Lexical cohesion computed by thesaural relations as an indicator of the structure of text
Computational Linguistics
Multi-paragraph segmentation of expository text
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Computational Linguistics - Summarization
Capturing phrases for ICU-Talk, a communication aid for intubated intensive care patients.
Proceedings of the fifth international ACM conference on Assistive technologies
Text summarization using a trainable summarizer and latent semantic analysis
Information Processing and Management: an International Journal - Special issue: An Asian digital libraries perspective
An efficient text summarizer using lexical chains
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
CollabSum: exploiting multiple document clustering for collaborative single document summarizations
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Using lexical chains for keyword extraction
Information Processing and Management: an International Journal
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
Document Compaction for Efficient Query Biased Snippet Generation
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
An approach to text summarization
CLIAWS3 '09 Proceedings of the Third International Workshop on Cross Lingual Information Access: Addressing the Information Need of Multilingual Societies
Extractive Summarization Based on Event Term Temporal Relation Graph and Critical Chain
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Exploiting neighborhood knowledge for single document summarization and keyphrase extraction
ACM Transactions on Information Systems (TOIS)
Not as easy as it seems: automating the construction of lexical chains using Roget's thesaurus
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
A new hybrid summarizer based on vector space model, statistical physics and linguistics
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Automatic categorization and summarization of documentaries
Journal of Information Science
Research on content-based text retrieval and collaborative filtering in hybrid peer-to-peer networks
CSCWD'04 Proceedings of the 8th international conference on Computer Supported Cooperative Work in Design I
Research on mobile agent based information content-sharing in peer to peer system
CDVE'05 Proceedings of the Second international conference on Cooperative Design, Visualization, and Engineering
Incorporating cross-document relationships between sentences for single document summarizations
ECDL'06 Proceedings of the 10th European conference on Research and Advanced Technology for Digital Libraries
The CQC algorithm: cycling in graphs to semantically enrich and enhance a bilingual dictionary
Journal of Artificial Intelligence Research
International Journal of Web Engineering and Technology
Use of genetic algorithm for cohesive summary extraction to assist reading difficulties
Applied Computational Intelligence and Soft Computing
Hi-index | 0.00 |
The rapid growth of the Internet has resulted in enormous amounts of information that has become more difficult to access efficiently. Internet users require tools to help manage this vast quantity of information. The primary goal of this research is to create an efficient and effective tool that is able to summarize large documents quickly. This research presents a linear time algorithm for calculating lexical chains which is a method of capturing the “aboutness” of a document. This method is compared to previous, less efficient methods of lexical chain extraction. We also provide alternative methods for extracting and scoring lexical chains. We show that our method provides similar results to previous research, but is substantially more efficient. This efficiency is necessary in Internet search applications where many large documents may need to be summarized at once, and where the response time to the end user is extremely important.