کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
401061 1439079 2006 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The frequent wayfinding-sequence (FWS) methodology: Finding preferred routes in complex virtual environments
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
The frequent wayfinding-sequence (FWS) methodology: Finding preferred routes in complex virtual environments
چکیده انگلیسی

Advances in computing techniques, as well as the reduction in the cost of technology, have made possible the viability and spread of complex virtual environments (VEs). However, efficient navigation within these environments remains problematic for the user. Several research projects have shown that users of VEs are often disoriented and have extreme difficulty completing navigational tasks. Furthermore, there is often more than one route to get to a specified destination. Novice users often lack the spatial knowledge needed to pick an appropriate route due to the deficiency of experience with the system. A number of navigation tools such as maps, 3-D thumbnails, trails, and personal agents have been proposed. The introduction of these tools have met with some degree of success, but most researchers agree that new techniques need to be developed to aid users efficiently navigate within complex VEs. In this paper, we propose the frequent wayfinding-sequence (FWS) methodology that uses a modified sequence mining technique to discover a model of routes taken by experienced users of a VE. The model is used to build an interface that provides navigation assistance to novice users by recommending routes. We conducted both real world and simulation experiments using our methodology. Results from the real world experiment suggest that the FWS approach has the potential to improve the user's navigation performance and the quality of the human-computer interaction. Our simulation studies showed that our approach is scalable, efficient, and able to find useful route models for complex VEs.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Human-Computer Studies - Volume 64, Issue 4, April 2006, Pages 356–374
نویسندگان
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