A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
Automatic text summarization aims to address the information overload problem by extracting the most important information from a document, which can help a reader to decide whether it is relevant or not. In this paper we propose a method of personalized text summarization which improves the conventional automatic text summarization methods by taking into account the differences in readers' characteristics. We use annotations added by readers as one of the sources of personalization. We havedoi:10.1109/dexa.2012.47 dblp:conf/dexaw/MoroB12 fatcat:tpgrraop5bddrlnulkpptjuec4