Towards expert finding by leveraging relevant categories in authority ranking

Author(s):  
Hengshu Zhu ◽  
Huanhuan Cao ◽  
Hui Xiong ◽  
Enhong Chen ◽  
Jilei Tian
2019 ◽  
Vol 82 ◽  
pp. 1-16 ◽  
Author(s):  
Paolo Cifariello ◽  
Paolo Ferragina ◽  
Marco Ponza

Author(s):  
Rodrigo Gonçalves ◽  
Carina F. Dorneles

Expert finding is traditionally related to a subject of research in information retrieval and, often, is taken to mean "expertise retrieval within a specific organization". The task involves finding an expert in an expertise topic. Even though there are interesting proposals in the literature, they do not consider the context in which a given expertise is bound. This Ph.D. thesis introduces the concept of a framework that chronologically contextualizes search results in expert finding. Our motivation is to provide more accurate results of search processes related to finding experts in a given topic, contextualizing the expertise on professional/academic activities, an open research topic. In this paper, we present the main concepts of the framework we are developing and a general overview of its operation. At the moment, we are using the Lattes platform as a data source, for which we developed a process to extract expertise evidence, supported by the Crossref database.


2019 ◽  
Vol 13 (3) ◽  
pp. 1-20 ◽  
Author(s):  
Mahdi Dehghan ◽  
Ahmad Ali Abin
Keyword(s):  

Author(s):  
Sebastian Heil ◽  
Stefan Wild ◽  
Martin Gaedke
Keyword(s):  

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