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Mrazovic, P., De La Rubia, I., Urmeneta, J., Balufo, C., Tapias, R., Matskin, M. & Larriba-Pey, J. L. (2016). CIGO! Mobility Management Platform for Growing Efficient and Balanced Smart City Ecosystem. In: IEEE SECOND INTERNATIONAL SMART CITIES CONFERENCE (ISC2 2016): . Paper presented at 2nd IEEE International Smart Cities Conference (ISC2), SEP 12-15, 2016, Trento, ITALY (pp. 106-109). IEEE
Open this publication in new window or tab >>CIGO! Mobility Management Platform for Growing Efficient and Balanced Smart City Ecosystem
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2016 (English)In: IEEE SECOND INTERNATIONAL SMART CITIES CONFERENCE (ISC2 2016), IEEE, 2016, p. 106-109Conference paper, Published paper (Refereed)
Abstract [en]

The massive amount of tourists, citizens and traffic in big cities usually collapse busy areas causing transport inefficiency, unbalanced economic growth, crime, and nuisance among citizens and visitors. Therefore, the Smart City strategies such as Smart Mobility and Smart Governance naturally arise as means to improve mobility in urban areas. In this paper we propose a novel mobility management platform and business model that can attract numerous actors and still be orchestrated by the city government. The proposed platform integrates mobility data from various sources such as Open Data, mobile applications, sensors and government data, allowing for its visualisation and analysis while making it actionable through associated third party mobile applications. We propose to inject the city mobility policies to the third party mobile applications which provide services related to the city resources. In this way we form a value chain which connects different actors (city governments, mobile application providers, POI owners, companies that require logistics in cities, and final users) who both take a part in improving the mobility in urban areas, and benefit from the way mobility policies being executed. In this paper we discuss the business model and logical architecture of the proposed platform which has been already deployed in the city of Barcelona.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
smart cities, smart mobility, mobility policies
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-202502 (URN)10.1109/ISC2.2016.7580750 (DOI)000392263700020 ()2-s2.0-84994127946 (Scopus ID)978-1-5090-1845-1 (ISBN)
Conference
2nd IEEE International Smart Cities Conference (ISC2), SEP 12-15, 2016, Trento, ITALY
Note

QC 20170228

Available from: 2017-02-28 Created: 2017-02-28 Last updated: 2017-03-07Bibliographically approved
Sato, H., Matskin, M. & Claycomb, W. (2016). Message from the Program Chairs-in-Chief. Paper presented at 10 June 2016 through 14 June 2016. Computer Software and Applications Conference, 1, Article ID 7551982.
Open this publication in new window or tab >>Message from the Program Chairs-in-Chief
2016 (English)In: Computer Software and Applications Conference, ISSN 0730-3157, Vol. 1, article id 7551982Article in journal (Refereed) Published
Place, publisher, year, edition, pages
IEEE Computer Society, 2016
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-194940 (URN)10.1109/COMPSAC.2016.14 (DOI)2-s2.0-84988039968 (Scopus ID)
Conference
10 June 2016 through 14 June 2016
Note

QC 20161124

Available from: 2016-11-24 Created: 2016-11-01 Last updated: 2017-11-29Bibliographically approved
Sato, H., Matskin, M. & Claycomb, W. (2016). Message from the Program Chairs-in-Chief - Volume 2. Paper presented at 10 June 2016 through 14 June 2016. Computer Software and Applications Conference, 2, Article ID 7551963.
Open this publication in new window or tab >>Message from the Program Chairs-in-Chief - Volume 2
2016 (English)In: Computer Software and Applications Conference, ISSN 0730-3157, Vol. 2, article id 7551963Article in journal (Refereed) Published
Place, publisher, year, edition, pages
IEEE Computer Society, 2016
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-194941 (URN)10.1109/COMPSAC.2016.241 (DOI)2-s2.0-84988037177 (Scopus ID)
Conference
10 June 2016 through 14 June 2016
Note

QC 20161124

Available from: 2016-11-24 Created: 2016-11-01 Last updated: 2017-11-29Bibliographically approved
Jaradat, S., Dokoohaki, N., Matskin, M. & Ferrari, E. (2016). Trust And Privacy Correlations in Social Networks: A Deep Learning Framework. In: PROCEEDINGS OF THE 2016 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING ASONAM 2016: . Paper presented at 8th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), AUG 18-21, 2016, San Francisco, CA (pp. 203-206). IEEE conference proceedings
Open this publication in new window or tab >>Trust And Privacy Correlations in Social Networks: A Deep Learning Framework
2016 (English)In: PROCEEDINGS OF THE 2016 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING ASONAM 2016, IEEE conference proceedings, 2016, p. 203-206Conference paper, Published paper (Refereed)
Abstract [en]

