Building Context-Aware Customized Stories Based on Uncovering Indirect Associations from Semantic Knowledge Bases

This paper describes the construction of an intelligent semantics-based system that exploits several knowledge bases to tell contextually relevant stories to individuals and groups. Starting from information stored in user profiles, textual queries and pictures, a set of readily available tools recognize topics of interest and features of context, thereupon, we run data mining and semantic reasoning processes to create the narratives and realize them using proper multimedia contents. User feedback is sought to enrich the knowledge bases in a sustainable and organic way.

[1]  Mihai Surdeanu,et al.  The Stanford CoreNLP Natural Language Processing Toolkit , 2014, ACL.

[2]  Okba Kazar,et al.  An improved semantic information searching scheme based multi-agent system and an innovative similarity measure , 2013, Int. J. Metadata Semant. Ontologies.

[3]  Magalie Ochs,et al.  From socio-emotional scenarios to expressive virtual narrators , 2011, 2011 IEEE Workshop on Affective Computational Intelligence (WACI).

[4]  Vincenzo Lombardo,et al.  Storytelling on mobile devices for cultural heritage , 2012, New Rev. Hypermedia Multim..

[5]  Matteo Gaeta,et al.  RST-Based Methodology to Enrich the Design of Digital Storytelling , 2014, 2014 International Conference on Intelligent Networking and Collaborative Systems.

[6]  Trevor Darrell,et al.  Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.

[7]  Alan Bundy,et al.  Reasoning with Context in the Semantic Web , 2012, J. Web Semant..

[8]  Jens Lehmann,et al.  DBpedia - A large-scale, multilingual knowledge base extracted from Wikipedia , 2015, Semantic Web.

[9]  Ian H. Witten,et al.  An open-source toolkit for mining Wikipedia , 2013, Artif. Intell..