Annotation of Smart Cities Twitter Micro-Contents for Enhanced Citizen's Engagement

被引：40

作者：

Alkhammash, Eman H. ^{[1
]}

Jussila, Jari ^{[2
]}

Lytras, Miltiadis D. ^{[3
]}

Visvizi, Anna ^{[4
]}

机构：

[1] Taif Univ, Coll Comp & Informat Technol, Dept Comp Sci, At Taif 21974, Saudi Arabia

[2] HAMK Hame Univ Appl Sci, HAMK Smart Res Unit, Hameenlinna 13100, Finland

[3] King Abdulaziz Univ, Fac Comp & Informat Technol, Jeddah 21589, Saudi Arabia

[4] Effat Univ, Effat Coll Business, Jeddah, Saudi Arabia

来源：

IEEE ACCESS | 2019年 / 7卷

关键词：

Ontotext; smart cities; social mining; sustainability; engagement; open innovation; technovation; semantic annotation; BIG DATA;

D O I：

10.1109/ACCESS.2019.2935186

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The digital content in smart city, is a critical asset. It can be used for multiple purposes and offers added value layers for customization and personalization of services. Numerous research issues, related to standardization, annotation, visualization and sentiment analysis pose critical research questions. In our approach within a greatest context of academic research we deal with the semi-automatic annotation of smart city contexts, and more specifically the annotation of twitter-content for the promotion of citizen's engagement. We discuss in detail the feasibility of technical approaches with the deployment of open platforms and approaches, towards value adding services. The greatest challenge of our research is to promote an open-collaborative semantic annotation framework for social content in smart city, promoting engagement modes.

引用

页码：116267 / 116276

页数：10

共 28 条

[1]

[Anonymous], 2012, UN E GOVT SURVEY 201, DOI DOI 10.18356/B1052762-EN

[2]

[Anonymous], 2018, P COMP WEB C 2018 WE

[3]

[Anonymous], DTG4 1 PRACTICAL EXP

[4]

Aramaki E., 2011, Proceedings of the 2011 Conference on empirical methods in natural language processing, P1568

[5]

Barbosa L., 2010, P 23 INT C COMP LING, P36

[6]

Bechhofer S, 2002, LECT NOTES COMPUT SC, V2519, P1152

[7] Annotating Relations Between Named Entities with Crowdsourcing [J].

Collovini, Sandra ;

Pereira, Bolivar ;

dos Santos, Henrique D. P. ;

Vieira, Renata .

NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS (NLDB 2018), 2018, 10859 :290-297

[8]

Finin Tim., 2010, Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, P80

[9] Social Media Data Can Be Used to Understand Tourists' Preferences for Nature-Based Experiences in Protected Areas [J].

Hausmann, Anna ;

Toivonen, Tuuli ;

Slotow, Rob ;

Tenkanen, Henrikki ;

Moilanen, Atte ;

Heikinheimo, Vuokko ;

Di Minin, Enrico .

CONSERVATION LETTERS, 2018, 11 (01)

[10]

Hawksey M., TAGS

← 1 2 3 →