Demographic recommendations for WEITBLICK, an assistance system for elderly

Stiller, Carsten; Roß, Fred; Ament, Christoph

doi:10.1109/iscit.2010.5664874

Cited by 7 publications

(6 citation statements)

References 11 publications

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“…For example, [30] proposed a contextaware-based location recommender system that can monitor the location of the elderly and deliver appropriate location recommendations by considering context. On the other hand, Stiller et al [31] used demographic attributes in order to provide personalised information about available services in the surroundings of elderly users, while Kitamura et al [32] proposed a system for recommending social services to elderly by classifying social services and subjective experiences among the elderly using the World Health Organization's (WHO) International Classification of Functioning, Disability and Health (ICF) [33].…”

Section: Related Workmentioning

confidence: 99%

A hybrid matchmaking approach in the ambient assisted living domain

Stavrotheodoros

Kaklanis

Votis

et al. 2021

Univ Access Inf Soc

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During the recent years, several new Information and Communication Technology solutions have been developed in order to meet the increasing needs of elderly with cognitive impairments and support their autonomous living. Most of these solutions follow a human-centred paradigm that aims to provide users with personalised services according to their needs by also ensuring their safety with mechanisms that can automatically trigger appropriate actions in situations where there may be a risk for an elderly. The present paper presents a hybrid matchmaking approach that uses efficiently both a rule-based and a statistical matchmaker in order to (a) propose ambient assisted living services to the end-users, based on their role, status and context of use and (b) identify and resolve problematic cases by automatically selecting the most proper set of services to be called in a single or combined manner.

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Section: Related Workmentioning

confidence: 99%

A hybrid matchmaking approach in the ambient assisted living domain

Stavrotheodoros

Kaklanis

Votis

et al. 2021

Univ Access Inf Soc

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“…Another proposed intervention recommendation approach was focused on a demographic recommender system for the elderly [15]. This recommender system focused on the demographic aspect to provide elderly with information about services of health, recreation, household, etc.…”

Section: A Related Workmentioning

confidence: 99%

“…The weightage was collected from the experts of each aspect in order to calculate the overall condition of the elderly. The weightages for each aspect are as follows: socialization (10), health (30), cognitive (15), physical (15), nutrition (10), spiritual (10) and environment (10). Below is the formula to calculate the weightage for each aspect based on the assessment data collected from the elderly.…”

Section: A User Profilingmentioning

confidence: 99%

A Collaborative Filtering Recommender System Model for Recommending Intervention to Improve Elderly Well-being

Azmi¹,

Abdullah²,

Akmar³

2019

IJACSA

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In improving elderly well-being nowadays, people at home or health care centre are mostly focusing on guarding and monitoring the elderly using tools, such as CCTV, robots, and other appliances that require a great deal of cost and neat fixtures to prevent damage. Elderly observations using the recommender system are found to be implemented, but only focusing on one aspect such as nutrition and health. However, it is important to give interventions to an elderly by concentrating more on the multiple aspects of successful ageing such as social, environment, health, physical, mental and other so that it can help the elderly people in achieving successful ageing as well as improving their well-being. In this paper, two recommender system models are proposed to recommend interventions for improving elderly well-being in the multiple aspects of successful ageing. These models using a Collaborative Filtering (CF) technique to recommend interventions to an elderly based on the interventions given to other elderly who have similar conditions with the user. The process of recommending interventions involves the generation of user profiles presenting the elderly conditions in multiple aspects of successful ageing. It also applying the k-Nearest Neighbor (kNN) method to find users with similar conditions and recommending interventions based on the interventions given to the similar user. The experiment is conducted to determine the performance of the proposed Collaborative Filtering (CF) recommender system and Collaborative Filtering and Profile Matching (CFS) compared to the Basic Search (BS). The results of the experiment showed that Collaborative Filtering (CF) recommender system and Collaborative Filtering and Profile Matching (CFS) outperformed Basic Search (BS) in terms of precision, recall and F1 measure. This result showed that the proposed models are efficient to recommend interventions using elderly profiles based on many aspects of successful ageing.

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“…Generally, the recommendation method [5][6][7][8] of the data mining [4] consists of the followings: content-based method, demographic method, and collaborative filtering method. Content-based method is word frequency method.…”

Section: Related Workmentioning

confidence: 99%

“…Most of recommended systems are based on content-based (CB), or collaborative filtering (CF) algorithm. The latter is more commonly used, which creates recommended results based on the preference similarity between the users [6,10,12,14].…”

Section: Introductionmentioning

confidence: 99%

Mobile Application Curation Service based on Big Data Platform

Hee¹,

Shim²,

Hwang³

et al. 2018

IJGDC

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Popularization of smartphone allows many people to be able to share information, and easily get information they want. And then, app store of smartphone plays an important role to make users get information and make transactions they want easily. With the increase of the number of apps traded at the app store, it is difficult for users to find appropriate apps they want. Commonly, app store recommends apps users want through key words posted by users. But, this method has limits, and may not be satisfactory to users. This paper proposes a method where app store recommends apps to users by classifying apps used by users' friends by category and degree of satisfaction and recommending apps which are likely to be used. The experiment to test satisfaction of users showed that the method proposed in this paper increased the degree of satisfaction of users by over 21%.

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Demographic recommendations for WEITBLICK, an assistance system for elderly

Cited by 7 publications

References 11 publications

A hybrid matchmaking approach in the ambient assisted living domain

A hybrid matchmaking approach in the ambient assisted living domain

A Collaborative Filtering Recommender System Model for Recommending Intervention to Improve Elderly Well-being

Mobile Application Curation Service based on Big Data Platform

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