The Microsoft Academic Search challenges at KDD Cup 2013

Martine De Cock, Senjuti Basu Roy, Swapna Savvana, Vani Mandava, Brian Dalessandro, Claudia Perlich, William Cukierski, Ben Hamner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Microsoft Academic Search is a free search engine specific to scholarly material. It currently covers more than 50 million publications and over 19 million authors across a variety of domains. One of the main challenges in correctly indexing this material is author name ambiguity and the resulting noise in author profiles. KDD Cup 2013 invited participants to tackle this problem in 2 ways: (1) by automatically determining which papers in an author profile are truly written by a given author, and (2) by identifying which author profiles need to be merged because they belong to the same author. This paper presents a brief account of the contest and the lessons learned.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE International Conference on Big Data, Big Data 2013
Pages1-4
Number of pages4
DOIs
StatePublished - Dec 1 2013
Externally publishedYes
Event2013 IEEE International Conference on Big Data, Big Data 2013 - Santa Clara, CA, United States
Duration: Oct 6 2013Oct 9 2013

Publication series

NameProceedings - 2013 IEEE International Conference on Big Data, Big Data 2013

Other

Other2013 IEEE International Conference on Big Data, Big Data 2013
CountryUnited States
CitySanta Clara, CA
Period10/6/1310/9/13

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • Microsoft Academic Search
  • author name disambiguation

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