Topic detection and tracking: event-based information organization
Topic detection and tracking: event-based information organization
Automatic labeling of multinomial topic models
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Enhancing cluster labeling using wikipedia
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Conceptualizing documents with Wikipedia
Proceedings of the fifth workshop on Exploiting semantic annotations in information retrieval
Unsupervised graph-based topic labelling using dbpedia
Proceedings of the sixth ACM international conference on Web search and data mining
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This paper presents a particular approach to collective labeling of multiple documents, which works by associating the documents with Wikipedia pages and labeling them with headings the pages carry. The approach has an obvious advantage over past approaches in that it is able to produce fluent labels, as they are hand-written by human editors. We carried out some experiments on the TDT5 dataset, which found that the approach works rather robustly for an arbitrary set of documents in the news domain. Comparisons were made with some baselines, including the state of the art, with results strongly in favor of our approach.