Evaluation of Features for Author Name Disambiguation Using Linear Support Vector Machines

Dendek, Piotr Jan; Bolikowski, Łukasz; Łukasik, Michał

doi:10.1109/das.2012.36

Cited by 6 publications

(6 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The whole set of objects is divided into blocks so that entities are compared pairwise and possibly merged only within a block (cf. [17,18,19]). We have used different method, though.…”

Section: Discussionmentioning

confidence: 99%

Large Scale Citation Matching Using Apache Hadoop

Fedoryszak

Tkaczyk

Bolikowski

2013

Research and Advanced Technology for Digital Libraries

View full text Add to dashboard Cite

During the process of citation matching links from bibliography entries to referenced publications are created. Such links are indicators of topical similarity between linked texts, are used in assessing the impact of the referenced document and improve navigation in the user interfaces of digital libraries. In this paper we present a citation matching method and show how to scale it up to handle great amounts of data using appropriate indexing and a MapReduce paradigm in the Hadoop environment.

show abstract

“…The whole set of objects is divided into blocks so that entities are compared pairwise and possibly merged only within a block (cf. [17,18,19]). We have used different method, though.…”

Section: Discussionmentioning

confidence: 99%

Large Scale Citation Matching Using Apache Hadoop

Fedoryszak

Tkaczyk

Bolikowski

2013

Research and Advanced Technology for Digital Libraries

View full text Add to dashboard Cite

show abstract

“…In our implementation, two authors are compared with each other if their names have a Jaro-Winkler similarity of at least 0.9 following Donner (2014) and Hajra, Radevski, and Tochtermann (2015). Concerning the rules for the author name disambiguation, we use factors that have already proven to be reliable in the literature and which are rated according to their importance (Caron & van Eck, 2014;Cen, Dragut, Si, & Ouzzani, 2013;Dendek, Bolikowski, & Lukasik, 2012;Protasiewicz & Dadas, 2016).…”

Section: Author Name Disambiguationmentioning

confidence: 99%

The data set knowledge graph: Creating a linked open data source for data sets

Färber

Lamprecht

2021

Quantitative Science Studies

View full text Add to dashboard Cite

Several scholarly knowledge graphs have been proposed to model and analyze the academic landscape. However, although the number of data sets has increased remarkably in recent years, these knowledge graphs do not primarily focus on data sets but rather associated entities such as publications. Moreover, publicly available data set knowledge graphs do not systematically contain links to the publications in which the data sets are mentioned. In this paper, we present an approach for constructing an RDF knowledge graph that fulfills these mentioned criteria. Our data set knowledge graph, DSKG, is publicly available at http://dskg.org and contains metadata of data sets for all scientific disciplines. To ensure high data quality of the DSKG, we first identify suitable raw data set collections for creating the DSKG. We then establish links between the data sets and publications modeled in the Microsoft Academic Knowledge Graph that mention these data sets. As the author names of data sets can be ambiguous, we develop and evaluate a method for author name disambiguation and enrich the knowledge graph with links to ORCID. Overall, our knowledge graph contains more than 2,000 data sets with associated properties, as well as 814,000 links to 635,000 scientific publications. It can be used for a variety of scenarios, facilitating advanced data set search systems and new ways of measuring and awarding the provisioning of data sets.

show abstract

“…Section 2 describes both the SYNAT project and the YADDA2 architecture. Section 3 presents the Author Disambiguation Framework (ADF) developed for purposes of YADDA2 [32] and the results of further examination [33]. Section 4 shows adaptation of the ADF to SYNAT platform with an emphasis on its presentation layer -the Query Framework (QF).…”

Section: Author Disambiguationmentioning

confidence: 99%

“…In our previous papers [32,33] we have established the vocabulary for ADF description, which, after further adjustments, can be described as follows. A contributor entity reflects the fact that a person was a co-author of a document.…”

Section: Vocabularymentioning

confidence: 99%

Author Disambiguation in the YADDA2 Software Platform

Dendek

Wojewódzki

Bolikowski

2013

Intelligent Tools for Building a Scientific Information Platform

Self Cite

View full text Add to dashboard Cite

SYNAT platform powered by the YADDA2 architecture has been extended with the Author Disambiguation Framework and the Query Framework. The former framework clusters occurrences of contributor names into identities of authors, the latter answers queries about authors and documents written by them. This paper presents an outline of the disambiguation algorithms, implementation of the query framework, integration into the platform and performance evaluation of the solution. 1. Data preparation, covering a parsing and a standardization procedures. [7-11] 2. Attribute matching techniques, as approximate string matching, token based and phonetic based. [12-15]

show abstract

Evaluation of Features for Author Name Disambiguation Using Linear Support Vector Machines

Cited by 6 publications

References 6 publications

Large Scale Citation Matching Using Apache Hadoop

Large Scale Citation Matching Using Apache Hadoop

The data set knowledge graph: Creating a linked open data source for data sets

Author Disambiguation in the YADDA2 Software Platform

Contact Info

Product

Resources

About