Semantic Web SIG: Make Machines Learn for Us

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  • Make Machines Learn for Us

    One advantage for being human is that we are able to learn. We gain even more advantage if we can make machines learn for us.  On this event, we are going to learn what machine learning is about from experts. Machine learning is being applied to optimize and automate many processes including search engine, online ad platform, customer intelligence, etc.  Hope you will get some ideas from the presentations that will help you implement machine learning in your applications.

    Evgeniy Gabrilovich from Yahoo Research will present "Machine learning in computational advertising: algorithms and applications": Online advertising is the primary economic force behind numerous Internet services ranging from major Web search engines to obscure forums. A new discipline - Computational Advertising - has recently emerged, which studies the process of advertising on the Internet from a variety of angles. A successful advertising campaign should be integral to the user experience and relevant to the users' information needs, as well as economically worthwhile to the advertiser and the publisher. This talk will survey the use of machine learning techniques in designing computational advertising systems. We demonstrate how to enrich query representation using Web search results, and thus use the Web as a repository of relevant query-specific knowledge. We also discuss the findings of our studies on when to advertise, as well as the insights we gained by studying how users interact with the ads.

    Ted Dunning, Ph.D. SENIOR ADVISOR, DEEPDYVE TECHNOLOGY

    Ted Dunning will talk about Mahout, the new open source tool for large scale machine learning. He will present a quick overview of the goals and major capabilities of Mahout in the brand new 0.4 release and then will drill down into the recently added classification framework that allows Mahout to be deployed in production settings for high volume training and classification tasks such as ad quality estimate, detailed offer targeting and fraud detection.

    Agenda:

    6:30pm - 7:00pm Registration / Networking / Refreshments / Pizza

    7:00pm - 7:10pm Introduction by AJ Chen (Moderator)

    7:10pm - 8:00pm Evgeniy Gabrilovich: Machine learning in computational advertising: algorithms and applications

    8:00pm - 8:50pm Ted Dunning: Mahout and new classification framework

    8:50pm - 9:00pm Joint Q&A.