@inproceedings{e0b33b4210584c84a2c0b3b8458246f7,
title = "From web crawled text to project descriptions: automatic summarizing of social innovation projects",
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.",
keywords = "evaluation metrics, natural language processing, neural networks, social innovation, summarization, SVM, text mining",
author = "Nikola Milo{\v s}evi{\'c} and Dimitar Marinov and Abdullah G{\"o}k and Goran Nenadi{\'c}",
year = "2019",
month = jun,
day = "21",
doi = "10.1007/978-3-030-23281-8_13",
language = "English",
isbn = "9783030232801",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "157--169",
editor = "Elisabeth M{\'e}tais and Farid Meziane and Sunil Vadera and Vijayan Sugumaran and Mohamad Saraee",
booktitle = "Natural Language Processing and Information Systems",
note = "24th International Conference on Application of Natural Language to Information Systems, NLDB 2019 ; Conference date: 26-06-2019 Through 28-06-2019",
}