Sunday, June 29, 2014

JWS ranked highly in the 2014 Google Scholar Metrics data

Google has released its 2014 Google Scholar Metrics data, which estimated the visibility and influence of journals and selected conferences based on citations to articles published in 2009-2013 and indexed in Google Scholar as of mid-June 2013. The primary measure is a publication venue's h5-index, a variation on the popular h-index. Google defines a venue's h5-index as the largest number h such that h articles published in the last five years have at least h citations each. A related measure, h5-median is also computed for a venue as the median number of citations for the articles that make up its h5-index.

Journal of Web Semantics 2014 h5-index was 36 and its h5-median was 62. This puts the JWS among the top venues for the Google-defined category Databases and Information Systems as well as among the top venues whose names contain one of the words web, semantics, knowledge, intelligence or intelligent.

Here are the 36 articles that make up the JWS's h5-index for 2014.

Friday, June 20, 2014

JWS preprint: Identifying Relevant Concept Attributes to Support Mapping Maintenance under Ontology Evolution

Duy Dinh, Julio Cesar Dos Reis, Cédric Pruskia, Marcos Da Silveiraa and Chantal Reynaud-Delaître, Identifying Relevant Concept Attributes to Support Mapping Maintenance under Ontology Evolution, Web Semantics: Science, Services and Agents on the World Wide Web, to appear, 2014.

Abstract: The success of distributed and semantic-enabled systems relies on the use of up-to-date ontologies and mappings between them. However, the size, quantity and dynamics of existing ontologies demand a huge maintenance effort pushing towards the development of automatic tools supporting this laborious task. This article proposes a novel method, investigating different types of similarity measures, to identify concepts' attributes that served to define existing mappings. The obtained experimental results reveal that our proposed method allows one to identify the relevant attributes for supporting mapping maintenance, since we found correlations between ontology changes affecting the identified attributes and mapping changes.

Friday, June 6, 2014

CFP: Special issue on machine learning and data mining for the Semantic Web

The Journal of Web Semantics seeks submissions of original research papers for a special issue on machine learning and data mining for the Semantic Web dealing with analytical, theoretical, empirical, and practical aspects of machine learning and data mining for all areas of the Semantic Web. Submissions are due by February 15, 2015December 15, 2014.

In the last years, machine learning, as well as data mining approaches have become the main focus of many research works and initiatives related to the Semantic Web and the Web of Data. Challenges imposed by the large scale of Web Data, the uncertainty related to contradictory and incomplete information, and also, by properties and characteristics of Linked Data represent an interesting domain for emerging machine learning and data mining approaches.

For this special issue, we invite high quality contributions from all areas of research that address any aspects of the aforementioned challenges. Topics of interest include but are not limited to the following.
  • Ontology-based data mining
  • Automatic (and semi-automatic) ontology learning and population
  • Distant-supervision (or weak-supervision) methods based on ontologies and knowledge bases
  • Web mining using semantic information
  • Meta-learning for the Semantic Web
  • Cognitive-inspired approaches and exploratory search in the Semantic Web
  • Discovery science involving linked data and ontologies
  • Data mining and machine learning applied to information extraction in the semantic web
  • Big Data analytics involving linked data
  • Inductive reasoning on uncertain knowledge for the Semantic Web
  • Ontology matching and instance matching using machine learning and data mining
  • Data mining and knowledge discovery in the Web of data
  • Knowledge base maintenance using Machine Learning and Data Mining
  • Crowdsourcing and the Semantic Web
  • Mining the social Semantic Web
We solicit contributions that address these challenges, as well as reports on novel applications with the potential to push Semantic Web and machine learning/data mining cooperation forward.

Submission guidelines

The Journal of Web Semantics solicits original scientific contributions of high quality. Following the overall mission of the journal, we emphasize the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services.

Submission of your manuscript is welcome provided that it, or any translation of it, has not been copyrighted or published and is not being submitted for publication elsewhere. Upon acceptance of an article, the author(s) will be asked to transfer copyright of the article to the publisher. This transfer will ensure the widest possible dissemination of information. Manuscripts should be prepared for publication in accordance with instructions given in the JWS guide for authors. The submission and review process will be carried out using Elsevier's Web-based EES system. Final decisions of accepted papers will be approved by an editor in chief.

Final review copies of accepted publications will appear in print and at the archival online server. Author preprints of the articles will be made freely accessible on the JWS preprint server.

Important Dates

  • Call for papers: June 2014
  • Submission deadline: 15 February 2015 15 December 2014
  • Author notification: 30 April 2015
  • Submission deadline for revisions: 15 June 2015
  • Author notification: 1 August 2015

Special issue editors