Algorithms for clustering data
Algorithms for clustering data
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
On the merits of building categorization systems by supervised clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Hierarchical neural networks for text categorization (poster abstract)
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Hierarchical classification of Web content
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Knowledge management and data mining for marketing
Decision Support Systems - Knowledge management support of decision making
Text classification in a hierarchical mixture model for small training sets
Proceedings of the tenth international conference on Information and knowledge management
Strategies for minimising errors in hierarchical web categorisation
Proceedings of the eleventh international conference on Information and knowledge management
Exploiting Hierarchy in Text Categorization
Information Retrieval
Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Improving Text Classification by Shrinkage in a Hierarchy of Classes
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Hierarchical Text Classification and Evaluation
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Building Hierarchical Classifiers Using Class Proximity
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
The VLDB Journal — The International Journal on Very Large Data Bases
Introduction to topic detection and tracking
Topic detection and tracking
A scalability analysis of classifiers in text categorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Large margin hierarchical classification
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Hierarchical document categorization with support vector machines
Proceedings of the thirteenth ACM international conference on Information and knowledge management
A practical web-based approach to generating topic hierarchy for text segments
Proceedings of the thirteenth ACM international conference on Information and knowledge management
InfoAnalyzer: a computer-aided tool for building enterprise taxonomies
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Toward Integrating Feature Selection Algorithms for Classification and Clustering
IEEE Transactions on Knowledge and Data Engineering
Automatically learning document taxonomies for hierarchical classification
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Support vector machines classification with a very large-scale taxonomy
ACM SIGKDD Explorations Newsletter - Natural language processing and text mining
Taxonomies by the numbers: building high-performance taxonomies
Proceedings of the 14th ACM international conference on Information and knowledge management
Learning hierarchical multi-category text classification models
ICML '05 Proceedings of the 22nd international conference on Machine learning
Hierarchical Dirichlet model for document classification
ICML '05 Proceedings of the 22nd international conference on Machine learning
Bias Analysis in Text Classification for Highly Skewed Data
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
ICML '06 Proceedings of the 23rd international conference on Machine learning
Hierarchical classification: combining Bayes with SVM
ICML '06 Proceedings of the 23rd international conference on Machine learning
Acclimatizing Taxonomic Semantics for Hierarchical Content Classification
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Computational Methods of Feature Selection (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)
Incremental Algorithms for Hierarchical Classification
The Journal of Machine Learning Research
Mining changes in customer behavior in retail marketing
Expert Systems with Applications: An International Journal
Large scale multi-label classification via metalabeler
Proceedings of the 18th international conference on World wide web
Relational learning via latent social dimensions
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Improving taxonomies for large-scale hierarchical classifiers of web documents
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Group Profiling for Understanding Social Structures
ACM Transactions on Intelligent Systems and Technology (TIST)
Hierarchy evolution for improved classification
Proceedings of the 20th ACM international conference on Information and knowledge management
Editorial: Narrative-based taxonomy distillation for effective indexing of text collections
Data & Knowledge Engineering
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A topic taxonomy is an effective representation that describes salient features of virtual groups or online communities. A topic taxonomy consists of topic nodes. Each internal node is defined by its vertical path (i.e., ancestor and child nodes) and its horizonal list of attributes (or terms). In a text-dominant environment, a topic taxonomy can be used to flexibly describe a group's interests with varying granularity. However, the stagnant nature of a taxonomy may fail to timely capture the dynamic change of a group's interest. This article addresses the problem of how to adapt a topic taxonomy to the accumulated data that reflects the change of a group's interest to achieve dynamic group profiling. We first discuss the issues related to topic taxonomy. We next formulate taxonomy adaptation as an optimization problem to find the taxonomy that best fits the data. We then present a viable algorithm that can efficiently accomplish taxonomy adaptation. We conduct extensive experiments to evaluate our approach's efficacy for group profiling, compare the approach with some alternatives, and study its performance for dynamic group profiling. While pointing out various applications of taxonomy adaption, we suggest some future work that can take advantage of burgeoning Web 2.0 services for online targeted marketing, counterterrorism in connecting dots, and community tracking.