Commonsense based text mining on urban policy.
Local laws on urban policy, i.e., ordinances directly affect our daily life in various ways (health, business etc.), yet in practice, for many citizens they remain impervious and complex. This article focuses on an approach to make urban policy more accessible and comprehensible to the general publi...
| Publicado en: | Language Resources & Evaluation Vol. 57; no. 2; pp. 733 - 764 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Jun2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=163826583&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 163826583 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Jun2023 vid: 57 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 163826583 10.1007/s10579-022-09584-6 ppf: 733 ppct: 31 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.7MB tig: atl: Commonsense based text mining on urban policy. aug: au: Puri, Manish Varde, Aparna S. de Melo, Gerard affil: Allstate Insurance Company, Northfield Township, AZ, USA Department of Computer Science, Montclair State University, Montclair, NJ, USA Department of Computer Science, and Environmental Science & Management, PhD Program, Montclair State University, Montclair, NJ, USA Visiting Researcher at Max Planck Institute for Informatics, Saarbrücken, Germany Artificial Intelligence & Intelligent Systems, Hasso Plattner Institute, Potsdam, Germany Rutgers University, New Brunswick, NJ, USA su: Urban policy Text mining Smart cities Government policy Satisfaction Public spaces sug: subj: Urban policy Text mining Smart cities Government policy Satisfaction Public spaces keyword: Commonsense reasoning Opinion mining Ordinances Social media ab: Local laws on urban policy, i.e., ordinances directly affect our daily life in various ways (health, business etc.), yet in practice, for many citizens they remain impervious and complex. This article focuses on an approach to make urban policy more accessible and comprehensible to the general public and to government officials, while also addressing pertinent social media postings. Due to the intricacies of the natural language, ranging from complex legalese in ordinances to informal lingo in tweets, it is practical to harness human judgment here. To this end, we mine ordinances and tweets via reasoning based on commonsense knowledge so as to better account for pragmatics and semantics in the text. Ours is pioneering work in ordinance mining, and thus there is no prior labeled training data available for learning. This gap is filled by commonsense knowledge, a prudent choice in situations involving a lack of adequate training data. The ordinance mining can be beneficial to the public in fathoming policies and to officials in assessing policy effectiveness based on public reactions. This work contributes to smart governance, leveraging transparency in governing processes via public involvement. We focus significantly on ordinances contributing to smart cities, hence an important goal is to assess how well an urban region heads towards a smart city as per its policies mapping with smart city characteristics, and the corresponding public satisfaction. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2023. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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