The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Language models for hierarchical summarization
Language models for hierarchical summarization
Centroid-based summarization of multiple documents
Information Processing and Management: an International Journal
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
Improving web search results using affinity graph
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Unsupervised construction of large paraphrase corpora: exploiting massively parallel news sources
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Using random walks for question-focused sentence retrieval
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
The Pyramid Method: Incorporating human content selection variation in summarization evaluation
ACM Transactions on Speech and Language Processing (TSLP)
Automatic summarising: The state of the art
Information Processing and Management: an International Journal
A tutorial on spectral clustering
Statistics and Computing
Multi-document summarization using cluster-based link analysis
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Mind the gap: dangers of divorcing evaluations of summary content from linguistic quality
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Scientific paper summarization using citation summary networks
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
Manifold-ranking based topic-focused multi-document summarization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
GenDocSum+MCLR: Generic document summarization based on maximum coverage and less redundancy
Expert Systems with Applications: An International Journal
Integrating statistical and lexical information for recognizing textual entailments in text
Knowledge-Based Systems
Hi-index | 12.05 |
Update summarization is a new challenge in automatic text summarization. Different from the traditional static summarization, it deals with the dynamically evolving document collections of a single topic changing over time, which aims to incrementally deliver salient and novel information to a user who has already read the previous documents. How to have a content selection and linguistic quality control in a temporal context are the two new challenges brought by update summarization. In this paper, we address a novel content selection framework based on evolutionary manifold-ranking and normalized spectral clustering. The proposed evolutionary manifold-ranking aims to capture the temporal characteristics and relay propagation of information in dynamic data stream and user need. This approach tries to keep the summary content to be important, novel and relevant to the topic. Incorporation with normalized spectral clustering is to make summary content have a high coverage for each sub-topic. Ordering sub-topics and selecting sentences are dependent on the rank score from evolutionary manifold-ranking and the proposed redundancy removal strategy with exponent decay. The evaluation results on the update summarization task of Text Analysis Conference (TAC) 2008 demonstrate that our proposed approach is competitive. In the 71 run systems, we receive three top 1 under PYRAMID metrics, ranking 13th in ROUGE-2, 15th in ROUGE-SU4 and 21st in BE.