Global ETD Search

Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

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Showing 1 to 4 of 4 for “"Expert Finding"”.

  1. Hefbib : hierarchical expert finding in heterogeneous bibliographic network

    Expert finding systems allow users to type simple text queries and retrieve names of individuals who possess the expertise described in the queries. Such applications are especially useful in real world: conference orga- nizers may search for reviewers, company recruiters may search for talented …

    uiuc Repository record for Hefbib : hierarchical expert finding in heterogeneous bibliographic network (opens in a new tab)

  2. Inferring Degree Of Localization Of Twitter Persons And Topics Through Time, Language, And Location Features

    … can aid content recommendation systems and local expert finding. This thesis addresses this important problem using Twitter data.</p><p>A geo-influencer is identified via the locations of its followers. On Twitter, due to privacy reasons, the location reported by followers is limited to profile …

    syracuse-diss Repository record for Inferring Degree Of Localization Of Twitter Persons And Topics Through Time, Language, And Location Features (opens in a new tab)

  3. Inferring Degree of Localization of Twitter Persons and Topics Through Time, Language, and Location Features

    … can aid content recommendation systems and local expert finding. This thesis addresses this important problem using Twitter data.</p><p>A geo-influencer is identified via the locations of its followers. On Twitter, due to privacy reasons, the location reported by followers is limited to profile …

    syracuse-diss Repository record for Inferring Degree of Localization of Twitter Persons and Topics Through Time, Language, and Location Features (opens in a new tab)

  4. Low-rank estimation and embedding learning: theory and applications

    … tasks. In the second application, the task of expert finding is studied, which is to rank candidates with appropriate expertise based on a given query. To capture the subtle semantic information regarding specific queries with narrow semantic meanings, locally-trained embedding learning with …

    uiuc Repository record for Low-rank estimation and embedding learning: theory and applications (opens in a new tab)