Publications -> Conference Papers

Progressive Sequence Matching for ADL Plan Recommendation


Authors: S. Gao, D. Wang, A.-H. Tan, and C. Miao
Title: Progressive Sequence Matching for ADL Plan Recommendation
Abstract: Activities of Daily Living (ADLs) are indicatives of a person’s lifestyle. In particular, daily ADL routines closely relate to a person’s well-being. With the objective of promoting active lifestyles, this paper presents an agent system that provides recommendations of suitable ADL plans (i.e., selected ADL sequences) to individual users based on the more active lifestyles of the others. Specifically, we develop a set of quantitative measures, named wellness scores, spanning the evaluation across the physical, cognitive, emotion, and social aspects based on his or her ADL routines. Then we propose an ADL sequence learning model, named Recommendation ADL ART, or RADLART, which proactively recommends healthier choices of activities based on the learnt associations among the user profiles, ADL sequence, and wellness scores. For empirical evaluation, extensive simulations have been conducted to assess the improvement in wellness scores for synthetic users with different acceptance rates of the provided recommendations. Experiments on real users further show that recommendations given by RADLART are generally more acceptable by the users because it takes into considerations of both the user profiles and the performed activities.
Keywords: 
Conference Name: 2015 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology (WI-IAT'15)
Location: Singapore, Singapore
Publisher: IEEE
Year: 2015
Accepted PDF File: Progressive_Sequence_Matching_for_ADL_Plan_Recommendation_accepted.pdf
Permanent Link: http://dx.doi.org/10.1109/WI-IAT.2015.171
Reference: S. Gao, D. Wang, A.-H. Tan, and C. Miao, “Progressive sequence matching for ADL plan recommendation,” in Proceedings of the 2015 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology (WI-IAT’15). IEEE, December 2015, accepted for publication.
bibtex: 
@inproceedings{LILY-c63, 
    author	= {Gao, Shan and Wang, Di and Tan, Ah-Hwee and Miao, Chunyan},
    title	= {Progressive Sequence Matching for {ADL} Plan Recommendation},  
    booktitle	= {Proceedings of the 2015 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology (WI-IAT'15)}, 
    year		= {2015}, 
    month	= {December}, 
    pages	= {360-367}, 
    location	= {Singapore, Singapore},
    publisher	= {IEEE},
 }