Please use this identifier to cite or link to this item: https://doi.org/10.1145/1835449.1835453
Title: Prototype hierarchy based clustering for the categorization and navigation of web collections
Authors: Ming, Z.-Y. 
Wang, K. 
Chua, T.-S. 
Keywords: Criterion function
Hierarchical clustering
Hierarchy induction
Prototype hierarchy
Issue Date: 2010
Source: Ming, Z.-Y.,Wang, K.,Chua, T.-S. (2010). Prototype hierarchy based clustering for the categorization and navigation of web collections. SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval : 2-9. ScholarBank@NUS Repository. https://doi.org/10.1145/1835449.1835453
Abstract: This paper presents a novel prototype hierarchy based clustering (PHC) framework for the organization of web collections. It solves simultaneously the problem of categorizing web collections and interpreting the clustering results for navigation. By utilizing prototype hierarchies and the underlying topic structures of the collections, PHC is modeled as a multi-criterion optimization problem based on minimizing the hierarchy evolution, maximizing category cohesiveness and inter-hierarchy structural and semantic resemblance. The flexible design of metrics enables PHC to be a general framework for applications in various domains. In the experiments on categorizing 4 collections of distinct domains, PHC achieves 30% improvement in μF 1 over the state-of-the-art techniques. Further experiments provide insights on performance variations with abstract and concrete domains, completeness of the prototype hierarchy, and effects of different combinations of optimization criteria. © 2010 ACM.
Source Title: SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
URI: http://scholarbank.nus.edu.sg/handle/10635/41921
ISBN: 9781605588964
DOI: 10.1145/1835449.1835453
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