Intelligent HTMLtoVXML Conversion using Automatic Object Extraction and Prior Structural Knowledge

This paper is a presentation a new intelligent agent which converts HTML contents to VXML contents for voice services via Web. In this paper, I propose an interactive hybrid sequential contents selection method to select desired contents fast and robustly from known Web pages. It uses real time structural features as well as included text and/or prior structural knowledge such as link symbol position. To verify its effectiveness, a full agent system is implemented and tested for Korean Web sites. The method reflects user intention more accurately than conventional selections using structural features and is more robust to variations of HTML programming techniques. The agent is fast and has less of computational burden than methods using conventional XML or XHTML conversion as intermediate stage