Online Social Networks (OSNs) remain the focal point of Internet usage. Since the beginning, networking sites tried best to have right privacy mechanisms in place for users, enabling them to share the right content with the right audience. With all these efforts, privacy customizations remain hard for users across the sites. Existing research that address this problem mainly focus on semi-supervised strategies that introduce extra complexity by requiring the user to manually specify initial privacy preferences for their friends. In this work, we suggest an adaptive solution that can dynamically generate privacy labels for users in OSNs. To this end, we introduce a deep reinforcement learning framework that targets two key problems in OSNs like Facebook: the exposure of users' interactions through the network to less trusted direct friends, and the possibility of propagating user updates through direct friends' interactions to indirect friends. By implementing this framework, we aim at understanding how social trust and privacy could be correlated, specifically in a dynamic fashion. We report the ranked dependence between the generated privacy labels and the estimated user trust values, which indicate the ability of the framework to identify the highly trusted users and share with them higher percentages of data.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016
National Category
Computer Sciences
Identifiers
urn:nbn:se:kth:diva-200264 (URN)000390760100031 ()2-s2.0-85006765626 (Scopus ID)978-1-5090-2846-7 (ISBN)
Conference
8th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), AUG 18-21, 2016, San Francisco, CA
Note

QC 20170130

Available from: 2017-01-30 Created: 2017-01-23 Last updated: 2018-01-13Bibliographically approved
Ozyagci, O. Z. & Matskin, M. (2016). Truthful Incentive Mechanism for Mobile Crowdsensing with Smart Consumer Devices. In: Proceedings - International Computer Software and Applications Conference: . Paper presented at 2016 IEEE 40th Annual Computer Software and Applications Conference, COMPSAC 2016, 10 June 2016 through 14 June 2016 (pp. 282-287). IEEE Computer Society
Open this publication in new window or tab >>Truthful Incentive Mechanism for Mobile Crowdsensing with Smart Consumer Devices
2016 (English)In: Proceedings - International Computer Software and Applications Conference, IEEE Computer Society, 2016, p. 282-287Conference paper, Published paper (Refereed)
Abstract [en]

Smart consumer devices have become one of the fundamental communication and computing devices in people's everyday lives over the past decade. Their various sensors and wireless connectivity have paved the way for a new application area called mobile crowdsensing (MCS) where sensing services are provided by using the sensor outputs collected from smart consumer devices. MCS system's service quality heavily depends on the participation of smart device users who probably expect to be compensated in return for their participation. Therefore, MCS applications need incentive mechanisms to motivate such people into participating. In this work, we first defined a reverse auction based incentive mechanism for a representative MCS system. Then, we integrated the Vickrey-Clarke-Groves (VCG) mechanism into the initial incentive mechanism so that truthful bidding would become the dominant strategy in the resulting incentive mechanism. Finally, we conducted simulations of both incentive mechanisms in order to measure the fairness of service prices and the fairness of cumulative participant earnings using Jain's fairness index. We observed that both the fairness of service prices and the fairness of cumulative participant earnings were generally better in the derived incentive mechanism when the VCG mechanism was applicable. We also found that at least 70% of service requests had fair prices, while between 5% and 85% of participants had fair cumulative earnings in both incentive mechanisms.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016
Keywords
fairness, mobile crowdsensing, social network services for consumer devices, truthful incentive mechanism, Vickrey-Clarke-Groves mechanism, Computer software, Costs, Quality of service, Consumer devices, Incentive mechanism, Application programs
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-194938 (URN)10.1109/COMPSAC.2016.214 (DOI)000389532200042 ()2-s2.0-84987984846 (Scopus ID)9781467388450 (ISBN)
Conference
2016 IEEE 40th Annual Computer Software and Applications Conference, COMPSAC 2016, 10 June 2016 through 14 June 2016
Note

