Incorporating multi-kernel function and Internet verification for Chinese person name disambiguation

The study on person name disambiguation aims to identify different entities with the same person name through document linking to different entities. The traditional disambiguation approach makes use of words in documents as features to distinguish different entities. Due to the lack of use of word order as a feature and the limited use of external knowledge, the traditional approach has performance limitations. This paper presents an approach for named entity disambiguation through entity linking based on a multi- kernel function and Internet verification to improve Chinese person name disambiguation. The proposed approach extends a linear kernel that uses in-document word features by adding a string kernel to construct a multi-kernel function. This multi-kernel can then calculate the similarities between an input document and the entity descriptions in a named per- son knowledge base to form a ranked list of candidates to different entities. Furthermore, Internet search results based on keywords extracted from the input document and entity descriptions in the knowledge base are used to train classifiers for verification. The evaluations on CIPS-SIGHAN 2012 person name disambiguation bakeoff dataset show that the use of word orders and Internet knowledge through a multi-kernel function can improve both precision and recall and our system has achieved state-of-the-art performance.

AMiner:Search and Mining of Academic Social Networks

AMiner is a novel online academic search and mining system,and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors,papers,conferences,journals and organizations.The system is subsequently able to extract researchers’profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation.Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise search.In addition,AMiner offers a set of researcher-centered functions,including social influence analysis,relationship mining,collaboration recommendation,similarity analysis and community evolution.The system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions.