Context and Intention-Awareness in POIs Recommender Systems
Authors
Abstract
This paper describes an agent-based approach for making context and intention-aware recommendations of Points of Interest (POI).A two-parted agent architecture was used, with an agent responsible for gathering POIs from a location-based mobile application, and a set of Personal Assistant Agents (PAA), collecting information about the context and intentions of its respective user.
Each PAA includes a probabilistic classifier for making recommendations given its information about the user's context and intentions.
Supervised, incremental learning occurs when the feedback of the true relevance of each recommendation is given by the user to his PAA.
To evaluate the system's recommendations, we performed an experiment based on the profile used in the training process, using different locations, contexts and goals.
Keywords
Context, Information Overload, Machine Learning, Personal Assistant Agents, Points of Interest Recommendation.Subject
Recommender SystemsRelated Project
Forms of Selective Attention in Intelligent Transportation SystemsConference
6th ACM Conference on Recommender Systems (RecSys 2012), 4th Workshop on Context-Aware Recommender Systems, (CARS 2012) Dublin, Ireland. ACM, September 2012Cited by
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