Abstract
This paper introduces a novel approach to represent multiple documents as a single graph, namely, the graph-of-docs model, together with an associated novel algorithm for text categorization. The proposed approach enables the investigation of the importance of a term into a whole corpus of documents and supports the inclusion of relationship edges between documents, thus enabling the calculation of important metrics as far as documents are concerned. Compared to well-tried existing solutions, our initial experimentations demonstrate a significant improvement of the accuracy of the text categorization process. For the experimentations reported in this paper, we used a well-known dataset containing about 19,000 documents organized in various subjects.
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Acknowledgements
The work presented in this paper is supported by the OpenBio-C project (www.openbio.eu), which is co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH—CREATE—INNOVATE (Project id: T1EDK-05275).
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Giarelis, N., Kanakaris, N., Karacapilidis, N. (2020). On a Novel Representation of Multiple Textual Documents in a Single Graph. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies. IDT 2020. Smart Innovation, Systems and Technologies, vol 193. Springer, Singapore. https://doi.org/10.1007/978-981-15-5925-9_9
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