Abstract
With the development of the World Wide Web and mobile devices, an enormous amount of explicit knowledge resources, distributed over multiple websites, can be accessed anywhere and anytime. However, to access this scattered knowledge, in unstructured text format, consumes a great deal of time and processing power, since the semantic relations among such resources are not directly stated and the content is not yet compiled into a meaningful context for effective action. Accordingly, instead of enhancing knowledge accessibility only, the challenge is how to provide a knowledge service that satisfies individual demands in actions and a timely manner. This paper focuses on developing a framework for handling knowledge extraction and integration across websites, using the agriculture domain as a case study, in order to provide more functional knowledge services to the end-user at the right time and in the right context. By merging two technologies, i.e., Knowledge Engineering and Language Engineering, a knowledge base can be constructed from unstructured text to enable the efficient and effective accessing and exploitation of knowledge. Usually, measurements for the success of knowledge service implementation are correctness of knowledge construction. However, this project aims to provide farmer service innovations with a functional knowledge according to crop calendar. Through the measurement of such operations, the farmer will gain maximum income while maximizing yields and minimizing costs through disease control and tailor-made fertilizing. Thus, the key performance indexes of knowledge service system, then, are benefit realization of the service consumer instead of service system correctness only.
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Kawtrakul, A. (2015). Knowledge Services Innovation: When Language Engineering Marries Knowledge Engineering. In: Gala, N., Rapp, R., Bel-Enguix, G. (eds) Language Production, Cognition, and the Lexicon. Text, Speech and Language Technology, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-319-08043-7_30
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