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  1. Topic Regression

    ... considers the opposite problem: predicting the textual content of documents based on non-text data. In this work I study several ... influence of specific metadata elements in determining the content of text documents. Such topic regression methods allow users of ...

  2. Shaw, Kerry

    ... Among other responsibilities, she oversees the content and design of the College's website and print publications, coordinates ... UMass Amherst Information Technology, and held marketing and content strategy roles at Penguin Group USA and OgilvyOne. Kerry received ...

  3. Lan, Andrew

    ... collecting and analyzing massive and multi-modal learner and content data. This massive and multi-modal learner and content data can be collected in both traditional classrooms and online ...

  4. Handling the Facebook Avalanche

    ... piece of hardware. Moreover, annotating user-contributed content as from "a friend of a friend" offers many more opportunities to de-anonymize content than using only the first-degree friend network.  We'll talk about ...

  5. Inference in Networking Systems with Designed Measurements

    ... our daily communication, delivering huge amount of content and large number of services, and providing large scale distributed ... aspects. In the context of mapping users to servers in content delivery networks, we show that letting user select a server that ...

  6. CICS Social Media Ambassador

    ... college create and curate fun, engaging, student-centered content for CICS Twitter, Facebook, and Instagram channels. Undergraduate ... of the CICS Director of External Relations, develop content for CICS branded social media channels Facebook, Instagram, and Twitter ...

  7. Spring 14 Course Descriptions

    ... operating system. Topics will include: producing dynamic content using a server-based language, content serving databases and XML documents, session state management, ...

  8. Visual Analysis of Verbatim Text Transcripts

    ... are characterized by an incremental development of their content structure. In contrast to highly-edited text data (e.g., literary, ... I will argue for the importance of tuning automatic content analysis models to unique textual characteristics, appearing, for ...

  9. Machine Learning for Human Learning

    ... analysis of the estimation error in learner and content parameters; this error analysis is more accurate than common asymptotic ... methods for educational applications including learning and content analytics, personalized learning action selection, automated grading ...

  10. Discovering and Using Implicit Data for Information Retrieval

    ... and thus have human-generated succinctdescriptions of their content (anchor text) associated with them. This indirectly available ... language modeling based techniques to effectively use content similarity among data for our work. Using the four different search ...

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