1 / 46

Making the Web Searchable

Making the Web Searchable. Peter Mika Researcher, Data Architect Yahoo! Research. Yahoo! Research (research.yahoo.com). Yahoo! Research Barcelona. Established January, 2006 Led by Ricardo Baeza-Yates Research areas Web Mining content, structure, usage Distributed Web retrieval

Download Presentation

Making the Web Searchable

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Making the Web Searchable Peter Mika Researcher, Data Architect Yahoo! Research

  2. Yahoo! Research (research.yahoo.com)

  3. Yahoo! Research Barcelona • Established January, 2006 • Led by Ricardo Baeza-Yates • Research areas • Web Mining • content, structure, usage • Distributed Web retrieval • Multimedia retrieval • NLP and Semantics

  4. Yahoo! by numbers (April, 2007) • There are approximately 500 million users of Yahoo! branded services, meaning we reach 50 percent – or 1 out of every 2 users – online, the largest audience on the Internet (Yahoo! Internal Data). • Yahoo! is the most visited site online with nearly 4 billion visits and an average of 30 visits per user per month in the U.S. and leads all competitors in audience reach, frequency and engagement (comScore Media Metrix, US, Feb. 2007). • Yahoo! accounts for the largest share of time Americans spend on the Internet with 12 percent (comScore Media Metrix, US, Feb. 2007) and approximately 8 percent of the world’s online time (comScore WorldMetrix, Feb. 2007). • Yahoo! is the #1 home page with 85 million average daily visitors on Yahoo! homepages around the world, an increase of nearly 5 million visitors in a month (comScore WorldMetrix, Feb. 2007). • Yahoo!’s social media properties (Flickr, delicious, Answers, 360, Video, MyBlogLog, Jumpcut and Bix) have 115 million unique visitors worldwide (comScore WorldMetrix, Feb. 2007). • Yahoo! Answers is the largest collection of human knowledge on the Web with more than 90 million unique users and 250 million answers worldwide (Yahoo! Internal Data). • There are more than 450 million photos in Flickr in total and 1 million photos are uploaded daily. 80 percent of the photos are public (Yahoo! Internal Data). • Yahoo! Mail is the #1 Web mail provider in the world with 243 million users (comScore WorldMetrix, Feb. 2007) and nearly 80 million users in the U.S. (comScore Media Metrix, US, Feb. 2007) • Interoperability between Yahoo! Messenger and Windows Live Messenger has formed the largest IM community approaching 350 million user accounts (Yahoo! Internal Data). • Yahoo! Messenger is the most popular in time spent with an average of 50 minutes per user, per day (comScore WorldMetrix, Feb. 2007). • Nearly 1 in 10 Internet users is a member of a Yahoo! Groups (Yahoo! Internal Data). • Yahoo! is one of only 26 companies to be on both the Fortune 500 list and the Fortune’s “Best Place to Work” List (2006).

  5. Agenda • The Annotated Web • SearchMonkey • Demo • Technology • DataRSS format • Query language • Lessons learned • Toward Semantic Search • BOSS • Build your Own Search Service • Y!OS 1.0 • Yahoo! Open Strategy

  6. The Annotated Web

  7. Previously in search • Horizontal search • Yahoo… • Keyword-based indexing • Minimal natural language processing • Limited experiments with ontologies (query expansion) • Vertical search • e.g. shopping.com, Kelkoo • Faceted search, browsing • Fixed ontology • Combinations • Google Base, Google Co-op • Web-scale, but fixed ontologies • Proprietary technology • Can we do better with the Semantic Web? • Address the long tail of queries (88% of queries) • Use standard technology • Not a new question. But the answer may be new.

  8. Which Semantic Web? • Two visions • Data Web • Bringing the content of databases to the Web (linkeddata.org) • Rich data, heavyweight semantics • Deep Web • Annotated Web • Annotating the content of Web resources (documents, mm) • Simple data, lightweight semantics • Shallow Web • This presentation is about the Annotated Web.

  9. Brief history of the Annotated Web • 1995: HTML meta tags • 1996: Simple HTML Ontology Extensions (SHOE) • 1998: RDF/XML • RDF/XML in HTML • RDF linked from HTML • 2003: Web 2.0 • Tagging • Microformats • Metadata in Wikipedia • Machine tags in Flickr • 2005: eRDF • 2008: RDFa

  10. RDF-based annotation #1: eRDF • eRDF • Ian Davis (Talis) • Embedding RDF in HTML • Straightforward mapping to RDF triples (XSLT available) • HTML4 compatible • More complex than microformats • Use any RDF/OWL vocabulary • Reuse of semantic-bearing HTML elements is limited • More limited than RDF • No blank nodes • No data types • No statements about subjects other than the current document • Limited usage

  11. RDF-based annotation #2: RDFa • RDFa • World Wide Web Consortium (W3C) last call document • Similar intent as eRDF, but full RDF support • Requires XHTML • Big question: user complexity ( data quality) <p typeof="contact:Info" about="http://example.org/staff/jo"> <span property="contact:fn">Jo Smith</span>. <span property="contact:title">Web hacker</span> at <a rel="contact:org" href="http://example.org"> Example.org </a>. You can contact me <a rel="contact:email" href="mailto:jo@example.org"> via email </a>. </p> ...

