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

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

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.

Bibliographical metadata

Original languageEnglish
Title of host publication24th International Conference on Applications of Natural Language to Information Systems
PublisherSpringer
Publication statusAccepted/In press - 5 Apr 2019
Event24th International Conference on Applications of Natural Language to Information Systems - University of Salford, MediaCityUK Campus, Salford, United Kingdom
Event duration: 26 Jun 201928 Jun 2019

Conference

Conference24th International Conference on Applications of Natural Language to Information Systems
Abbreviated titleNLDB2019
CountryUnited Kingdom
CitySalford
Period26/06/1928/06/19