BACKGROUND
E-commerce sites nowadays expose variable degrees of sophistication, functionality, and complexity. Most ecommerce sites offer lists of available products, usually organized in categories. For each product, a brief description, the price, and possibly an image are made available to e-customers; more information items may be included depending on the e-commerce domain (e.g., customer reviews for books and music). A basic e-commerce site offers the same content to all its visitors.
The first step towards offering services tailored to the user needs is the categorization of users into groups and serving each group with specifically selected content (e.g., Arlitt, Krishnamurthy, & Rolia, 2001). Personalization provides a finer granularity for tailored content delivery, because content formulation is based on the preferences and behavior of individual users, rather than aggregate data from user groups. Preferences may be declared through static profiling (Datta, Dutta, VanderMeer, Ramamritham, & Navathe, 2001) where users declare their preferences through profile definition pages; dynamic profiles extend their static counterparts by incorporating information collected from user activities during the interaction sessions.
On the other hand, 3D objects and VR can greatly enhance user experience within an electronic shop. Since 3D environments are inherently more complex as compared to 2D interfaces, the issue of navigation within such an environment is important. Chittaro and Coppola (2000) discuss the use of animated products as a navigation aid for e-commerce. Hughes et al. (2002) examine the integration of ideal viewing parameters with navigation, to assist the navigation procedure. Park and Woohun (2004) present a prototype augmented reality system, enabling users to “put and feel a product” in order to find the match in the real environment.
Although adaptation and VR technologies seem promising for e-commerce, their adoption is currently hindered due to a number of challenges, mainly related to the technologies themselves. The first major challenge is content creation: for each item in the VR-mall, the respective representations have to be created. The virtual space for the mall must also be designed, and stands and shelves on which items will be placed must be inserted. Finally, interaction methods for each item need to be designed.
These may vary from item to item depending on the type of digital representations (e.g., 3D models may be rotated; videos may be played, paused, and continued; photographs may be only viewed), and the nature and semantics of the item (e.g., for a 3D model of a camera, interaction may be provided to illustrate change of lenses, while a 3D model of a vase can be only rotated). This is a cumbersome, time consuming, and costly process (Lepouras, Charitos, Vassilakis, Charissi, & Halatsi, 2001).
A second major challenge is the overall system complexity, stemming from the diversity of its components, structures, and interactions (European Center for Virtual Reality, 2004). The system must include provisions for user profile modeling (both static and dynamic parts), selection of the items that best fit the current user profile, dynamic creation of virtual worlds (VR-worlds) in which the selected items must be placed, coupled with proper interaction methods.
A final challenge is the overall size of the VR-mall description. VR-worlds tend to be of large size, and thus their download time can be considerable. Constructing thus a single world representing the whole VR-mall will result in long waiting times, which may lead users to navigate away from the VR-mall. A more prominent approach would be the formulation of smaller VR-worlds, each one containing a subset of the VR-mall merchandise.
These worlds may be interconnected using gates, teleports, or any other suitable means (when a user reaches an interconnection item, they are transferred to another VR-world constructed and downloaded at that time; thus waiting times are broken down into small portions). The proposed architecture adopts this approach, which additionally provides the opportunity to populate each VRworld with the merchandise that best fits the user interests, as this can be determined by the user activities observed so far. The details of this process are analyzed in the next section.
The first step towards offering services tailored to the user needs is the categorization of users into groups and serving each group with specifically selected content (e.g., Arlitt, Krishnamurthy, & Rolia, 2001). Personalization provides a finer granularity for tailored content delivery, because content formulation is based on the preferences and behavior of individual users, rather than aggregate data from user groups. Preferences may be declared through static profiling (Datta, Dutta, VanderMeer, Ramamritham, & Navathe, 2001) where users declare their preferences through profile definition pages; dynamic profiles extend their static counterparts by incorporating information collected from user activities during the interaction sessions.
On the other hand, 3D objects and VR can greatly enhance user experience within an electronic shop. Since 3D environments are inherently more complex as compared to 2D interfaces, the issue of navigation within such an environment is important. Chittaro and Coppola (2000) discuss the use of animated products as a navigation aid for e-commerce. Hughes et al. (2002) examine the integration of ideal viewing parameters with navigation, to assist the navigation procedure. Park and Woohun (2004) present a prototype augmented reality system, enabling users to “put and feel a product” in order to find the match in the real environment.
Although adaptation and VR technologies seem promising for e-commerce, their adoption is currently hindered due to a number of challenges, mainly related to the technologies themselves. The first major challenge is content creation: for each item in the VR-mall, the respective representations have to be created. The virtual space for the mall must also be designed, and stands and shelves on which items will be placed must be inserted. Finally, interaction methods for each item need to be designed.
These may vary from item to item depending on the type of digital representations (e.g., 3D models may be rotated; videos may be played, paused, and continued; photographs may be only viewed), and the nature and semantics of the item (e.g., for a 3D model of a camera, interaction may be provided to illustrate change of lenses, while a 3D model of a vase can be only rotated). This is a cumbersome, time consuming, and costly process (Lepouras, Charitos, Vassilakis, Charissi, & Halatsi, 2001).
A second major challenge is the overall system complexity, stemming from the diversity of its components, structures, and interactions (European Center for Virtual Reality, 2004). The system must include provisions for user profile modeling (both static and dynamic parts), selection of the items that best fit the current user profile, dynamic creation of virtual worlds (VR-worlds) in which the selected items must be placed, coupled with proper interaction methods.
A final challenge is the overall size of the VR-mall description. VR-worlds tend to be of large size, and thus their download time can be considerable. Constructing thus a single world representing the whole VR-mall will result in long waiting times, which may lead users to navigate away from the VR-mall. A more prominent approach would be the formulation of smaller VR-worlds, each one containing a subset of the VR-mall merchandise.
These worlds may be interconnected using gates, teleports, or any other suitable means (when a user reaches an interconnection item, they are transferred to another VR-world constructed and downloaded at that time; thus waiting times are broken down into small portions). The proposed architecture adopts this approach, which additionally provides the opportunity to populate each VRworld with the merchandise that best fits the user interests, as this can be determined by the user activities observed so far. The details of this process are analyzed in the next section.
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