What is happening now? entertainment

Abstract

Everyday people exchange data back and forth over the internet, describing their ongoing activities, their plans for the weekend and anything that comes to mind. Most data on the internet consists of unstructured text containing links to more structured information. To our knowledge, there is no automatic solution that identifies and extract entertainment events from multiple sources. Hence, the problem is finding a way we can use this data to extract useful information such as events.[1] In this research, we propose a solution for the automated detection and extraction of entertainment events, and the representation of these features in a structured format. The method proposed is divided in a number of steps: firstly, through supervised event classification the system finds out whether the data retrieved from various RSS feeds (e.g local press news sites) is an entertainment event or not. Secondly, the system annotates the documents that are classified to be entertainment events using different NERs included in GATE[2] pipelines to extract named entities (such as Event Date, Location, Participants and Organisations Involved). Moreover, we eliminate ambiguous dates and solve temporal expressions on these extracted event details. Furthermore, this event data is compared to previously extracted events and information aggregation is performed. Information aggregation is the coalescing of event data from multiple news reports detected to be referring to the same event. Finally, these event details need to be represented. For extensibility of the system the use of RDF model has been employed to represent these events in a semantic way. We even showcased an RDF API that allows others to perform free text searches on the entertainment events extracted by the system. In addition to this, we stored these entertainment events in database tuples to utilise such information for the web interface (front end UI). In this web interface we provide a way to search for entertainment events by their details using our simple RESTful API. In this prototype, we mainly focused on the detection and extraction of entertainment events in Malta. Nevertheless, such a system can be extended to retrieve and extract entertainment events for other countries. The results obtained based on our evaluation were very promising.