  12. SearchMonkey

  13. SearchMonkey • Creating an ecosystem of publishers, developers and end-users • Motivating and helping publishers to implement semantic annotation • Providing tools for developers to create compelling applications • Focusing on end-user experience • Rich abstracts as a first application • Addressing the long tail of query and content production • Standard Semantic Web technology • dataRSS = Atom + RDFa • Industry standard vocabularies • http://developer.yahoo.com/searchmonkey/

  14. What is SearchMonkey? an open platform for using structured data to build more useful and relevant search results Before After

  15. Enhanced Result deep links image name/value pairs or abstract

  16. Infobar YAHOO! CONFIDENTIAL | 27

  17. SearchMonkey 1 site owners/publishers share structured data with Yahoo!. site owners & third-party developers build SearchMonkey apps. 2 consumers customize their search experience with Enhanced Results or Infobars 3 Page Extraction RDF/Microformat Markup Acme.com’s Web Pages Index DataRSS feed Web Services Acme.com’s database

  18. Developer tool

  19. Developer tool

  20. Developer tool

  21. Developer tool

  22. Developer tool

  23. Gallery

  24. Example apps • LinkedIn • hCard plus feed data • Creative Commons by Ben Adida • CC in RDFa

  25. Example apps. II. • Other me by Dan Brickley • Google Social Graph API wrapped using a Web Service

  26. DataRSS <?profile http://search.yahoo.com/searchmonkey-profile ?> <feed xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.w3.org/2005/Atom ../latest/xsd/datarss.xsd“> <id>http://www.linkedin.com/datarss/</id> <author> <name>Peter Mika (pmika@yahoo-inc.com)</name> </author> <title>Example data feed for social</title> <updated>2007-11-14T04:05:06+07:00</updated> <entry> <!-- title field of entry is not used for anything --> <title>Peter Mika</title> <!--URL of the webpage extracted from --> <id>http://www.linkedin.com/ppl/webprofile?id=5054019</id> <updated>2007-11-14T04:05:06+07:00</updated> <content type="application/xml"> <y:adjunct version="1.0" name="social-simple" xmlns:y="http://search.yahoo.com/datarss/"> <y:item rel="dc:subject"> <y:type typeof="foaf:Person"> <y:meta property="foaf:name">John Doe</y:meta> <y:meta property="foaf:gender">male</y:meta> <y:item rel="foaf:homepage" resource="http://www.joeisageek.com"/> <y:item rel="foaf:mbox" resource="mailto:johndoe@example.org"/> <y:item rel="foaf:weblog" resource="http://johnblog.example.org"/> <y:item rel="foaf:knows"> <y:type typeof="foaf:Person"> <y:meta property="foaf:name">Jane Doe</y:meta> <y:meta property="foaf:gender">female</y:meta> <y:item rel="foaf:mbox" resource="mailto:janedoe@example.org"/> </y:type> </y:item> </y:type> </y:item> </y:adjunct> </entry> </feed> Atom 1.0 XML + RDFa

  27. The data part <adjunct version="1.0" id=“com.yahoo.page.rdfa" xmlns="http://search.yahoo.com/datarss/“ updated=“2007-11-14T04:05:06+07:00”> <item rel="dc:subject"> <type typeof="foaf:Person"> <meta property="foaf:name">John Doe</meta> <meta property="foaf:gender">male</meta> <item rel="foaf:homepage" resource="http://www.joeisageek.com"/> <item rel="foaf:mbox" resource="mailto:johndoe@example.org"/> <item rel="foaf:weblog" resource="http://johnblog.example.org"/> <item rel="foaf:knows"> <type typeof="foaf:Person"> <meta property="foaf:name">Jane Doe</meta> <meta property="foaf:gender">female</meta> <item rel="foaf:mbox" resource="mailto:janedoe@example.org"/> </type> </item> </type> </item> </adjunct>

  28. DataRSS • An Atom extension for structured data • Why a new format? • A feed format is required by publishers • Exclusive content (e.g. partnerships, paid inclusion) • No changes necessary to the web page • No standard named graph format for the Semantic Web • Needed to capture meta-metadata such as source and timestamp of information • Not really a new format • An Atom extension • Use any RDFa parser to get the triples out • cf. Google Base feeds

  29. What happened since the launch? • It’s starting to work! • Click rates improve  Publishers are willing to invest  More structured data  More applications  More users  Click rates improve • Increasing excitement all around • Standardization of RDFa is bringing new energy • Good market for companies that help publishers to ‘semantify’ or support developers in extracting structured from web pages • OpenCalais, Dapper, AdaptiveBlue, Intel MashMaker, Zemanta… • There have been some lessons learned…

