Paper Info
Title
A French Human Reference Corpus for Multi-Document Summarization and Sentence Compression
Abstract
This paper presents two corpora produced within the RPM2 project: a multi-document summarization corpus and a sentence compression corpus. Both corpora are in French. The first one is the only one we know in this language. It contains 20 topics with 20 documents each. A first set of 10 documents per topic is summarized and then the second set is used to produce an update summarization (new information). 4 annotators were involved and produced a total of 160 abstracts. The second corpus contains all the sentences of the first one. 4 annotators were asked to compress the 8432 sentences. This is the biggest corpus of compressed sentences we know, whatever the language. The paper provides some figures in order to compare the different annotators: compression rates, number of tokens per sentence, percentage of tokens kept according to their POS, position of dropped tokens in the sentence compression phase, etc. These figures show important differences from an annotator to the other. Another point is the different strategies of compression used according to the length of the sentence.
Year
Venue
Keywords
2010
LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
multi document summarization
Field
DocType
Citations 
Multi-document summarization,Automatic summarization,Computer science,Speech recognition,Sentence compression,Natural language processing,Artificial intelligence,Sentence
Conference
1
PageRank 
References 
Authors
0.39
7
5
Name
Order
Citations
PageRank
Claude De Loupy1338.58
Marie Guégan271.63
Christelle Ayache320018.69
Somara Seng411.06
Juan-Manuel Torres-Moreno535951.36