On November 3, 2010 Palo Alto at Cubberley Community Center, SDForumâ€™s Semantic Web SIG hosted â€œMake Machines Learn for Us.â€ Ted Dunning of MapR Technologies and Evgeniy Gabrilovich of Yahoo Research. The dramatic increase in computer network speed and capacity in the cloud create new strategies for machine learning.
Ted Dunning talked about Mahout, the new open source tool for large-scale machine learning. The new 0.4 release has a new classification framework that can be deployed in production settings for high volume training and classification tasks such as ad quality estimates, detailed offer targeting and fraud detection. Mahout provides early production quality scalable data mining. New classification systems like Sequential Gradient Descent (SGD) and training APIs allow industrial scale classification.
Evgeniy Gabrilovich from Yahoo Research presented “Machine learning in computational advertising: algorithms and applications.” Most Internet services make money from advertising determined by the growing field of â€œcomputational advertisingâ€ that studies all the various elements of an ad. Gabrilovich explained how machine-learning techniques design evaluation strategies. Web search results enrich query representation and then use the Web as a repository of relevant query-specific knowledge. The results are then used to understand which ads work for particular users.
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