Folksonomy-based Indexing for Location-aware Retrieval of Learning Contents
(0) With the fast development of wirelesscommunication and sensor technologies, ubiquitouslearning has become a promising learning paradigm.In context-aware ubiquitous learning environments, itis desirable that learning content is retrievedaccording to environmental contexts, such as learners location. However, traditional information retrievalschemes are not designed for content retrieval inubiquitous learning environments. Recently,folksonomies have emerged as a successful kind ofapplications for categorizing web resources in acollaborative manner. This paper focuses on the indexcreation problem for location-aware learning contentretrieval. First, we propose a bottom-up approach toconstructing the index according to the similaritybetween tags, which considers metadata and structuralinformation of the teaching materials annotated by the tags. Then, a maintenance mechanism is designed toefficiently update the index. The index creation methodhas been implemented, and a synthetic learning objectrepository has been built to evaluate the proposedapproach. Experimental results show that this methodcan increase precision of retrieval. In addition,impacts of different similarity functions on precisionare discussed.
Folksonomy Location-aware Information retrieval Ubiquitous learning
Wen-Chung Shih Shian-Shyong Tseng
Department of Computer Science Chiao Tung University,Hsinchu,30010,Taiwan Department of Computer Science Chiao Tung University,Hsinchu,30010,Taiwan;Department of Information
国际会议
北京
英文
143-147
2008-03-01（万方平台首次上网日期，不代表论文的发表时间）