Cover coefficient-based multi-document summarization
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/26745
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- Conference Paper 
In this paper we present a generic, language independent multi-document summarization system forming extracts using the cover coefficient concept. Cover Coefficient-based Summarizer (CCS) uses similarity between sentences to determine representative sentences. Experiments indicate that CCS is an efficient algorithm that is able to generate quality summaries online. © Springer-Verlag Berlin Heidelberg 2009.
Showing items related by title, author, creator and subject.
Demirtas, K.; Cicekli, N.K.; Cicekli I. (2010)In this paper, we propose automatic categorization and summarization of documentaries using subtitles of videos. We propose two methods for video categorization. The first makes unsupervised categorization by applying ...
Demirtas, K.; Cicekli I.; Cicekli, N.K. (2010)Video summarization algorithms present condensed versions of a full length video by identifying the most significant parts of the video. In this paper, we propose an automatic video summarization method using the subtitles ...
Ciǧir, C.; Kutlu, M.; Cicekli I. (2009)In this paper, we propose a generic text summarization method that generates summaries of Turkish texts by ranking sentences according to their scores calculated using their surface level features and extracting the highest ...