Handling Instability using Semantic Case Based Reasoning | ||||
| The Egyptian Journal of Language Engineering | ||||
| Article 3, Volume 3, Issue 2, September 2016, Page 25-40 PDF (1.01 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ejle.2016.60186 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Passent Mohamed Elkafrawy1; Rania A. Mohamed  2
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| 1Mathematics and computer science department, Faculty Science, Menoufia University | ||||
| 2Modern University for Technology and Information | ||||
| Abstract | ||||
| This paper proposes a joint effort technique between Case-Based Reasoning (CBR) and Semantic learning (SCBR) to handle instability in the cases recovery process with a specific end goal to cover more significant things in consequence of pursuit procedure. The coordinated effort strategy utilizes Ontological learning and Case-Based Reasoning in positioning (CBR) improvement. We diagram how Semantic Case-based Reasoning methodology can be actualized to handle the instability data keeping in mind the end goal to recognize trusted and untrusted members. The methodology could be stretched out to other application spaces of CBR. The real preferred standpoint of such approach is that Semantic information frameworks are intended to comprehend the substance of this present reality as precisely as would be prudent inside the information set. This paper additionally acquaints another methodology with Case-Based Reasoning (CBR) utilizing Semantic learning (SCBR) where it can deal with a few issues in customary CBR. | ||||
| Keywords | ||||
| Uncertainty information; Case-Based Reasoning; ontology; Semantic Knowledge | ||||
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