A High Level Model for Developing Intelligent Visual Travel Recommender Systems
A High Level Model for Developing Intelligent Visual Travel Recommender Systems
复制标题
开发智能视觉旅游推荐系统的高级模型
DOI:
10.1007/978-3-211-69566-1_4
复制
发表时间:
2007
期刊:
影响因子:
--
通讯作者:
N. Sharda
中科院分区:
文献类型:
--
作者:
Mohan Ponnada;N. Sharda
This paper presents the model of an Intelligent Visual Travel Recommender system (IV-TRS). IV-TRS is a system that makes use of visual information such as images and video, along with audio, to present a virtual tour of the destination. The IV-TRS model is divided into three layers, namely Augmented Web, Application and Intelligence layers. The IV-TRS makes use of the TRIPS (Tour Recommendation using Image-Based Planning with SCORM) concept to bring together relevant tourism data stored in the form of Sharable Content Objects (SCOs). The Augmented Web Layer consists of data stored as SCO’s built on the SCORM standard with their location is resolved by CORDRA. SCORM (Shamble Content Object Reference Model) is a model that defines how information is to be stored, referenced and used by packaging data with metadata. CORDRA (Content Object Repository Discovery and Registration/Resolution Architecture) is a model that aims to locate and reference SCORM repositories over the web. The Intelligence Layer provides the reasoning engine of the system, and can be built on Semantic Web technology, Expert Systems technology, or Artificial Neural Networks. For this research, we focus on the Semantic Web technology for building the Intelligence Layer. The Application layer is made up of two components; namely, Search and Presentation. The Search component makes use of the CORDRA functionality to crawl and index the SCO’s on the Internet. The Presentation component aims to provide a user interface that lets the user customize the presentation based on personal preferences. The IV-TRS system will provide the user a virtual experience to support better destination selection, and tour planning.