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

Standard

From web crawled text to project descriptions: automatic summarizing of social innovation projects. / Milošević, Nikola; Marinov, Dimitar; Gӧk, Abdullah; Nenadic, Goran.

24th International Conference on Applications of Natural Language to Information Systems. Springer, 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Milošević, N, Marinov, D, Gӧk, A & Nenadic, G 2019, From web crawled text to project descriptions: automatic summarizing of social innovation projects. in 24th International Conference on Applications of Natural Language to Information Systems. Springer, 24th International Conference on Applications of Natural Language to Information Systems, Salford, United Kingdom, 26/06/19. https://doi.org/10.1007/978-3-030-23281-8_13

APA

Milošević, N., Marinov, D., Gӧk, A., & Nenadic, G. (2019). From web crawled text to project descriptions: automatic summarizing of social innovation projects. In 24th International Conference on Applications of Natural Language to Information Systems Springer. https://doi.org/10.1007/978-3-030-23281-8_13

Vancouver

Milošević N, Marinov D, Gӧk A, Nenadic G. From web crawled text to project descriptions: automatic summarizing of social innovation projects. In 24th International Conference on Applications of Natural Language to Information Systems. Springer. 2019 https://doi.org/10.1007/978-3-030-23281-8_13

Author

Milošević, Nikola ; Marinov, Dimitar ; Gӧk, Abdullah ; Nenadic, Goran. / From web crawled text to project descriptions: automatic summarizing of social innovation projects. 24th International Conference on Applications of Natural Language to Information Systems. Springer, 2019.

Bibtex

@inproceedings{26e3507ca2d64b448086efdb06935baa,
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. I 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 = "Summarization, evaluation metrics, text mining, natural language processing, social innovation, SVM, neural networks",
author = "Nikola Milošević and Dimitar Marinov and Abdullah Gӧk and Goran Nenadic",
year = "2019",
month = "6",
day = "21",
doi = "10.1007/978-3-030-23281-8_13",
language = "English",
booktitle = "24th International Conference on Applications of Natural Language to Information Systems",
publisher = "Springer",

}

RIS

TY - GEN

T1 - From web crawled text to project descriptions: automatic summarizing of social innovation projects

AU - Milošević, Nikola

AU - Marinov, Dimitar

AU - Gӧk, Abdullah

AU - Nenadic, Goran

PY - 2019/6/21

Y1 - 2019/6/21

N2 - 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. I 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.

AB - 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. I 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.

KW - Summarization

KW - evaluation metrics

KW - text mining

KW - natural language processing

KW - social innovation

KW - SVM

KW - neural networks

U2 - 10.1007/978-3-030-23281-8_13

DO - 10.1007/978-3-030-23281-8_13

M3 - Conference contribution

BT - 24th International Conference on Applications of Natural Language to Information Systems

PB - Springer

ER -