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Titlebook: Context-Aware Machine Learning and Mobile Data Analytics; Automated Rule-based Iqbal Sarker,Alan Colman,Paul Watters Book 2021 The Editor(s

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發(fā)表于 2025-3-23 12:40:03 | 只看該作者
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發(fā)表于 2025-3-23 17:46:14 | 只看該作者
Sustainability and Social Policy Nexusnted various components of context-aware machine learning framework and systems with their related issues, where contextual data acquisition is the primary step for context-aware machine learning modeling. In this chapter, we present several contextual datasets that can be utilized to build a machin
13#
發(fā)表于 2025-3-23 21:20:19 | 只看該作者
14#
發(fā)表于 2025-3-23 22:14:40 | 只看該作者
Nikolaos Karagiannis,Debbie A. Mohammedavioral patterns. In this chapter, we focus on discovering behavioral rules of individual mobile phone users by taking into account multi-dimensional contexts—for example temporal, spatial, or social context. Association rule mining is the most prominent rule-based machine learning method for genera
15#
發(fā)表于 2025-3-24 03:25:38 | 只看該作者
Proper Future Economic Policiesntexts (temporal, spatial, and social context) utilizing their phone log data. However, user behavior is not static, may change over time in the real world. The discovered rules from mobile phone data, therefore, need to be dynamically updated and managed according to the recent behavioral patterns
16#
發(fā)表于 2025-3-24 10:31:15 | 只看該作者
Global Institute for Sustainable Prosperityrather than using traditional procedural code, are structured to solve complex problems by reasoning through sources of knowledge, which are primarily interpreted as if–then rules. In this chapter, we explore primarily on context-aware rule-based expert system modeling, which is considered one of th
17#
發(fā)表于 2025-3-24 14:46:08 | 只看該作者
18#
發(fā)表于 2025-3-24 18:36:48 | 只看該作者
Finland: Vocational Guidance in Finland and availability in various real-world applications, there has been a lot of development in the domain of context-aware computing systems in recent years. However, building a context-aware machine learning system still poses a variety of genuine challenges. This chapter addresses the most important
19#
發(fā)表于 2025-3-24 19:30:35 | 只看該作者
https://doi.org/10.1007/978-3-030-88530-4mobile data analytics; user behavior modeling; context-aware mobile computing; personalization; mac
20#
發(fā)表于 2025-3-25 02:01:26 | 只看該作者
978-3-030-88532-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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