Exploiting relational structure to understand publication patterns in high-energy physics

We analyze publication patterns in theoretical high-energy physics using a relational learning approach. We focus on four related areas: understanding and identifying patterns of citations, examining publication patterns at the author level, predicting whether a paper will be accepted by specific journals, and identifying research communities from the citation patterns and paper text. Each of these analyses contributes to an overall understanding of theoretical high-energy physics.

[1]  Charles Gide,et al.  Cours d'économie politique , 1911 .

[2]  Alfred J. Lotka,et al.  The frequency distribution of scientific productivity , 1926 .

[3]  Morroe Berger,et al.  Freedom and control in modern society , 1954 .

[4]  D. A. Bell,et al.  Applied Statistics , 1953, Nature.

[5]  P. Lazarsfeld,et al.  Friendship as Social process: a substantive and methodological analysis , 1964 .

[6]  Paul R. Thompson AUTHOR! , 1982, The Lancet.

[7]  M. Oppenheim Apprentice to Genius: The Making of a Scientific Dynasty , 1987 .

[8]  Ted E. Senator,et al.  Restructuring Databases for Knowledge Discovery by Consolidation and Link Formation , 1995, KDD.

[9]  Chanathip Namprempre,et al.  HyPursuit: a hierarchical network search engine that exploits content-link hypertext clustering , 1996, HYPERTEXT '96.

[10]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  M. KleinbergJon Authoritative sources in a hyperlinked environment , 1999 .

[12]  W. Scott Spangler,et al.  Clustering hypertext with applications to web searching , 2000, HYPERTEXT '00.

[13]  Chris H. Q. Ding,et al.  Automatic topic identification using webpage clustering , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[14]  Jennifer Neville,et al.  Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning , 2002, ICML.

[15]  Jennifer Neville,et al.  Avoiding Bias when Aggregating Relational Data with Degree Disparity , 2003, ICML.

[16]  Jennifer Neville,et al.  Learning relational probability trees , 2003, KDD '03.

[17]  David D. Jensen,et al.  Identifying Predictive Structures in Relational Data Using Multiple Instance Learning , 2003, ICML.