Kanopy: Analysing the Semantic Network Around Document Topics
Abstract
External knowledge bases, both generic and domain specific, available on the Web of Data have the potential of enriching the content of text documents with structured information. We present the Kanopy system that makes explicit use of this potential. Besides the common task of semantic annotation of documents, Kanopy analyses the semantic network that resides in DBpedia around extracted concepts. The system’s main novelty lies in the translation of social network analysis measures to semantic networks in order to find suitable topic labels. Moreover, Kanopy extracts advanced knolwedge in the form of subgraphs that capture the relationships between the concepts.
Cite
Text
Hulpus et al. "Kanopy: Analysing the Semantic Network Around Document Topics." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2013. doi:10.1007/978-3-642-40994-3_53Markdown
[Hulpus et al. "Kanopy: Analysing the Semantic Network Around Document Topics." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2013.](https://mlanthology.org/ecmlpkdd/2013/hulpus2013ecmlpkdd-kanopy/) doi:10.1007/978-3-642-40994-3_53BibTeX
@inproceedings{hulpus2013ecmlpkdd-kanopy,
title = {{Kanopy: Analysing the Semantic Network Around Document Topics}},
author = {Hulpus, Ioana and Hayes, Conor and Karnstedt, Marcel and Greene, Derek and Jozwowicz, Marek},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2013},
pages = {677-680},
doi = {10.1007/978-3-642-40994-3_53},
url = {https://mlanthology.org/ecmlpkdd/2013/hulpus2013ecmlpkdd-kanopy/}
}