A quartet method based on variable neighborhood search for biomedical literature extraction and clustering

[1]  Jia Zeng,et al.  Enhancing MEDLINE document clustering by incorporating MeSH semantic similarity , 2009, Bioinform..

[2]  Paul M. B. Vitányi,et al.  Clustering by compression , 2003, IEEE Transactions on Information Theory.

[3]  Xiaohua Hu,et al.  A comprehensive comparison study of document clustering for a biomedical digital library MEDLINE , 2006, Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '06).

[4]  Zhiyong Lu,et al.  PubMed and beyond: a survey of web tools for searching biomedical literature , 2011, Database J. Biol. Databases Curation.

[5]  Lior Pachter,et al.  Why Neighbor-Joining Works , 2006, Algorithmica.

[6]  G. Furnas.  The generation of random, binary unordered trees , 1984 .

[7]  Y Yang,et al.  An analysis of statistical term strength and its use in the indexing and retrieval of molecular biology texts , 1996, Comput. Biol. Medicine.

[8]  Kevin W. Boyack,et al.  Clustering More than Two Million Biomedical Publications: Comparing the Accuracies of Nine Text-Based Similarity Approaches , 2011, PloS one.

[9]  Pierre Hansen,et al.  Variable Neighborhood Search , 2018, Handbook of Heuristics.

[10]  Jan H. M. Korst,et al.  Heuristic Approaches for the Quartet Method of Hierarchical Clustering , 2010, IEEE Transactions on Knowledge and Data Engineering.

[11]  Manuel Cebrián,et al.  Reducing the Loss of Information through Annealing Text Distortion , 2011, IEEE Transactions on Knowledge and Data Engineering.

[12]  Lefteris Angelis,et al.  PuReD-MCL: a graph-based PubMed document clustering methodology , 2008, Bioinform..

[13]  Marco Turchi,et al.  Robustness Issues in Text Mining , 2012, SMPS.

[14]  Hong Cheng,et al.  Graph Clustering Based on Structural/Attribute Similarities , 2009, Proc. VLDB Endow..

[15]  Ronald de Wolf,et al.  Algorithmic Clustering of Music Based on String Compression , 2004, Computer Music Journal.

[16]  James E Andrews,et al.  An author co-citation analysis of medical informatics. , 2003, Journal of the Medical Library Association : JMLA.

[17]  Jens Lagergren,et al.  Fast neighbor joining , 2009, Theor. Comput. Sci..

[18]  V. de Boer,et al.  Instance Classification using Co-Occurrences on the Web , 2006 .

[19]  Paul M. B. Vitányi,et al.  The Google Similarity Distance , 2004, IEEE Transactions on Knowledge and Data Engineering.

[20]  Shlomo Moran,et al.  Optimal implementations of UPGMA and other common clustering algorithms , 2007, Inf. Process. Lett..

[21]  Janez Demsar,et al.  Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..

[22]  M. Friedman.  A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings , 1940 .

[23]  Zhiyong Lu,et al.  Improving accuracy for identifying related PubMed queries by an integrated approach , 2009, J. Biomed. Informatics.

[24]  George Karypis,et al.  A Comparison of Document Clustering Techniques , 2000 .

[25]  Sophia Ananiadou,et al.  Text mining and its potential applications in systems biology. , 2006, Trends in biotechnology.

[26]  Paul M. B. Vitányi,et al.  Author ' s personal copy A Fast Quartet tree heuristic for hierarchical clustering , 2010 .

[27]  Bettina Berendt,et al.  Intelligent Bibliography Creation and Markup for Authors: A Step Towards Interoperable Digital Libraries , 2006, ECDL.

[28]  C. Lee Giles,et al.  CiteSeer: an autonomous Web agent for automatic retrieval and identification of interesting publications , 1998, AGENTS '98.

[29]  Bernard De Baets,et al.  UPGMA clustering revisited: A weight-driven approach to transitive approximation , 2006, Int. J. Approx. Reason..

[30]  Mirjana Cangalovic,et al.  Solving spread spectrum radar polyphase code design problem by tabu search and variable neighbourhood search , 2003, Eur. J. Oper. Res..

[31]  Diego Reforgiato Recupero,et al.  A new unsupervised method for document clustering by using WordNet lexical and conceptual relations , 2007, Information Retrieval.