A Classification of Data Mining Algorithms for Wireless Sensor Networks, and Classification Extension to Concept Modeling in System of Wireless Sensor Networks Based on Natural Language Processing

In this article, we propose one original classification and one extension thereof, which takes into consideration the relevant issues in Natural Language Processing. The newly introduced classification of Data Mining algorithms is on the level of a single Wireless Sensor Network and its extension to Concept Modeling on the level of a System of Wireless Sensor Networks. Most of the scientists in this field put emphasis on issues related to applications of Wireless Sensor Networks in different areas, while we here put emphasis on categorization of the selected approaches from the open literature, to help application designers/developers get a better understanding of their options in different areas. Our main goal is to provide a good starting point for a more effective analysis leading to possible new solutions, possible improvements of existing solutions, and possible combination of two or more of the existing solutions into new ones, using the hybridization principle. Another contribution of this article is a synergistic interdisciplinary review of problems in two areas: Data Mining and Natural Language Processing. This enables interoperability improvements on the interface between Wireless Sensor Networks that often share data in native natural languages.