<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This work proposes a software environment implementing a methodology for acquiring and exploiting the collective perception (CP) of Points of Interests (POIs) in a Smart City, which is meant to support decision makers in urban planning and management. This environment relies upon semantic knowledge discovery techniques and fuzzy computational approaches, including natural language processing, sentiment analysis, POI signatures and Fuzzy Cognitive Maps, turning them into a cohesive architectural blend in order to effectively gather the realistic perception of a user community towards given areas and attractions of a Smart City. The environment has been put to the test via a thorough experimentation against a massive user base of an online community with respect to a large metropolitan city (the City of Naples). Such an experimentation yielded consistent results, useful for providing decision makers with a clear awareness of the positive as well as critical aspects of urban areas, and thus helping them shape the measures to be taken for an improved city management and development.</p></abstract>

This work proposes a software environment implementing a methodology for acquiring and exploiting the collective perception (CP) of Points of Interests (POIs) in a Smart City, which is meant to support decision makers in urban planning and management. This environment relies upon semantic knowledge discovery techniques and fuzzy computational approaches, including natural language processing, sentiment analysis, POI signatures and Fuzzy Cognitive Maps, turning them into a cohesive architectural blend in order to effectively gather the realistic perception of a user community towards given areas and attractions of a Smart City. The environment has been put to the test via a thorough experimentation against a massive user base of an online community with respect to a large metropolitan city (the City of Naples). Such an experimentation yielded consistent results, useful for providing decision makers with a clear awareness of the positive as well as critical aspects of urban areas, and thus helping them shape the measures to be taken for an improved city management and development.

An Environment for Collective Perception based on Fuzzy and Semantic Approaches

Department of Information and Electrical Engineering and Applied Mathematics

Department of Electrical and Computer Engineering

Journal of Artificial Intelligence and Soft Computing Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"An Environment for Collective Perception based on Fuzzy and Semantic Approaches"}

This work proposes a software environment implementing a methodology for acquiring and exploiting the collective perception (CP) of Points of Interests (POIs)...

An Environment for Collective Perception based on Fuzzy and Semantic Approaches

Online veröffentlicht: 09. Feb. 2018

Seitenbereich: 191 - 210

Eingereicht: 05. Sept. 2017

Akzeptiert: 30. Aug. 2017

DOI: https://doi.org/10.1515/jaiscr-2018-0013

Schlüsselwörter
smart cities, fuzzy logic, text mining, sentiment analysis

© 2018 Giuseppe D’Aniello et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

An Environment for Collective Perception based on Fuzzy and Semantic Approaches

Online veröffentlicht: 09. Feb. 2018

Seitenbereich: 191 - 210

Eingereicht: 05. Sept. 2017

Akzeptiert: 30. Aug. 2017

DOI: https://doi.org/10.1515/jaiscr-2018-0013

Schlüsselwörtersmart cities, fuzzy logic, text mining, sentiment analysis

© 2018 Giuseppe D’Aniello et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
smart cities, fuzzy logic, text mining, sentiment analysis