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Aardvark

Aardvark. Anatomy of a Large-Scale Social Search Engine. The Library vs. The Village. The Library Keywords are used to search Knowledge base comes from a small number of publishers Content is created before the question is asked Trust is based on Authority

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Aardvark

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  1. Aardvark Anatomy of a Large-Scale Social Search Engine

  2. The Library vs. The Village • The Library • Keywords are used to search • Knowledge base comes from a small number of publishers • Content is created before the question is asked • Trust is based on Authority • Traditional search engines (e.g. Google) • The Village • Questions are phrased in natural language • Answers are generated in real time • Anyone in the community might answer • Trust is based on intimacy

  3. Purpose • Harness the power of the village to answer questions not easily answered with traditional search engines. • Works best for subjective questions • “What is a good Italian restaurant in the north end of Boston with live entertainment on Fridays? • Utilize the power of mobile devices to provide quick answers from knowledgeable users.

  4. Aardvark Components • Crawler / Indexer • Finds and labels resources • Users, not documents • Query Analyzer • Classifies queries • Filters out non-questions, trivial questions, inappropriate questions • Determines if the query is specific to a location • Determines the topic • Uses natural language processing to find salient phrases and determine what is semantically significant. • Uses a taxonomy of popular topics • Ranking Function • Ranks resources (users) to determine which provide the best information on a topic • UI • Web, IM, Mobile devices

  5. Aardvark Architecture

  6. User Experience • Approached directly, via IM or Mobile Application to answer a specific question they should know something about. • Answerers are found within the users social network • Interaction is real-time • One on One conversation

  7. Ranking • Similar to traditional ranking in concept, a statistical probability that the user can answer a question on a topic is computed. • Also takes into account the “connectedness” of the users. • Asks for feedback as to the quality of the question after it is answered.

  8. Does it work? • 87.7% of questions received an answer • 57.2% answered in less than 10 minutes • 70.4% of answers were ranked “good” • In my experience, works great for: • Idea generator • Getting pointed in the right direction • Getting opinions on subjective topics

  9. References • “Anatomy of a Large-Scale Social Search Engine” by Damon Horowitz and Sepandar Kumar • http://vark.com/aardvarkFinalWWW2010.pdf • Try it yourself – www.vark.com

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