Social Event Detection–A Systematic Approach using Ontology and Linked Open Data with Significance to Semantic Links

Sheba Selvam, Ramadoss Balakrishnan, and Balasundaram Ramakrishnan

Department of Computer Applications, National Institute of Technology Tiruchirappalli, India

Abstract: With the growing interest in capturing daily activities and sharing it through social media sites, enormous amount of multimedia content such as photographs, videos, texts, audio are made available on the web. Retrieval of multimedia content has now become a trivial task. Generally, people show interest in sharing photographs to a well-known closed community through social media sites like Flickr and Facebook. One solution to retrieve photographs is by identifying them as events. This task is known as Social Event Detection (SED). From the Flickr website, with the use of metadata like photoID, title, tags, description, date, time and geo-location for each photograph, the SED task is performed. As a central piece of the SED task, ontology for events domain is implemented. First half of the work is an explicit knowledge representation by constructing ontology for event detection using Protégé. Then, reasoning is done through HermiT reasoner and later SPARQL query is done to retrieve the media representing each event. The second half of the work involves in linking open description of specific events from different web services like Eventful, Last.fm, Foursquare, Upcoming and GeoNames. SPARQL query is done to measure the retrieval performance of each event after making semantic link using Linked Open Data (LOD). Finally an additional feature, the weather information for events is added, which shows removal of false positives in the SED task.

Keywords: Multimedia, social media, social events, photographs, event detection, ontology, linked open data, contextual metadata.