Ming Han Teh

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Traditional information retrieval systems have limited functionality. For instance, they are not able to adequately support queries containing non-textual fragments such as images or videos, queries that are very long or ambiguous, or semantically-rich queries over non-textual corpora. In this paper, we present DataSift, an expressive and accurate(More)
Traditional search engines are unable to support a large number of potential queries issued by users, for instance, queries containing non-textual fragments such as images or videos, queries that are very long, ambiguous, or those that require subjective judgment, or semantically-rich queries over non-textual corpora. We demonstrate DataSift, a(More)
Introduction Social coding tools such as GitHub [1] have transformed the way software gets developed collaboratively and openly on the World Wide Web. GitHub has various avenues and features for collaborative development, but perhaps the most fundamental feature that allows non-listed collaborators to contribute to a repository is a pull request. A pull(More)
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