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Web-scale knowledge graphs containing billions of entities are common nowadays. Querying these graphs can be modeled as a subgraph matching problem. Since knowledge graphs are incomplete and noisy in nature, it is important to discover answers matching exactly as well as answers similar to queries. Existing graph matching algorithms usually use graph indices to accelerate query processing. For billion-node...
With the explosion of data in the past decade, big data is becoming a research hotspot in the information field. Many cloud-based distributed data processing platforms have been proposed to provide efficient and cost effective solutions for big data query processing, such as Hadoop, Hive, Pig, etc. However, most of the current research works are focus on improving the performance of query processing...
Sampling-based approximate query processing method provides the way, in which the users can save their time and resources for 'Big Data' analytical applications, if the estimated results can satisfy the accuracy expectation earlier before a long wait for the final accurate results. Online aggregation (OLA) is such an attractive technology to respond aggregation queries by calculating approximate results...
Fundamental problems that confront traditional centralized Grid information services are low query efficiency and single points of failure. This paper presents an improved DHT-based Grid information services architecture, that resolves these problems well. The architecture assigns each resource node and information server an m-bit identifier by hashing attribute values. Every node makes connection...
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