【摘要】 随着信息化技术的发展,面对材料等相关领域数据的多源异构、扩展性强、爆炸增长等特点,传统关系数据库无法对数据进行存储,因此可利用NoSQL的无模式存储、高扩展性等特性来解决这一难题。作为NoSQL数据库常用的数据存储格式,JSON因简单性和灵活性备受欢迎。然而,NoSQL数据库缺乏模式信息,在JSON文档存入数据库之前,需要对其进行数据验证与分析。目前,大多数方法是基于JSON schema对JSON文档格式的规范性进行校验,无法有效解决JSON文档的异常检测以及语义歧义问题。为此,文中提出了面向NoSQL数据库的JSON文档异常检测与语义消歧模型doctorJSON。该模型基于JSON schema对存入的JSON文档分别设计了异常检测算法deoutJSON和语义消歧算法disemaJSON,以检测JSON文档存在的异常和歧义。在真实数据集与合成数据集上的实验验证了所提模型的有效性和执行效率。更多还原

【Abstract】 With the development of information technology,traditional relational database cannot be used for storage due to multi-source heterogeneity,strong scalability and explosive growth of data in materials and other related fields.Therefore,NoSQL can be used with the charactersitics of schemaless storage and high scalability to solve this problem.As a common data storage format for NoSQL databases,JSON is popular for its simplicity and flexibility.However,NoSQL databases lack schema information,and JSON documents need to be validated and analyzed before being stored in the database.At present,most methods verify the normalization of JSON document format based on JSON schema,which cannot effectively solve the problem of exception detection and semantic ambiguity of JSON document.Therefore,a JSON document outlier detection and semantic disambiguating model for NoSQL database is proposed,named doctorJSON.Based on JSON schema,the model designs outlier detection algorithm deout JSON and semantic disambiguation algorithm disemaJSON to detect the outlier and disambiguation in JSON documents.The vali-dity and efficiency of the model are verified by experiments on the real and synthetic datasets.更多还原