Graph based multi-modality learning
Proceedings of the 13th annual ACM international conference on Multimedia
Bayesian query-focused summarization
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Satisfying information needs with multi-document summaries
Information Processing and Management: an International Journal
Developing learning strategies for topic-based summarization
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
AdaSum: an adaptive model for summarization
Proceedings of the 17th ACM conference on Information and knowledge management
Topic-driven multi-document summarization with encyclopedic knowledge and spreading activation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Manifold-ranking based topic-focused multi-document summarization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Topic analysis for topic-focused multi-document summarization
Proceedings of the 18th ACM conference on Information and knowledge management
Topic analysis for topic-focused multi-document summarization
Proceedings of the 18th ACM conference on Information and knowledge management
Topic aspect analysis for multi-document summarization
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
To diversify or not to diversify entity summaries on RDF knowledge graphs?
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Summaries on the fly: query-based extraction of structured knowledge from web documents
ICWE'13 Proceedings of the 13th international conference on Web Engineering
The notion of diversity in graphical entity summarisation on semantic knowledge graphs
Journal of Intelligent Information Systems
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Topic-focused multi-document summarization has been a challenging task because the created summary is required to be biased to the given topic or query. Existing methods consider the given topic as a single coarse unit and then directly incorporate the relevance between each sentence and the single topic into the sentence evaluation process. However, the given topic is usually not well-defined and it consists of a few explicit or implicit subtopics. In this study, the related subtopics are discovered from the topic's narrative text or document set through topic analysis techniques. Then, the sentence relationships against each subtopic are considered as an individual modality and the multi-modality manifold-ranking method is proposed to evaluate and rank sentences by fusing the multiple modalities. Experimental results on the DUC benchmark datasets show the promising results of our proposed methods.