ACM Computing Surveys (CSUR)
Techniques of Cluster Algorithms in Data Mining
Data Mining and Knowledge Discovery
Journal of Global Optimization
Introduction to the special issue on summarization
Computational Linguistics - Summarization
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Creating Generic Text Summaries
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Efficient Phrase-Based Document Indexing for Web Document Clustering
IEEE Transactions on Knowledge and Data Engineering
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
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Effective Summarization Method of Text Documents
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Summary in context: Searching versus browsing
ACM Transactions on Information Systems (TOIS)
One story, one flow: Hidden Markov Story Models for multilingual multidocument summarization
ACM Transactions on Speech and Language Processing (TSLP)
Sentence Similarity Based on Semantic Nets and Corpus Statistics
IEEE Transactions on Knowledge and Data Engineering
Dominant Sets and Pairwise Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Novel Partitioning-Based Clustering Method and Generic Document Summarization
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Measuring semantic similarity between words using web search engines
Proceedings of the 16th international conference on World Wide Web
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
Multi-candidate reduction: Sentence compression as a tool for document summarization tasks
Information Processing and Management: an International Journal
QCS: A system for querying, clustering and summarizing documents
Information Processing and Management: an International Journal
Sentence Similarity based on Dynamic Time Warping
ICSC '07 Proceedings of the International Conference on Semantic Computing
An overview of clustering methods
Intelligent Data Analysis
Text Clustering with Feature Selection by Using Statistical Data
IEEE Transactions on Knowledge and Data Engineering
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
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
An intelligent summarization system based on cognitive psychology
Information Sciences: an International Journal
Automatic Clustering Using an Improved Differential Evolution Algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Blended metrics for novel sentence mining
Expert Systems with Applications: An International Journal
Short communication: A novel sentence similarity measure for semantic-based expert systems
Expert Systems with Applications: An International Journal
SyMSS: A syntax-based measure for short-text semantic similarity
Data & Knowledge Engineering
Integrated expert system applied to the analysis of non-technical losses in power utilities
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Applied Computational Intelligence and Soft Computing
Fine-grained topic detection in news search results
Proceedings of the 27th Annual ACM Symposium on Applied Computing
MCMR: Maximum coverage and minimum redundant text summarization model
Expert Systems with Applications: An International Journal
GenDocSum+MCLR: Generic document summarization based on maximum coverage and less redundancy
Expert Systems with Applications: An International Journal
TakeLab: systems for measuring semantic text similarity
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
CDDS: Constraint-driven document summarization models
Expert Systems with Applications: An International Journal
Automatic multi-document summarization based on new sentence similarity measures
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Multiple documents summarization based on evolutionary optimization algorithm
Expert Systems with Applications: An International Journal
Formulation of document summarization as a 0-1 nonlinear programming problem
Computers and Industrial Engineering
A cross-media evolutionary timeline generation framework based on iterative recommendation
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Automated crime report analysis and classification for e-government and decision support
Proceedings of the 14th Annual International Conference on Digital Government Research
Information Sciences: 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 |
The technology of automatic document summarization is maturing and may provide a solution to the information overload problem. Nowadays, document summarization plays an important role in information retrieval. With a large volume of documents, presenting the user with a summary of each document greatly facilitates the task of finding the desired documents. Document summarization is a process of automatically creating a compressed version of a given document that provides useful information to users, and multi-document summarization is to produce a summary delivering the majority of information content from a set of documents about an explicit or implicit main topic. In our study we focus on sentence based extractive document summarization. We propose the generic document summarization method which is based on sentence clustering. The proposed approach is a continue sentence-clustering based extractive summarization methods, proposed in Alguliev [Alguliev, R. M., Aliguliyev, R. M., Bagirov, A. M. (2005). Global optimization in the summarization of text documents. Automatic Control and Computer Sciences 39, 42-47], Aliguliyev [Aliguliyev, R. M. (2006). A novel partitioning-based clustering method and generic document summarization. In Proceedings of the 2006 IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology (WI-IAT 2006 Workshops) (WI-IATW'06), 18-22 December (pp. 626-629) Hong Kong, China], Alguliev and Alyguliev [Alguliev, R. M., Alyguliev, R. M. (2007). Summarization of text-based documents with a determination of latent topical sections and information-rich sentences. Automatic Control and Computer Sciences 41, 132-140] Aliguliyev, [Aliguliyev, R. M. (2007). Automatic document summarization by sentence extraction. Journal of Computational Technologies 12, 5-15.]. The purpose of present paper to show, that summarization result not only depends on optimized function, and also depends on a similarity measure. The experimental results on an open benchmark datasets from DUC01 and DUC02 show that our proposed approach can improve the performance compared to sate-of-the-art summarization approaches.