Research talk 1 - Expert Search by Andreas Henrich

Rui Meng

Andreas Henrich is a professor at University of Bamberg. In this talk, he mainly introduced an important application of Information Retrieval in industry - Expert Search. Different from other general academic talks, he didn’t talk too much about some novel scientific ideas. Instead, he reviewed many mature techniques in expert search and emphasized the content of how to implement a real system.

Expert Search by Andreas Henrich, lecture at ASIRF 2016

Expert Search by Andreas Henrich, lecture at ASIRF 2016

The primary models used in expert search include:

  • Candidate Generation Model: like language model, score of expert is estimated by the query and his/her documents. But this method may fail due to the little query information.
  • Topic Generation Model: improve the CGM by introducing prior knowledge and avoiding query-based generation.
  • Voting Model: the ranking of documents with respect to query can be treated as a voting for candidate experts.
  • Other models like graph-based model, measuring experts’ influence based on their centrality in the network.

Unlike general document retrieval, entity retrieval primarily concerns the problem of finding the relevant items, in which the expert retrieval is a representative. However it’s still a difficult problem regarding how to represent an entity.