Paper: Generating Aspect-oriented Multi-Document Summarization with Event-aspect model

ACL ID D11-1105
Title Generating Aspect-oriented Multi-Document Summarization with Event-aspect model
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

In this paper, we propose a novel approach to automatic generation of aspect-oriented sum- maries from multiple documents. We first de- velop an event-aspect LDA model to cluster sentences into aspects. We then use extend- ed LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Pro- grammingforsentenceselection. Keyfeatures of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantita- tive evaluation based on Rouge metric demon- strates the effectiveness and advantages of our method.