Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps
Table 2: Topic clusters in comparison to classic corpora (size in token, mean with standard deviation).
['Corpus', 'Cluster', 'Cluster Size', 'Docs', 'Doc. Size', 'Rel. Std.']
The corpus consists of document clusters for 30 different topics. Each of them contains around 40 documents with on average 2413 tokens, which leads to an average cluster size of 97,880 token. In addition, the documents are also more variable in terms of length, as the (length-adjusted) standard deviation is twice as high as in the other corpora. With these properties, the corpus represents an interesting challenge towards real-world application scenarios, in which users typically have to deal with much more than ten documents.