From web crawled text to project descriptions : automatic summarizing of social innovation projects

Milošević, Nikola and Marinov, Dimitar and Gök, Abdullah and Nenadić, Goran; Métais, Elisabeth and Meziane, Farid and Vadera, Sunil and Sugumaran, Vijayan and Saraee, Mohamad, eds. (2019) From web crawled text to project descriptions : automatic summarizing of social innovation projects. In: Natural Language Processing and Information Systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer, GBR, pp. 157-169. ISBN 9783030232801 (https://doi.org/10.1007/978-3-030-23281-8_13)

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Abstract

In the past decade, social innovation projects have gained the attention of policy makers, as they address important social issues in an innovative manner. A database of social innovation is an important source of information that can expand collaboration between social innovators, drive policy and serve as an important resource for research. Such a database needs to have projects described and summarized. In this paper, we propose and compare several methods (e.g. SVM-based, recurrent neural network based, ensambled) for describing projects based on the text that is available on project websites. We also address and propose a new metric for automated evaluation of summaries based on topic modelling.

ORCID iDs

Milošević, Nikola, Marinov, Dimitar, Gök, Abdullah ORCID logoORCID: https://orcid.org/0000-0002-9378-3336 and Nenadić, Goran; Métais, Elisabeth, Meziane, Farid, Vadera, Sunil, Sugumaran, Vijayan and Saraee, Mohamad
CORE (COnnecting REpositories)