QC 20161124

Available from: 2016-11-24 Created: 2016-11-01 Last updated: 2017-01-23Bibliographically approved
Claycomb, W., Matskin, M. & Nakamura, M. (2015). Message from the Workshop Chairs - Part III. In: Proceedings - International Computer Software and Applications Conference: . Paper presented at 39th IEEE Annual Computer Software and Applications Conference Workshops, COMPSACW 2015; Taichung; Taiwan. IEEE Communications Society, 3
Open this publication in new window or tab >>Message from the Workshop Chairs - Part III
2015 (English)In: Proceedings - International Computer Software and Applications Conference, IEEE Communications Society, 2015, Vol. 3Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE Communications Society, 2015
National Category
Computer Sciences
Identifiers
urn:nbn:se:kth:diva-187109 (URN)10.1109/COMPSAC.2015.322 (DOI)2-s2.0-84962091477 (Scopus ID)
Conference
39th IEEE Annual Computer Software and Applications Conference Workshops, COMPSACW 2015; Taichung; Taiwan
Note

QC 20160519

Available from: 2016-05-19 Created: 2016-05-17 Last updated: 2018-01-10Bibliographically approved
Mrazovic, P. & Matskin, M. (2015). MobiCS: Mobile Platform for Combining Crowdsourcing and Participatory Sensing. In: : . Paper presented at Computer Software and Applications Conference (COMPSAC), 2015 IEEE 39th Annual (pp. 553-562). IEEE, 2
Open this publication in new window or tab >>MobiCS: Mobile Platform for Combining Crowdsourcing and Participatory Sensing
2015 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Current participatory sensing approaches usuallydo not consider device carriers as intelligent participants insensing processes. However, modern mobile communicationdevices allow users express their opinions and judgementswhich can complement to captured sensor data. In this paperwe bring together different modes of mobile crowdsourcinginto a general sensing platform which treats device carriersas intelligent problem solvers. We propose a conceptual archi-tecture for versatile context-aware mobile crowdsourcing, andaddress issues related to data representation, quality control,trust and reputation management, and task allocation. Toprove the potential advantages of the proposed conceptualarchitecture we developedMobiCS, a prototype platform whichallows crowdsourcers formulate and distribute both sensingand human intelligence tasks to Android-powered mobilecommunication devices.

Place, publisher, year, edition, pages
IEEE, 2015
Keywords
mobile crowdsourcing, participatory sensing, mobile crowd sensing
National Category
Communication Systems
Research subject
Information and Communication Technology
Identifiers
urn:nbn:se:kth:diva-183157 (URN)10.1109/COMPSAC.2015.26 (DOI)000380584300075 ()2-s2.0-84962142430 (Scopus ID)
Conference
Computer Software and Applications Conference (COMPSAC), 2015 IEEE 39th Annual
Note

QC 20160415

Available from: 2016-03-02 Created: 2016-03-02 Last updated: 2017-01-20Bibliographically approved
Dokoohaki, N., Zikou, F., Gillblad, D. & Matskin, M. (2015). Predicting Swedish Elections with Twitter: A Case for Stochastic Link Structure Analysis. In: PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015): . Paper presented at IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), AUG 25-28, 2015, Paris, FRANCE (pp. 1269-1276). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Predicting Swedish Elections with Twitter: A Case for Stochastic Link Structure Analysis
2015 (English)In: PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015), Association for Computing Machinery (ACM), 2015, p. 1269-1276Conference paper, Published paper (Refereed)
Abstract [en]

The question that whether Twitter data can be leveraged to forecast outcome of the elections has always been of great anticipation in the research community. Existing research focuses on leveraging content analysis for positivity or negativity analysis of the sentiments of opinions expressed. This is while, analysis of link structure features of social networks underlying the conversation involving politicians has been less looked. The intuition behind such study comes from the fact that density of conversations about parties along with their respective members, whether explicit or implicit, should reflect on their popularity. On the other hand, dynamism of interactions, can capture the inherent shift in popularity of accounts of politicians. Within this manuscript we present evidence of how a well-known link prediction algorithm, can reveal an authoritative structural link formation within which the popularity of the political accounts along with their neighbourhoods, shows strong correlation with the standing of electoral outcomes. As an evidence, the public time-lines of two electoral events from 2014 elections of Sweden on Twitter have been studied. By distinguishing between member and official party accounts, we report that even using a focus-crawled public dataset, structural link popularities bear strong statistical similarities with vote outcomes. In addition we report strong ranked dependence between standings of selected politicians and general election outcome, as well as for official party accounts and European election outcome.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2015
National Category
Political Science (excluding Public Administration Studies and Globalisation Studies)
Identifiers
urn:nbn:se:kth:diva-185414 (URN)10.1145/2808797.2808915 (DOI)000371793500194 ()2-s2.0-84962601806 (Scopus ID)978-1-4503-3854-7 (ISBN)
Conference
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), AUG 25-28, 2015, Paris, FRANCE
Projects
Networks
Note

