Paper Info
Title
Topic-driven multi-document summarization with encyclopedic knowledge and spreading activation
Abstract
Information of interest to users is often distributed 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 understanding the query and linking it with the associated set of documents. To "understand" the query we expand it using encyclopedic knowledge 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 summarization data. The system implemented ranks high compared to the participating systems in the DUC competitions, confirming our hypothesis that encyclopedic knowledge is a useful addition to a summarization system.
Year
Venue
Keywords
2008
EMNLP
summarization system,extractive summary,expanded query,encyclopedic knowledge,activated node,good summary,associated document,duc summarization data,duc competition,relevant information,topic-driven multi-document summarization,multi document summarization,spreading activation
Field
DocType
Volume
Automatic summarization,Graph,Multi-document summarization,Information retrieval,Computer science,Request for information,Artificial intelligence,Natural language processing
Conference
D08-1
Citations 
PageRank 
References 
56
2.23
16
Authors
1
Name
Order
Citations
PageRank
Vivi Nastase152341.30