For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
19
views
Article has an altmetric score of 5
6
references
 Top references
cited by
0
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      216
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Homonym Detection in Curated Bibliographies: Learning from dblp's Experience (full version)

      Preprint
      Author(s): ,
      Publication date Created:

      Read this article at

      ScienceOpenArXiv
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Identifying (and fixing) homonymous and synonymous author profiles is one of the major tasks of curating personalized bibliographic metadata repositories like the dblp computer science bibliography. In this paper, we present and evaluate a machine learning approach to identify homonymous author bibliographies using a simple multilayer perceptron setup. We train our model on a novel gold-standard data set derived from the past years of active, manual curation at the dblp computer science bibliography.

          Related collections

          Most cited references6

          • Record: found
          • Abstract: found
          • Article: not found

          Comparison of the predicted and observed secondary structure of T4 phage lysozyme.

          B W Matthews (1975)
          Predictions of the secondary structure of T4 phage lysozyme, made by a number of investigators on the basis of the amino acid sequence, are compared with the structure of the protein determined experimentally by X-ray crystallography. Within the amino terminal half of the molecule the locations of helices predicted by a number of methods agree moderately well with the observed structure, however within the carboxyl half of the molecule the overall agreement is poor. For eleven different helix predictions, the coefficients giving the correlation between prediction and observation range from 0.14 to 0.42. The accuracy of the predictions for both beta-sheet regions and for turns are generally lower than for the helices, and in a number of instances the agreement between prediction and observation is no better than would be expected for a random selection of residues. The structural predictions for T4 phage lysozyme are much less successful than was the case for adenylate kinase (Schulz et al. (1974) Nature 250, 140-142). No one method of prediction is clearly superior to all others, and although empirical predictions based on larger numbers of known protein structure tend to be more accurate than those based on a limited sample, the improvement in accuracy is not dramatic, suggesting that the accuracy of current empirical predictive methods will not be substantially increased simply by the inclusion of more data from additional protein structure determinations.
          Article 0 comments Cited 703 times – based on 0 reviews     Review now
          Article has an altmetric score of 27
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            A brief survey of automatic methods for author name disambiguation

            Anderson A. Ferreira, Marcos Gonçalves, Alberto Laender (2012)
            Article 0 comments Cited 58 times – based on 0 reviews     Review now
            Article has an altmetric score of 7
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Data sets for author name disambiguation: an empirical analysis and a new resource

              Mark-Christoph Müller, Florian Reitz, Nicolas Roy (2017)
              Data sets of publication meta data with manually disambiguated author names play an important role in current author name disambiguation (AND) research. We review the most important data sets used so far, and compare their respective advantages and shortcomings. From the results of this review, we derive a set of general requirements to future AND data sets. These include both trivial requirements, like absence of errors and preservation of author order, and more substantial ones, like full disambiguation and adequate representation of publications with a small number of authors and highly variable author names. On the basis of these requirements, we create and make publicly available a new AND data set, SCAD-zbMATH. Both the quantitative analysis of this data set and the results of our initial AND experiments with a naive baseline algorithm show the SCAD-zbMATH data set to be considerably different from existing ones. We consider it a useful new resource that will challenge the state of the art in AND and benefit the AND research community.
              Article 0 comments Cited 17 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Publication date Created: 15 June 2018
                Article
                ArXiV ID: 1806.06017
                SO-VID: 87014923-df79-41c8-961c-b22793558031
                License:

                http://creativecommons.org/licenses/by/4.0/

                History
                Custom metadata
                Comments 13 pages, 5 figures, short paper version accepted at TPDL 2018
                Categories cs.DL cs.LG

                ScienceOpen disciplines: Information & Library science,Artificial intelligence
                Data availability:
                ScienceOpen disciplines: Information & Library science, Artificial intelligence

                Comments

                Comment on this article