Comparative news summarization using concept-based optimization

• Published in: Knowledge and information systems Vol. 38; no. 3; pp. 691 - 716
• Main Authors: Huang, Xiaojiang, Wan, Xiaojun, Xiao, Jianguo
• Format: Journal Article
• Language: English
• Published: London Springer London 01.03.2014; Springer; Springer Nature B.V
• Subjects: Analysis; Applied sciences; Artificial intelligence; Commonality; Comparative analysis; Computer Science; Computer science; control theory; systems; Data mining; Data Mining and Knowledge Discovery; Database Management; Exact sciences and technology; Information Storage and Retrieval; Information systems; Information Systems and Communication Service; Information Systems Applications (incl.Internet); Information systems. Data bases; Integer programming; IT in Business; Linear programming; Linguistics; Memory organisation. Data processing; Mining accidents & safety; News; Optimization; Regular Paper; Semantics; Sentences; Software; Speech and sound recognition and synthesis. Linguistics; Studies; Summaries; Tasks; Mixed integer programming; Comparative text mining; Multi-document summarization; Comparative news summarization; Hierarchical classification; Abstract; Text; Data mining; Conceptual analysis; Legibility; Modeling; Optimization; Experimental result; Semantics; Linguistics; Sentence; Pattern extraction; Mathematical programming

Comparative news summarization aims to highlight the commonalities and differences between two comparable news topics by using human-readable sentences. The summary ought to focus on the salient comparative aspects of both topics, and at the same time, it should describe the representative propertie...