Hierarchical mixtures of experts and the EM algorithm
Neural Computation
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Learning to classify text from labeled and unlabeled documents
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
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 classification of Web content
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Modern Information Retrieval
Self-Organizing Maps
Hierarchical Text Categorization Using Neural Networks
Information Retrieval
Toward Optimal Active Learning through Sampling Estimation of Error Reduction
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Partially Supervised Classification of Text Documents
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Hierarchical Text Classification and Evaluation
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Enhancing Supervised Learning with Unlabeled Data
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Building Hierarchical Classifiers Using Class Proximity
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Using Taxonomy, Discriminants, and Signatures for Navigating in Text Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Clustering documents in a web directory
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
Bootstrapping for hierarchical document classification
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Hierarchical classification of HTML documents with WebClassII
ECIR'03 Proceedings of the 25th European conference on IR research
A similarity-based method for retrieving documents from the SCI/SSCI database
Journal of Information Science
Mining taxonomies of process models
Data & Knowledge Engineering
Improving density-based methods for hierarchical clustering of web pages
Data & Knowledge Engineering
Building Quality-Based Views of the Web
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Bayesian network models for hierarchical text classification from a thesaurus
International Journal of Approximate Reasoning
Neural network for graphs: a contextual constructive approach
IEEE Transactions on Neural Networks
Efficient Coverage of Case Space with Active Learning
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Automatically computed document dependent weighting factor facility for Naïve Bayes classification
Expert Systems with Applications: An International Journal
d-Confidence: an active learning strategy which efficiently identifies small classes
ALNLP '10 Proceedings of the NAACL HLT 2010 Workshop on Active Learning for Natural Language Processing
Automatic maintenance of web directories by mining web browsing data
Journal of Web Engineering
Expert Systems with Applications: An International Journal
Two phase semi-supervised clustering using background knowledge
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Semi-supervised clustering algorithm for haplotype assembly problem based on MEC model
International Journal of Data Mining and Bioinformatics
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The management of hierarchically organized data is starting to play a key role in the knowledge management community due to the proliferation of topic hierarchies for text documents. The creation and maintenance of such organized repositories of information requires a great deal of human intervention.The machine learning community has partially addressed this problem by developing hierarchical supervised classifiers that help people categorize new resources within given hierarchies. The worst problem of hierarchical supervised classifiers, however, is their high demand in terms of labeled examples. The number of examples required is related to the number of topics in the taxonomy. Bootstrapping a huge hierarchy with a proper set of labeled examples is therefore a critical issue.This paper proposes some solutions for the bootstrapping problem, that implicitly or explicitly use taxonomy definition: a baseline approach that classifies documents according to the class terms, and two clustering approaches, whose training is constrained by the a priori knowledge encoded in the taxonomy structure, which consists of both terminological and relational aspects. In particular, we propose the Tax-SOM model, that clusters a set of documents in a predefined hierarchy of classes, directly exploiting the knowledge of both their topological organization and their lexical description. Experimental evaluation was performed on a set of taxonomies taken from the GoogleTM and LookSmartTM web directories, obtaining good results.