QC 20160418

Available from: 2016-04-18 Created: 2016-04-18 Last updated: 2018-01-10Bibliographically approved
Mrazovic, P., Matskin, M. & Dokoohaki, N. (2015). Trajectory-Based Task Allocation for Reliable Mobile Crowd Sensing Systems. In: Proceedings - 15th IEEE International Conference on Data Mining Workshop: . Paper presented at 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015; Atlantic City; United States; 14 November 2015 through 17 November 2015 (pp. 398-406). Institute of Electrical and Electronics Engineers (IEEE), 1, Article ID 7395697.
Open this publication in new window or tab >>Trajectory-Based Task Allocation for Reliable Mobile Crowd Sensing Systems
2015 (English)In: Proceedings - 15th IEEE International Conference on Data Mining Workshop, Institute of Electrical and Electronics Engineers (IEEE), 2015, Vol. 1, p. 398-406, article id 7395697Conference paper, Published paper (Refereed)
Abstract [en]

Mobile crowd sensing (MCS) is as a promising people-centric sensing paradigm which allows ordinary citizens to contribute sensing data using mobile communication devices. In this paper we study correlation between users’ mobility and their role as contributors in MCS applications. We propose a new trajectory-based approach for task allocation in MCS environments and model participants’ spatio-temporal competences by analyzing their mobile traces. By allocating MCS tasks only to participant who are familiar with the target location we significantly increase the reliability of contributed data and reduce total communication cost. We introduce novel metric to estimate participants’ competence to conduct MCS tasks and propose fair ranking approach allowing newcomers to compete with experienced senior contributors. Additionally, we group similar expert contributors and thus open up new possibilities for physical collaboration between them. We evaluate our work using GeoLife trajectory dataset and the experimental results show the advantages of our approach.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2015
Keywords
mobile crowd sensing, mobile crowdsourcing, mobility profiling, participatory sensing, task allocation
National Category
Communication Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-188127 (URN)10.1109/ICDMW.2015.90 (DOI)000380556700054 ()2-s2.0-84964777811 (Scopus ID)978-1-4673-8492-6 (ISBN)
External cooperation:
Conference
15th IEEE International Conference on Data Mining Workshop, ICDMW 2015; Atlantic City; United States; 14 November 2015 through 17 November 2015
Note

QC 20160623

Available from: 2016-06-05 Created: 2016-06-05 Last updated: 2016-09-05Bibliographically approved
Mokarizadeh, S., Kungas, P. & Matskin, M. (2014). A framework for evaluating semantic annotations of Web services: A network theory based approach for measuring annotation quality. Web Intelligence and Agent Systems, 12(1), 15-34
Open this publication in new window or tab >>A framework for evaluating semantic annotations of Web services: A network theory based approach for measuring annotation quality
2014 (English)In: Web Intelligence and Agent Systems, ISSN 1570-1263, E-ISSN 1875-9289, Vol. 12, no 1, p. 15-34Article in journal (Refereed) Published
Abstract [en]

In the past years various methods have been developed which require semantic annotations of Web services as an input. Such methods typically leverage discovery, match-making, composition and execution of Web services in dynamic settings. At the same time a number of automated Web service annotation approaches have been proposed for enabling application of these methods in settings where it is not feasible to provide the annotations manually. However, lack of effective automated evaluation frameworks has seriously limited proper assessment of the constructed annotations in settings where the overall annotation quality of large quantities of Web services needs to be evaluated. This paper describes an evaluation framework for measuring the quality of semantic annotations for a large number of real-world Web services from heterogeneous application domains. The evaluation framework is generally based on analyzing properties of Web service networks constructed from semantic annotations of the Web services. More specifically, we measure scale-free, small-world and correlation degree properties of the networks to evaluate the overall quality of annotations. The evaluation is demonstrated using annotations constructed semi-automatically for a set of publicly available WSDL documents containing descriptions of about 200 000 Web service operations.

Keywords
Web service networks, semantic Web services, web service annotation, evaluation of annotation quality, network theory
National Category
Computer Systems
Identifiers
urn:nbn:se:kth:diva-160449 (URN)10.3233/WIA-140283 (DOI)2-s2.0-84897993325 (Scopus ID)
Note

QC 20150410

Available from: 2015-02-19 Created: 2015-02-19 Last updated: 2017-12-04Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-4722-0823

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