2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA) (2016)
March 23, 2016 to March 25, 2016
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AINA.2016.61
Many authors can share the same name and this constitutes a serious problem that affects the relevancy of retrieval results and constitutes our motivation of finding such approach to cover this issue at the author names entity level. Solving such a problem may return with positive gain at the level of document retrieval, web search and the quality of data. This entity resolution task can be tackled as an unsupervised problem, where there are set of features that can be employed for the resolution job, or as supervised problem to compute the similarities among two citations and then classify if they are the same or not. Recent approaches usually utilize features such as: co-author, venue, topic similarity, affiliations and title of publications to deal with author ambiguity. In this paper, three attributes are used to treat this problem sequentially. The co-authorship firstly which is a well-known attribute, and then the topic and affiliation extracted from biographies, which can be found inside the publication, and this is our novelty frame in this paper.
Biographies, Data mining, Feature extraction, Libraries, History, Supervised learning, Classification algorithms
H. Hazimeh et al., "Leveraging Co-authorship and Biographical Information for Author Ambiguity Resolution in DBLP," 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), Crans-Montana, Switzerland, 2016, pp. 1080-1084.