Results 151 to 160 of about 2,936,085 (211)
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Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018AMiner 1 is a free online academic search and mining system, having collected more than 130,000,000 researcher profiles and over 200,000,000 papers from multiple publication databases [25].
Yutao Zhang +3 more
semanticscholar +2 more sources
Online author name disambiguation in evolving digital library
Neurocomputing, 2022Joydeep Chandra, Samrat Mondal
exaly +2 more sources
Cost-effective on-demand associative author name disambiguation
Information Processing and Management, 2012 Authorship disambiguation is an urgent issue that affects the quality of digital library ser-vices and for which supervised solutions have been proposed, delivering state-of-the-art effectiveness.
Alberto Laender +2 more
exaly +5 more sources
On Graph-Based Name Disambiguation
Journal of Data and Information Quality, 2011Name ambiguity stems from the fact that many people or objects share identical names in the real world. Such name ambiguity decreases the performance of document retrieval, Web search, information integration, and may cause confusion in other applications.
Jianyong Wang, Lizhu Zhou
exaly +2 more sources
ACM Transactions on Knowledge Discovery from Data, 2022
Name ambiguity is a prevalent problem in scholarly publications due to the unprecedented growth of digital libraries and number of researchers. An author is identified by their name in the absence of a unique identifier.
K. Pooja, S. Mondal, Joydeep Chandra
semanticscholar +1 more source
Name ambiguity is a prevalent problem in scholarly publications due to the unprecedented growth of digital libraries and number of researchers. An author is identified by their name in the absence of a unique identifier.
K. Pooja, S. Mondal, Joydeep Chandra
semanticscholar +1 more source
Author Name Disambiguation in Citations
2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2011Members of the academic community have increasingly turned to digital libraries to search for the latest work of their peers. On account of their role in the academic community, it is very important that these digital libraries collect citations in a consistent, accurate, and up-to-date manner, yet they do not correctly compile citations for myriads of
Kai-Hsiang Yang, Yi Hsuan Wu
openaire +1 more source
LAGOS‐AND: A large gold standard dataset for scholarly author name disambiguation
J. Assoc. Inf. Sci. Technol., 2021In this article, we present a method to automatically build large labeled datasets for the author ambiguity problem in the academic world by leveraging the authoritative academic resources, ORCID and DOI.
Li Zhang, Wei Lu, Jinqing Yang
semanticscholar +1 more source
A unified framework for name disambiguation
Proceedings of the 17th international conference on World Wide Web, 2008Name ambiguity problem has been a challenging issue for a long history. In this paper, we intend to make a thorough investigation of the whole problem. Specifically, we formalize the name disambiguation problem in a unified framework. The framework can incorporate both attribute and relationship into a probabilistic model. We explore a dynamic approach
Jie Tang 0001 +3 more
openaire +2 more sources
Person name disambiguation by bootstrapping
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, 2010In this paper, we report our system that disambiguates person names in Web search results. The system uses named entities, compound key words, and URLs as features for document similarity calculation, which typically show high precision but low recall clustering results. We propose to use a two-stage clustering algorithm by bootstrapping to improve the
Minoru Yoshida +4 more
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Location-Aware Named Entity Disambiguation
Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021Named Entity Disambiguation (NED) and linking has been traditionally evaluated on natural language content that is both well-written and contextually rich. However, many NED approaches display poor performance on text sources that are short and noisy.
Maithrreye Srinivasan, Davood Rafiei
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