The Research On Knowledge Context Recognizaton And Acquisition Based On Ontology

The age of the information has brought the opportunity to the big data, at the same time, the knowledge information is exploding. People are enjoying the convenient bringing by the large scale information and also annoyed by the question—how to obtain the knowledge which they really interested in. For this sake, the service on recommend knowledge personalized was born at the right moment. On the research of personalized knowledge recommendation, researchers integrate the context concept into knowledge to make people obtain not only knowledge itself but also make them knew more about the background and the process when the knowledge is created. This will provide more accurate and personalized recommendation service for users, during this process, the technology of recognizing and acquiring knowledge context is the key foundation of the service.Because ontology use its particular concept, relations, function, axioms and cases expression to descript things, ontology has been widely used in the field of knowledge engineering to achieve the knowledge’s sharing and reusing standardized and normalized. According to the complex knowledge context, ontology can descript the relations among the knowledge and its elements clearly, and also, ontology Provide a reasoning mechanism for users to obtain more hidden knowledge context. In addition, ontology combining with SWRL rules language performance a better superiority on context reasoning.This paper presents a general framework based on ontology theory to acquire and recognize the knowledge context named KC-CRRM(Knowledge Context-Collection Recognition Reasoning and Storage).This framework divide the process of the knowledge context recognition and acquisition into five blocks—knowledge context collection, knowledge context recognizing, knowledge context reasoning, knowledge context representation and knowledge context storage. These blocks descript the process of the original context collection, knowledge context interpretation, hidden knowledge context reasoning, context modeling and storage in detail.In this paper, we will expatiate on the five modules, and select the broadband user knowledge as a case to test the framework.At last, we will present the context we have recognized and acquitted.