面向中文知識圖譜的數(shù)據(jù)重組與應(yīng)用
[Abstract]:With the rapid development of semantic web, more and more map data based on RDF have been published on the world wide web, forming open link data (Linking Open Data). In general, this open data provides SPARQL query services and keyword access services. In fact, quite a number of users choose keyword access when accessing, and these access behaviors are also recorded in the server log. Although the complexity of Sparql and the lack of understanding of the query graph, it is difficult for users to obtain ideal query results. In addition to RDF, the standard format of semantic web data exchange, with the rise and development of No SQL, query and storage based on attribute graph data have been paid more and more attention and research. Although some attribute graph-based metrics have been published and applied to actual scenarios, there is still a lack of widely accepted benchmarks to measure comprehensive performance. Therefore, how to better organize and use the accumulated mass of semantic data based on RDF has become an open problem in the field of semantic Web. It is against this background that the graduation project proposes a framework for SPARQL query and recommendation on the RDF graph and a method for benchmarking attribute diagrams using RDF data. Specifically, the first is to propose a framework for the recommendation of SPARQL queries. By analyzing the access log of the knowledge map, the framework can mine the preference of the user query, and combine with the original SPARQL query statement of the user. The experimental results on the recommended query statement. Zhishi.me show that the recommended query statement can return the query results with better readability and can help users to traverse the knowledge map better by using SPARQL sentences. In addition, this paper proposes a benchmark to generate the store of the attribute graph by using the existing RDF data set. Firstly, the data model of RDF is transformed into the data model of attribute graph, and the corresponding query statement set is generated by analyzing the access log. The data set based on Zhishi.me implements the benchmark, and gives a full evaluation of the two most popular databases, Neo4j and Titan, which support the storage of attribute diagrams, which provides a reliable reference for users to choose the appropriate database.
【學(xué)位授予單位】:上海交通大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2015
【分類號】:TP391.3
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