Selecting the most suitable classification algorithm for supporting assistive technology adoption for people with dementia: A multicriteria framework

The number of people with dementia (PwD) is increasing dramatically. PwD exhibit impairments of reasoning, memory, and thought that require some form of self‐management intervention to support the completion of everyday activities while maintaining a level of independence. To address this need, efforts have been directed to the development of assistive technology solutions, which may provide an opportunity to alleviate the burden faced by the PwD and their carers. Nevertheless, uptake of such solutions has been limited. It is therefore necessary to use classifiers to discriminate between adopters and nonadopters of these technologies in order to avoid cost overruns and potential negative effects on quality of life. As multiple classification algorithms have been developed, choosing the most suitable classifier has become a critical step in technology adoption. To select the most appropriate classifier, a set of criteria from various domains need to be taken into account by decision makers. In addition, it is crucial to define the most appropriate multicriteria decision‐making approach for the modelling of technology adoption. Considering the above‐mentioned aspects, this paper presents the integration of a five‐phase methodology based on the Fuzzy Analytic Hierarchy Process and the Technique for Order of Preference by Similarity to Ideal Solution to determine the most suitable classifier for supporting assistive technology adoption studies. Fuzzy Analytic Hierarchy Process is used to determine the relative weights of criteria and subcriteria under uncertainty and Technique for Order of Preference by Similarity to Ideal Solution is applied to rank the classifier alternatives. A case study considering a mobile‐based self‐management and reminding solution for PwD is described to validate the proposed approach. The results revealed that the best classifier was k‐nearest‐neighbour with a closeness coefficient of 0.804, and the most important criterion when selecting classifiers is scalability. The paper also discusses the strengths and weaknesses of each algorithm that should be addressed in future research

Determinants of online shopping among tertiary students in Ghana: An extended technology acceptance model

The increasing penetration rate of the internet and technology in the world is quickly promoting online shopping. This has been fueled by growing innovations in the telecommunication and financial sector in an attempt to depeen financial inclusion. Innovations such as mobile money payments systems by mobile telephony companies have contributed to the continuous growth in online shopping amidst and the new generation of consumers who desire richer experiences. This study sought to identify the determinants of online shopping behaviour among tertiary students through the lens of the Technology Acceptance Model (TAM). The study proposed a revised TAM that integrated perceived cost and perceived risk to investigate what determined students online shopping intention and actual use. The survey involved a sample of 580 undergraduate students. The statistical technique used was Structural Equation Modelling-Partial Least Squares (SEM-PLS). The results showed that effect of ease of use on usefulness was very significant as same has been predicted by the Technology Acceptance Model. Among the independent variables, perceived cost (PC) was found to be the most significant factor affecting actual use (AU) of online shopping among students, nonetheless, perceived cost (PC) had no significant effect on purchase intention (PI). Perceived risk (PR) had no significant effect on actual use (AU) however, had a significant effect on purchase intention (PI). The study recommends online sellers to make online shopping efficient and less costive with assured safety and security of transactions as well as the product itself. A set of shopping platform could even be created specifically to give discounts and other offers to students. It also recommends future studies to employ additional determining factors such as the type of product/service, convenience and personal/demographic and geographic factors as influential to students’ online purchasing behaviour. © 2019, © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license

Y.: Challenges Faced by Ontology Matching Techniques: Case Study of the OAEI Datasets

Abstract: The aim of this study is to review some of the most successful recent techniques in ontology matching and to lay down pending challenges that need to be addressed in this area. Ontologies are essential for the realization of the semantic web, which in turn relies on the ability of systems to identify and exploit relationships that exist between and within ontologies. As ontologies can be used to represent different domains, there is a high need for efficient ontology matching techniques that can allow information to be easily shared between different heterogeneous systems. In this paper, six systems that obtained overall good performance in the Ontology Alignment Evaluation Initiative (OAEI) for the year 2008 and the year 2009 are analyzed based on their underlying techniques, datasets, and matching results. According to the analysis carried out, it is found that although some systems work well for dataset representing a given domain, the same system does not perform well for datasets representing other domains. To assist further research in this area, techniques that work well for particular domains are highlighted and areas for cross-domain ontology matching that still require attention are discussed with recommendations based on lessons learnt from the techniques described

Interoperable Metadata Framework to facilitate Retrieval of Educational Resources from the Internet

The Internet is in doubt the largest network ever with a large collection of useful resources. Major related concern however lies in how to store, organize and retrieve information from this ever growing network. This paper focuses exclusively on educational resources available on the Internet, highlighting the main limitations faced by users in actually getting access and retrieving information they desire. Information search process over the Internet is explained and use of controlled Meta data for efficient retrieval over the Internet is presented. Semantic interoperability as a key issue is also discussed in this paper