Title :
Cluster Labeling for the Blogosphere
Author :
Hennig, Patrick ; Berger, Philipp ; Meinel, Christoph ; Steuer, Claus ; Wuerz, Christian
Author_Institution :
Hasso-Plattner-Inst., Univ. of Potsdam, Potsdam, Germany
Abstract :
Hierarchical Cluster Labeling helps users to quickly understand and analyze hierarchical clusters. This may be used to enhance search engine results or interactive browsing like it is being used in the Blog Intelligence application. The hierarchical organization of data helps to represent different levels of detail. Hierarchical clustering may be quite common, but there are few good solutions for labeling those clusters. We decided to lay the focus of this work on labeling binary hierarchical clusters. Current approaches focus either on statistical features of the clustered documents or external sources like Wikipedia. We combined those ideas to profit from both advantages and created an algorithm, that can handle clustered documents as well as terms.
Keywords :
Web sites; pattern clustering; search engines; statistical analysis; Blog Intelligence; Blogosphere; Wikipedia; clustered documents; hierarchical cluster labeling; hierarchical organization; search engine; statistical features; Blogs; Clustering algorithms; Electronic publishing; Encyclopedias; Internet; Labeling; Blogosphere; Cluster Labeling; Clustering; Social Network; Text Mining;
Conference_Titel :
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location :
Sydney, NSW
DOI :
10.1109/BDCloud.2014.68