PUBLICATIONS' CLASSIFICATION ANALYSIS USING CONCEPT LATTICES

The definitive classification of scientific journals depends on their aims and scopes details. In this paper, we present an approach to facilitate the journals classification of the DBLP datasets. For the analysis, the DBLP data sets were preprocessed by assigning each journal attributes defined by its topics and then the theory of formal concept analysis is introduced. It is subsequently shown how this theory can be applied to analyze the relations between journals and the extracted topics from their aims and scopes. The result is a concept lattice that contains information on journal-topic relational context depending on how they are associated. It is shown how this approach can be used to facilitate the classifications of scientific journals.

[1]  Bernhard Ganter,et al.  Scale Coarsening as Feature Selection , 2008, ICFCA.

[2]  Bernhard Ganter,et al.  Formal Concept Analysis: Mathematical Foundations , 1998 .

[3]  Qingyuan Yue,et al.  Accounting Information Sharing in Government Management , 2010, 2010 International Conference on Multimedia Technology.

[4]  Mondher Maddouri.  A Formal Concept Analysis Approach to Discover Association Rules from Data , 2005, CLA.

[5]  Ghassan Beydoun,et al.  Evolving semantic web with social navigation , 2007, Expert Syst. Appl..

[6]  Rudolf Wille,et al.  Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts , 2009, ICFCA.

[7]  Zhengxin Chen,et al.  Recent trends in Data Mining (DM): Document Clustering of DM Publications , 2006, 2006 International Conference on Service Systems and Service Management.

[8]  N. J. Davies,et al.  Concept Lattices for Knowledge Management , 1999 .

[9]  Gerd Stumme,et al.  Computing iceberg concept lattices with T , 2002, Data Knowl. Eng..

[10]  Chris H. Q. Ding,et al.  Knowledge transformation from word space to document space , 2008, SIGIR '08.

[11]  Yizhou Sun,et al.  RankClus: integrating clustering with ranking for heterogeneous information network analysis , 2009, EDBT '09.

[12]  Jimeng Sun,et al.  Beyond streams and graphs: dynamic tensor analysis , 2006, KDD '06.

[13]  Ghassan Beydoun.  Using Formal Concept Analysis towards Cooperative E-Learning , 2008, PKAW.

[14]  Gerd Stumme,et al.  Conceptual Knowledge Discovery in Databases Using Formal Concept Analysis Methods , 1998, PKDD.

[15]  Uta Priss.  Formal concept analysis in information science , 2006 .

[16]  Ralf Klamma,et al.  You Never Walk Alone: Recommending Academic Events Based on Social Network Analysis , 2009, Complex.

[17]  Randy Goebel,et al.  DBconnect: mining research community on DBLP data , 2007, WebKDD/SNA-KDD '07.

[18]  Michael Ley,et al.  The DBLP Computer Science Bibliography: Evolution, Research Issues, Perspectives , 2002, SPIRE.