Enriching news for supporting users’ information needs using schema-driven classification of entities and relations
The LinkedTV project News scenario aims at improving the experience of watching news on TV. It envisages that potential users of the system watch news broadcasts, express a need for additional information and that the system provides resources from the web that are potentially relevant to them. Our goal was to investigate user information needs for a given news topic, based on news video fragments. Furthermore, we aimed at representing the news video fragment and related information needs in a form compatible with the system knowledge representation model. Our contribution consisted of a method to formally represent fragments and requirements using a controlled vocabulary, which was applied to information needs collected through a user study. The analysis resulted in lists of concepts and schemas of the content structure. This contribution supports semantic linking between news, related information needs and additional resources to be retrieved from the web to satisfy those needs.