Paper: Topic-Driven Multi-Document Summarization with Encyclopedic Knowledge and Spreading Activation

ACL ID D08-1080
Title Topic-Driven Multi-Document Summarization with Encyclopedic Knowledge and Spreading Activation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

Information of interest to users is often dis- tributed over a set of documents. Users can specify their request for information as a query/topic – a set of one or more sentences or questions. Producing a good summary of the relevant information relies on understand- ing the query and linking it with the associ- ated set of documents. To “understand” the query we expand it using encyclopedic knowl- edge in Wikipedia. The expanded query is linked with its associated documents through spreading activation in a graph that represents words and their grammatical connections in these documents. The topic expanded words and activated nodes in the graph are used to produce an extractive summary. The method proposed is tested on the DUC summariza- tion data. The system implemented ranks high ...