Towards BOTTARI: using stream reasoning to make sense of location-based micro-posts

Authors:
Irene Celino;Yi Huang;Tony Lee;Seon-Ho Kim;Volker Tresp
Affiliations:
CEFRIEL --- ICT Institute, Politecnico of Milano, Milano, Italy;Corporate Technology, SIEMENS AG, Muenchen, Germany;Saltlux, Seoul, Korea;Saltlux, Seoul, Korea;Corporate Technology, SIEMENS AG, Muenchen, Germany
Venue:
ESWC'11 Proceedings of the 8th international conference on The Semantic Web
Year:
2011

Citing 6
Cited 1

Data Stream Management: Processing High-Speed Data Streams (Data-Centric Systems and Applications)

Data Stream Management: Processing High-Speed Data Streams (Data-Centric Systems and Applications)
Towards LarKC: A Platform for Web-Scale Reasoning

ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
It's a Streaming World! Reasoning upon Rapidly Changing Information

IEEE Intelligent Systems
Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics

IEEE Intelligent Systems
Large knowledge collider: a service-oriented platform for large-scale semantic reasoning

Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Incremental reasoning on streams and rich background knowledge

ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I

BOTTARI: An augmented reality mobile application to deliver personalized and location-based recommendations by continuous analysis of social media streams

Web Semantics: Science, Services and Agents on the World Wide Web

Quantified Score

Hi-index	0.00

Visualization

Abstract

Consider an urban environment and its semi-public realms (e.g., shops, bars, visitors attractions, means of transportation). Who is the maven of a district? How fast and how broad can such maven influence the opinions of others? These are just few of the questions BOTTARI (our Location-based Social Media Analysis mobile app) is getting ready to answer. In this position paper, we recap our investigation on deductive and inductive stream reasoning for social media analysis, and we show how the results of this research form the underpinning of BOTTARI.