Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
While traditional recommender systems focus on single items, there is an emerging demand for package recommenders that can suggest composite items based on multiple criteria. For instance, they can recommend a combination of dishes based on price, cuisine, and dietary restrictions. Several challenges arise when dealing with package recommenders, including the complexity of the decision-making process and the need of handling trade-offs among conflicting objectives. We introduce OptiGuide, a domain-independent package recommender system that uses efficient multi-objective optimization techniques to guide users effectively in finding their Pareto-optimal recommendations. The user is engaged in the decision-making by capturing their user-system interactions and offering customization options to help them find their optimal recommendation. The system employs preprocessing algorithms to balance the need for quick response times with the computational complexity of the optimization process. A dynamic configuration mechanism is adopted using a pluggable analytic model to enable system versatility across diverse domains.
Recommended Citation
Almanie, Tahani and Brodsky, Alexander, "OptiGuide: An Efficient Domain-Independent Package Recommender System Based on Multi-Objective Optimization and User Decision Guidance" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 6.
https://aisel.aisnet.org/hicss-57/da/service_analytics/6
OptiGuide: An Efficient Domain-Independent Package Recommender System Based on Multi-Objective Optimization and User Decision Guidance
Hilton Hawaiian Village, Honolulu, Hawaii
While traditional recommender systems focus on single items, there is an emerging demand for package recommenders that can suggest composite items based on multiple criteria. For instance, they can recommend a combination of dishes based on price, cuisine, and dietary restrictions. Several challenges arise when dealing with package recommenders, including the complexity of the decision-making process and the need of handling trade-offs among conflicting objectives. We introduce OptiGuide, a domain-independent package recommender system that uses efficient multi-objective optimization techniques to guide users effectively in finding their Pareto-optimal recommendations. The user is engaged in the decision-making by capturing their user-system interactions and offering customization options to help them find their optimal recommendation. The system employs preprocessing algorithms to balance the need for quick response times with the computational complexity of the optimization process. A dynamic configuration mechanism is adopted using a pluggable analytic model to enable system versatility across diverse domains.
https://aisel.aisnet.org/hicss-57/da/service_analytics/6