Context-aware knowledge-based middleware for selective information delivery in data-intensive monitoring systems

In this article, we propose (1) a knowledge-based probabilistic collaborative filtering (CF) recommendation approach using both an ontology-based semantic similarity metric and a latent Dirichlet allocation (LDA) model-based recommendation technique and (2) a context-aware software architecture and system with the objective of validating the recommendation approach in the eating domain (foodservice places). The ontology on which the similarity metric is based is additionally leveraged to model and reason about users’ contexts; the proposed LDA model also guides the users’ context modelling to some extent. An evaluation method in the form of a comparative analysis based on traditional information retrieval (IR) metrics and a reference ranking-based evaluation metric (correctly ranked places) is presented towards the end of this article to reliably assess the efficacy and effectiveness of our recommendation approach, along with its utility from the user’s perspective. Our recommendation approach achieves higher average precision and recall values (8% and 7.40%, respectively) in the best-case scenario when compared with a CF approach that employs a baseline similarity metric. In addition, when compared with a partial implementation that does not consider users’ preferences for topics, the comprehensive implementation of our recommendation approach achieves higher average values of correctly ranked places (2.5 of 5 versus 1.5 of 5).

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A strategy for near-term success using knowledge-based systems

The Knowledge Engineering Review ◽

10.1017/s026988890000093x ◽

1987 ◽

Vol 2 (3) ◽

pp. 179-183 ◽

Cited By ~ 3

Author(s):

S. C. Laufmann

Keyword(s):

Cost Effective ◽

Valuable Insight ◽

Specific Data ◽

Knowledge Based System ◽

Data Intensive ◽

Knowledge Based ◽

Effective Manner ◽

Near Term ◽

Characteristic Features ◽

Insight Into

AbstractKnowledge-based System (KBS) technologies have been applied to a variety of knowledge-related tasks with varying degrees of success. Differentiating among classes of knowledge-related tasks, based on the amounts of problem-solving knowledge and case-specific data involved, can provide valuable insight into why this occurs. Based on this comparison, four classes of problems are described. One class, of data-intensive tasks, includes problem types that are difficult or impossible for humans to perform, yet may be solved in a cost-effective manner using currently accessible KBS technology. The characteristic features of problems in this class are given, together with an example of a successfully fielded knowledge-based system that solves a problem from this class.

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The Requirements to Enhance the Design of Context-Aware Mobile Patient Monitoring Systems Using Wireless Sensors

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Context-Aware Systems and Applications ◽

10.1007/978-3-642-36642-0_7 ◽

2013 ◽

pp. 62-71 ◽

Cited By ~ 2

Author(s):

Mahmood Ghaleb Al-Bashayreh ◽

Nor Laily Hashim ◽

Ola Taiseer Khorma

Keyword(s):

Wireless Sensors ◽

Patient Monitoring ◽

Monitoring Systems ◽

Context Aware ◽

Patient Monitoring Systems

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Context-Aware Mobile and Wearable Device Interfaces

Recent Advances in Ambient Intelligence and Context-Aware Computing - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-4666-7284-0.ch019 ◽

2015 ◽

pp. 308-321

Author(s):

Claas Ahlrichs ◽

Hendrik Iben ◽

Michael Lawo

Keyword(s):

Interaction Design ◽

Interface Design ◽

Wearable Computing ◽

Wearable Devices ◽

Future Research ◽

Context Information ◽

Context Aware ◽

Knowledge Based ◽

Input And Output ◽

Recent Developments

In this chapter, recent research on context-aware mobile and wearable computing is described. Starting from the observation of recent developments on Smartphones and research done in wearable computing, the focus is on possibilities to unobtrusively support the use of mobile and wearable devices. There is the observation that size and form matters when dealing with these devices; multimodality concerning input and output is important and context information can be used to satisfy the requirement of unobtrusiveness. Here, Frameworks as middleware are a means to an end. Starting with an introduction on wearable computing, recent developments of Frameworks for context-aware user interface design are presented, motivating the need for future research on knowledge-based intuitive interaction design.

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