The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
A framework for abstracting data sources having heterogeneous representation formats
Data & Knowledge Engineering
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Choosing the content of textual summaries of large time-series data sets
Natural Language Engineering
Data & Knowledge Engineering
Noise reduction through summarization for Web-page classification
Information Processing and Management: 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
Text Entailment for Logical Segmentation and Summarization
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Multilingual Feature-Driven Opinion Extraction and Summarization from Customer Reviews
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
The AMTEx approach in the medical document indexing and retrieval application
Data & Knowledge Engineering
Natural Language Engineering
Extractive summarization based on event term clustering
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Scientific paper summarization using citation summary networks
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Extractive summarization using supervised and semi-supervised learning
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
CBSEAS, a summarization system integration of opinion mining techniques to summarize blogs
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations Session
Using citations to generate surveys of scientific paradigms
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
An integrated framework for de-identifying unstructured medical data
Data & Knowledge Engineering
A perspective-based approach for solving textual entailment recognition
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
Automatically generating Wikipedia articles: a structure-aware approach
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
A classification algorithm for predicting the structure of summaries
UCNLG+Sum '09 Proceedings of the 2009 Workshop on Language Generation and Summarisation
Non-textual event summarization by applying machine learning to template-based language generation
UCNLG+Sum '09 Proceedings of the 2009 Workshop on Language Generation and Summarisation
INLG '08 Proceedings of the Fifth International Natural Language Generation Conference
A new approach to improving multilingual summarization using a genetic algorithm
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Multi-sentence compression: finding shortest paths in word graphs
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Retrieval of similar electronic health records using UMLS concept graphs
NLDB'10 Proceedings of the Natural language processing and information systems, and 15th international conference on Applications of natural language to information systems
Extracting hot spots of topics from time-stamped documents
Data & Knowledge Engineering
AZOM: a Persian structured text summarizer
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Editorial: Narrative-based taxonomy distillation for effective indexing of text collections
Data & Knowledge Engineering
Extracting multi-document summaries with a double clustering approach
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Can text summaries help predict ratings? a case study of movie reviews
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Hierarchical clustering of XML documents focused on structural components
Data & Knowledge Engineering
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This article analyzes the appropriateness of a text summarization system, COMPENDIUM, for generating abstracts of biomedical papers. Two approaches are suggested: an extractive (COMPENDIUM"E), which only selects and extracts the most relevant sentences of the documents, and an abstractive-oriented one (COMPENDIUM"E"-"A), thus facing also the challenge of abstractive summarization. This novel strategy combines extractive information, with some pieces of information of the article that have been previously compressed or fused. Specifically, in this article, we want to study: i) whether COMPENDIUM produces good summaries in the biomedical domain; ii) which summarization approach is more suitable; and iii) the opinion of real users towards automatic summaries. Therefore, two types of evaluation were performed: quantitative and qualitative, for evaluating both the information contained in the summaries, as well as the user satisfaction. Results show that extractive and abstractive-oriented summaries perform similarly as far as the information they contain, so both approaches are able to keep the relevant information of the source documents, but the latter is more appropriate from a human perspective, when a user satisfaction assessment is carried out. This also confirms the suitability of our suggested approach for generating summaries following an abstractive-oriented paradigm.