Affiliations: [a] Graduate School of Culture, Chonnam National University, Gwangju, Korea. E-mail: [email protected] | [b] Division of Computer Engineering, Hanshin University, Gyeonggi-do, Osan-si, Korea. E-mail: [email protected]
Abstract: People spend their leisure time on cultural and historical stories by visiting exhibitions and museums with family members and friends. This small gathering establishes a voluntary platform to engage in activities and share experiential knowledge. Since members of a small group tend to have diverse preferences, both individual and group preferences should be considered for a cohesive and harmonious guide. This paper proposes a mixed-initiative tour path planning system for multiple visitors that builds a group path supported by automatic path generation and users’ participation. In the proposed system, individual user profiles are merged into a group profile by favoring multiple users’ higher preferences with low deviation. Then the system constructs a tour path based on mixed-initiative interaction that consists of the system’s automatic decision and participation of members. When group members have similar preferences, a tour path is automatically decided by the system. If group members have different and divergent preferences, the system asks group members to intervene and confirm appropriate places to collaboratively construct a tour path. To show feasibility of our proposed system, we evaluate our approach in twofold consists of a synthesized group simulation and a user study. For the simulation, we collected user preferences of 12 real users to simulate groups of two, three, and four members and explored characteristics of similar and different preference scenarios. For the user study, we conducted a comparative study with 11 participants under 4 different exhibition scenarios using the implemented mixed-initiative path planning system. Evaluation results support that our system constructs a cohesive, satisfying and usable path for a small group tour.
Keywords: Collaborative tools, human computer interaction, path planning, recommender systems, cultural enrichment
