Algorithms for clustering data
Algorithms for clustering data
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
A trainable document summarizer
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
The retrieval effectiveness of five clustering algorithms as a function of indexing exhaustivity
Journal of the American Society for Information Science
Feature selection, perceptron learning, and a usability case study for text categorization
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
A Robust Competitive Clustering Algorithm With Applications in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
OPTICS: ordering points to identify the clustering structure
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Information Retrieval: Algorithms and Heuristics
Information Retrieval: Algorithms and Heuristics
Modern Information Retrieval
Introduction to the special issue on summarization
Computational Linguistics - Summarization
Creating Generic Text Summaries
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
A class of fuzzy random optimization: expected value models
Information Sciences: an International Journal
An Intelligent Information System for Organizing Online Text Documents
Knowledge and Information Systems
Text summarization using a trainable summarizer and latent semantic analysis
Information Processing and Management: an International Journal - Special issue: An Asian digital libraries perspective
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
A web-trained extraction summarization system
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization
IEEE Transactions on Knowledge and Data Engineering
Text classification: A least square support vector machine approach
Applied Soft Computing
Measuring semantic similarity between words using web search engines
Proceedings of the 16th international conference on World Wide Web
Using SVD and demographic data for the enhancement of generalized Collaborative Filtering
Information Sciences: an International Journal
An automatic method for summary evaluation using multiple evaluation results by a manual method
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A novel document similarity measure based on earth mover's distance
Information Sciences: an International Journal
Automatic summarising: The state of the art
Information Processing and Management: an International Journal
QCS: A system for querying, clustering and summarizing documents
Information Processing and Management: an International Journal
A Graph-Theoretic Approach to Nonparametric Cluster Analysis
IEEE Transactions on Computers
Top 10 algorithms in data mining
Knowledge and Information Systems
GA, MR, FFNN, PNN and GMM based models for automatic text summarization
Computer Speech and Language
Text Clustering with Feature Selection by Using Statistical Data
IEEE Transactions on Knowledge and Data Engineering
Expert Systems with Applications: An International Journal
A fast k-means clustering algorithm using cluster center displacement
Pattern Recognition
Document summarization using conditional random fields
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Manifold-ranking based topic-focused multi-document summarization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Fuzzy sets in machine learning and data mining
Applied Soft Computing
K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonparametric genetic clustering: comparison of validity indices
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Multiobjective GAs, quantitative indices, and pattern classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
ICE - Intelligent Clustering Engine: A clustering gadget for Google Desktop
Expert Systems with Applications: An International Journal
Semi supervised clustering: a pareto approach
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
CDDS: Constraint-driven document summarization models
Expert Systems with Applications: An International Journal
Multiple documents summarization based on evolutionary optimization algorithm
Expert Systems with Applications: An International Journal
Data summarization ontology-based query processing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Extractive single-document summarization based on genetic operators and guided local search
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Modern information retrieval (IR) systems consist of many challenging components, e.g. clustering, summarization, etc. Nowadays, without browsing the whole volume of datasets, IR systems present users with clusters of documents they are interested in, and summarize each document briefly which facilitates the task of finding the desired documents. This paper proposes a fuzzy evolutionary optimization modeling (FEOM) and its applications to unsupervised categorization and extractive summarization. In view of the nature of biological evolution, we take advantage of several fuzzy control parameters to adaptively regulate the behaviors of the evolutionary optimization, which can effectively prevent premature convergence to a local optimal solution. As a portable, modular and extensively executable model, FEOM is firstly implemented for clustering text documents. The searching capability of FEOM is exploited to explore appropriate partitions of documents such that the similarity metric of the resulting clusters is optimized. In order to further investigate its effectiveness as a generic data clustering model, FEOM is then applied to sentence clustering based extractive document summarization. It selects the most important sentence from each cluster to represent the overall meaning of document. We demonstrate the improved performance by a series of experiments using standard test sets, e.g. Reuter document collection, 20-newsgroup corpus, DUC01 and DUC02, as evaluated by some commonly used metrics, i.e. F-measure and ROUGE. The experimental results show that FEOM achieves performance as good as or better than state of arts of clustering and summarizing systems.