Map-Based Interaction with a Conversational Mobile Recommender System

Authors:
Olga Averjanova;Francesco Ricci;Quang Nhat Nguyen
Affiliations:
-;-;-
Venue:
UBICOMM '08 Proceedings of the 2008 The Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies
Year:
2008

Citing 0
Cited 5

An energy-efficient mobile recommender system

Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A web search-centric approach to recommender systems with URLs as minimal user contexts

Journal of Systems and Software
Technological and organizational determinants of information management in the urban space (based on scientific research)

Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Evaluating the impact of proactivity in the user experience of a context-aware restaurant recommender for Android smartphones

Journal of Systems Architecture: the EUROMICRO Journal
Review: Mobile recommender systems in tourism

Journal of Network and Computer Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recommender systems are information search and decision support tools used when there is an overwhelming set of options to consider or when the user lacks the domain-specific knowledge necessary to take autonomous decisions. They provide users with personalized recommendations adapted to their needs and preferences in a particular usage context. In this paper, we present an approach for integrating recommendation and electronic map technologies to build a map-based conversational mobile recommender system that can effectively and intuitively support users in finding their desired products and services. The results of our real-user study show that integrating map-based visualization and interaction in mobile recommender systems improves the system recommendation effectiveness and increases the user satisfaction.