  30. Data quality • Publishers/developers want the quick and dirty answer, not the long and clean one • Resource or literal? • <meta property=“vcard:url”>http://www.example.org</meta> • <meta property=“vcard:tel”>0034691792522</meta> • Webpage or resource? • Should we allow a resource have the same URI as an existing webpage? • This is the default in eRDF/RDFa! • <div class=“foaf-name”>Peter Mika</div> • Types vs. datatypes • <meta property=“use:email”>pmika@cs.vu.nl</meta> • Extensibility • rdfs:movies Complexity of the formalism = Data quality down

  31. Vocabularies • Coverage is small • Books, movies, stuff people care about… • Competing proposals • Versions floating around • Not maintained • I cannot maintain your vocabulary for you • Vocabularies for microformats • A must • The role of the W3C • Ontologies as member submission…. • Vocabularies not designed for the annotated Web Distributed ontology development = Mess

  32. eRDF • Difficult for complex pages and dangerous in non-expert hands • Serious limitations • No datatypes • No subjects other than identifiers within the current page • Reuse of the id attribute <div id=“blue_panel”> <span class=“foaf-name”>Peter Mika</span> <div id=“white_clickable_thingy_on_the right”> <span class=“foaf-mbox”>pmika@hotmail.com</span> ….

  33. RDFa • A huge improvement • E.g. no repurposing of HTML attributes • Still, not everything is intuitive to the uninitiated: <div about=“#id”> <span property=“foaf:name“>Peter Mika</span> <span rel=“foaf:img“ typeof=“foaf:Image”> <span property=“dc:format”>jpg</span> … </span </div> <div about=“#id”> <span property=“foaf:name“>Peter Mika</span> <span rel=“foaf:img“ resource=“http://www.example.org/photo.jpg”> <span typeof=“foaf:Image”> <span property=“dc:format”>jpg</span> </span </span </div>

  34. Semantic Search

  35. Semantics and IR • Hard searches that cannot be solved with purely syntactical approach • Ontologies in IR shown to work in limited domains • In Web IR most attempts (e.g. query expansion) have failed • What is new? The scale and breadth. • Growth in annotations, all domains (Web 2.0) • Data Web vs. Deep Web

  36. Hard searches • Ambiguous searches • Paris Hilton • Multimedia search • Images of Paris Hilton • Imprecise or overly precise searches • Publications by Jim Hendler • Find images of strong and adventurous people (Lenat) • Searches for descriptions • Search for yourself without using your name • Product search (ads!) • Searches that require aggregation • Size of the Eiffer tower (Lenat) • Public opinion on Britney Spears • Queries that require a deeper understanding of the query, the content and/or the world at large • Note: some of these are so hard that users don’t even try them any more

  37. Example…

  38. Application: query intent Paris Hilton is a person!

  39. Application: query intent #2 Hugo is a person!

  40. Time to experiment! • Future work in IR • Ranking documents • Ranking resources/triples • Ranking resources in the presence of documents • New interfaces • Query interface • Result presentation • Metrics • Precision/recall • CTR • ROI

  41. Time to experiment! #2 • Future work in Semantic Web • (Semi-)automated ways of metadata creation (NLP!) • Entity resolution • Scale • Data quality • We allow providing metadata for other people’s sites! • Reasoning • To the extent that it’s useful • Constraints • Keyword-based search can not suffer • Preference for very conservative solutions • Metadata in the context of documents • Assumption is still that the user will want to see/visit the source • (what to do with linked data?)

  42. Going even further… • NLP, Information Extraction • New types of application • Aggregators • Stateful apps • Intent-driven apps • Mobile apps • … • Beyond search • Analysis, design, diagnosis etc. on top of aggregated data • Personalization • Building rich user profiles • Re-ranking results based on interests • Monetization • No more “buy virgins on eBay”

  43. BOSS: Build your Own Search Service • Unlimited queries per day • Ability to re-order results and blend-in addition content • No restrictions on presentation • No branding or attribution • Access to multiple verticals (web search, image, news) • Ability to monetize • 40+ supported language and region pairs • http://developer.yahoo.com/search/boss/

  44. Y!OS 1.0 • Yahoo! Open Strategy • Yahoo! Social Platform • Profiles, Connections, Updates, Contacts and Status • Yahoo! Query Language (YQL) • Access (other) web services using a SQL-like language • Yahoo! Application Platform (YAP) • Developer hosted execution of applications with access to Yahoo's Social APIs and YQL; • Support for OpenSocial's JavaScript API; and • Support for server-side YML tags. • Future: run applications on Y! sites • OpenID, OAuth

  45. Contact • Peter Mika • pmika@yahoo-inc.com • Come to Barcelona and stop by • SearchMonkey • developer.yahoo.com/searchmonkey/ • mailing lists • searchmonkey-developers@yahoogroups.com • searchmonkey-siteowners@yahoogroups.com • forums • http://suggestions.yahoo.com/searchmonkey • http://suggestions.yahoo.com/datarss • Semantic Web FAQ • http://devel.yahoo.com/searchmonkey/smguide/faq.html

  46. the monkey is out!

More Related