky assumption that if a page is much linked-to. "The Google results just had too much stuff I wasn‘t looking for.”  3 rd generation (?) Semantic Web? Personalization? Social network? IDS Lab. Seminar - 2Center for E-Business Technology

3. Copyright  2007 by CEBT 5 Problems with Today's Web Search  Too many search results and too many irrelevant search results. After spending time on the first few pages of the search results, you don't have time or patience to go beyond those pages.  No ability to manage the results by defining context or meaning. It is not easy to build an advanced search query. Lack of hints for search.  No user-friendly visual management with mouse click.  Documents are ranked by a search engine according to an algorithm. specific to a search engine, and not specific to your interests.  Over-ranked commercial and under-ranked non-commercial search results. IDS Lab. Seminar - 3Center for E-Business Technology

4. Copyright  2007 by CEBT Semantic Search  We need algorithms that match the meaning of concepts and emulate "understanding“  The sense of a word as a factor in its ranking algorithm.  One of the first impacts of semantic search engine will be on the handling of long-tail queries. Popularity algorithms fail at the long-tail queries, because there is never enough statistical sampling. The idea of "personalized search" actually requires semantic capabilities without the need for tracking the user's behavior.  NLP based “Semantic Search Engine” approach : HAKIA IDS Lab. Seminar - 4Center for E-Business Technology

5. Copyright  2007 by CEBT Long Tail Query IDS Lab. Seminar - 5Center for E-Business Technology

6. Copyright  2007 by CEBT Is Semantic Technology the Answer?  Peter Norvig : “They don't want the burden of having to express it as a fu ll sentence.”  Google AdSense?  NLP processing? NLP may well be web 4.0 and semantic web. IDS Lab. Seminar - 6Center for E-Business Technology

7. Copyright  2007 by CEBT What is the “Perfect Search”?  What do we expect when we enter a term into a search box? Get the Perfect Answer.  Can we explain what we want perfectly?  Can we expect the "perfect" answer all the time?  Interaction is needed (Google does not do that) Excuse me, what do you mean? Did you mean to look for ~~? IDS Lab. Seminar - 7Center for E-Business Technology

8. Copyright  2007 by CEBT The Alternative Search Engine of the Year, 2007! IDS Lab. Seminar - 8Center for E-Business Technology

9. Copyright  2007 by CEBT Quintura : Semantic Map  As you click on words, they get added to your query, causing the words in your map to update and restrict the focus of your search, allowing you to quickly and graphically structure very specific queries.  By clicking through a semantic map will allow you To spend less time sifting through irrelevant results. To refine the search when you're not exactly sure of the query you should be using. IDS Lab. Seminar - 9Center for E-Business Technology

10. Copyright  2007 by CEBT References  Quintura, Staking The Future In Semantic Mapping  Semantic search antidote for poor relevancy, ReadwriteWeb  Taking on Google: Is Semantic Technology the Answer?, Gord Hotchkiss  Is google a semantic search engine?, ReadwriteWeb  Overview of clustering, ReadwriteWeb  Search Engine of the year, ReadwriteWeb IDS Lab. Seminar - 10Center for E-Business Technology