基于多源家校溝通數(shù)據(jù)的個體特征分析支撐平臺
[Abstract]:At the beginning of 21 ~ (st) century, there are new ways of communication between home and school, such as mobile communication, Unicom and telecommunication. With the rapid development of the Internet, homeschooling communication platforms emerge in endlessly. There are system and semantic heterogeneity between platform data, there is no unified standard, and they are incompatible with other communication platforms. It is bound to create a new "data island". At present, the integration process of heterogeneous data sources based on ETL in traditional data warehouse is very complicated, semantic heterogeneity is difficult to deal with, and can not solve the problems of data sharing, reuse and semantic integration. In addition, ontology can accurately express conceptual semantics and has powerful reasoning ability. Ontology mapping is guided by ontology generation rules, which avoids the shortcomings of traditional heterogeneous data source integration. In summary, this paper proposes an ontology-based heterogeneous data source integration scheme in data warehouse. The integration scheme firstly constructs a shared vocabulary database, uses automatic tagging data storage algorithm to mark the data source pattern, generates application ontology, and then finds hidden hierarchy based on ontology mapping and reasoning. According to these generation rules, automatic ETL operation is realized. Then, the integration scheme is applied to the practical scenario of multi-source homeschooling data communication. The case shows that the ETL process guided by ontology solves the shortcomings of the traditional process and improves the efficiency of data source integration and integration. By analyzing the domain-oriented plug-in architecture, this paper proposes a data analysis support platform based on plug-in technology, and designs and implements it according to the principle of functional modularization. This paper introduces a multi-data source adaptation framework for multi-data sources, and proposes a dynamic data mining algorithm plug-in adaptation framework for the data analysis algorithm library, and implements dynamic loading and management of the algorithm plug-in. Finally, based on the data analysis support platform based on plug-in technology proposed in this paper, through the integration of heterogeneous data sources based on ontology, the data target number warehouse is used as the input source, and the main students, parents, as the input source. The basic data and behavior data of teachers are analyzed and excavated, and scientific management and decision are made according to the results, which is bound to bring inestimable value to the present educational pattern.
【學位授予單位】:浙江大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TP311.13
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