Recommending Scientific Collaboration Based on Topical, Authors and Venues Similarities
作者： Abdulrhman M. Alshareef , Mohammed F. Alhamid , Abdulmotaleb El Saddik
关键词: Metadata 、 Common area 、 Anticipation (artificial intelligence) 、 Similarity (psychology) 、 Data science 、 Publishing 、 Semantics 、 Computer science 、 Scientific production
摘要: Scientific communities can be considered as a particular kind of practice communities. They consist various interdisciplinary groups that are often geographically distributed. A common area research interests bring them together. production growth has been increasing the difficulties for identifying most relevant article to cite or find an appropriate conference journal submit publication potential author collaborator with. In this paper, we propose algorithm analyzes manuscript along with cited articles determine suitable venue and Our exams topical similarity, authors' similarities, venues' similarities given query estimate collaborative confident score represents anticipation prospective relationship between researchers among scientific community. The effectiveness our approach is evaluated based on real academic dataset.
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