分布式信息檢索系統(tǒng)的優(yōu)化設(shè)計和實現(xiàn)
[Abstract]:The traditional search engine adopts a centralized information crawling and indexing method, and has certain limitation on the deep content, dynamic content and the processing of the private content on the network. The distributed information retrieval can be better adapted to the retrieval of various heterogeneous resources. It can effectively integrate and process the information of a variety of sources, and provide more diversified interactive services. The retrieval process can be divided into four stages: resource description, resource selection, query distribution and result fusion. In which the query distribution stage is accompanied by a large number of network communication, and a general IO model and a communication mode can be used to cause a large overhead, so a special design is required. In addition, the retrieval system needs to have good scalability to handle heterogeneous resources and diverse query requirements. Infrastructure for service registration, service management, service discovery and service monitoring also plays a key role in the stable operation of distributed systems. The focus of this paper is to design and implement a highly efficient, stable and scalable distributed information retrieval system. The paper mainly includes the following parts: (1) The overall architecture design of the distributed information retrieval system, according to the characteristics of the distributed information retrieval, the functional module of the division system, the IO model and the communication mode used by the analysis and selection system. (2) The basic components such as service registration, service management, service discovery and service monitoring of the system shall be designed and implemented so as to ensure the access and communication among all the service nodes of the system to be stable and reliable. And (3) in the core search module of the system, a resource selection, a query distribution and a result fusion interface are defined, and a corresponding algorithm is realized. The plug-in mechanism is designed and implemented to support a flexible extension of the core search module algorithm and functionality. And the cache function of resource selection and query distribution is realized, so that the throughput of the system is improved, the response time of the query is reduced, and the bandwidth is saved. (4) establishing a central sampling bank, and storing the sampling documents of each resource library so as to support the resource selection process. The query sampling tool is implemented, the resource pool is queried and sampled based on the retrieval interface of the resource pool, and the result is imported into the central sampling library. (5) The function and performance of the system are tested, and the performance changes of the system under different query parameters, resource pool response time, resource pool quantity and different concurrent numbers are compared and analyzed.
【學(xué)位授予單位】:華南理工大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2016
【分類號】:TP391.3
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