Automatic Topic Identification Using Webpage Clustering

Authors:
Xiaofeng He;Chris H. Q. Ding;Hongyuan Zha;Horst D. Simon
Affiliations:
-;-;-;-
Venue:
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Year:
2001

Citing 0
Cited 17

Learning implicit user interest hierarchy for context in personalization

Proceedings of the 8th international conference on Intelligent user interfaces
Iteratively clustering web images based on link and attribute reinforcements

Proceedings of the 13th annual ACM international conference on Multimedia
A Visual Framework for Knowledge Discovery on the Web: An Empirical Study of Business Intelligence Exploration

Journal of Management Information Systems
Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis

Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic structure mining using temporal co-occurrence

Proceedings of the 2nd international conference on Ubiquitous information management and communication
Architecture of an Hybrid System for Experimentation on Web Information Retrieval Incorporating Clustering Techniques

KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Hybrid clustering for validation and improvement of subject-classification schemes

Information Processing and Management: an International Journal
A fast tree-based search algorithm for cluster search engine

SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Semantic analysis and classification method for customer enquiries in telecommunication services

Engineering Applications of Artificial Intelligence
Generalized Adjusted Rand Indices for cluster ensembles

Pattern Recognition
Topic structure mining for document sets using graph-based analysis

DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
Topic structure mining using pagerank without hyperlinks

ICADL'06 Proceedings of the 9th international conference on Asian Digital Libraries: achievements, Challenges and Opportunities
Topic mining based on graph local clustering

MICAI'11 Proceedings of the 10th international conference on Artificial Intelligence: advances in Soft Computing - Volume Part II
Towards a formal concept analysis approach to exploring communities on the world wide web

ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
Capturing market intelligence from customer feedback e-mails using self-enhancing bolzmann machine-based network of knowledge maps

ICDCIT'05 Proceedings of the Second international conference on Distributed Computing and Internet Technology
Summary extraction from chinese text for data archives of online news

DNIS'11 Proceedings of the 7th international conference on Databases in Networked Information Systems
Post-retrieval search hit clustering to improve information retrieval effectiveness: Two digital forensics case studies

Decision Support Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Grouping webpage into distinct topics is one way to organize the large amount of retrieved information on the web. In this paper, we report that based on similaritymetric which incorporates textual information, hyperlinkstructure and co-citation relations, an unsupervised clustering method can automatically and effectively identify relevant topics, a shown in experiments on several retrieved sets of webpages. The clustering method is a state-of-art spectral graph partitioning method based on normalized cutcriterion first developed for image segmentation.