Text-based Semantic Annotation Service for Multimedia Content in the Esperonto project

Within the Esperonto project, an integration of NLP, ontologies and other knowledge bases, is being performed with the goal to implement a semantic annotation service that upgrades the actual Web towards the emerging Semantic Web. Research is being currently conducted on how to apply the Esperonto semantic annotation service to text material associated with still images in web pages. In doing so, the project will allow for semantic querying of still images in the web, but also (automatically) create a large set of text-based semantic annotations of still images, which can be used by the Multimedia community in order to support the task of content indexing of image material, possibly combining the Esperonto type of annotations with the annotations resulting from image analysis

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Contribution of NLP to the Content Indexing of Multimedia Documents

This paper describes the role natural language processing (NLP) can play for multimedia applications. As an example of such an application, we present an approach dealing with the conceptual indexing of soccer videos which the help of structured information automatically extracted by NLP tools from multiple sources of information relating to video content, consisting in a rich range of textual and transcribed sources covering soccer games. This work has been investigated and developed in the EU funded project MUMIS. As a second example of such an application, we describe briefly ongoing work in the context of the Esperonto project dealing with upgrading the actual web towards the Semantic Web (SW), including the automatic semantic indexing of web pages containing a combination of text and images

Contribution of NLP to the Content Indexing of Multimedia Documents

This paper describes the role natural language processing (NLP) can play for multimedia applications. As an example of such an application, we present an approach dealing with the conceptual indexing of soccer videos which the help of structured information automatically extracted by NLP tools from multiple sources of information relating to video content, consisting in a rich range of textual and transcribed sources covering soccer games. This work has been investigated and developed in the EU funded project MUMIS. As a second example of such an application, we describe briefly ongoing work in the context of the Esperonto project dealing with upgrading the actual web towards the Semantic Web (SW), including the automatic semantic indexing of web pages containing a combination of text and images