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Development of a Novel Compressed Index-Query Web Search Engine Model

机译:新型压缩索引查询网络搜索引擎模型的开发

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摘要

In this paper, the authors present a description of a new Web search engine model, the compressed index-query (CIQ) Web search engine model. This model incorporates two bit-level compression layers implemented at the back-end processor (server) side, one layer resides after the indexer acting as a second compression layer to generate a double compressed index (index compressor), and the second layer resides after the query parser for query compression (query compressor) to enable bit-level compressed index-query search. The data compression algorithm used in this model is the Hamming codes-based data compression (HCDC) algorithm, which is an asymmetric, lossless, bit-level algorithm permits CIQ search. The different components of the new Web model are implemented in a prototype CIQ test tool (CIQTT), which is used as a test bench to validate the accuracy and integrity of the retrieved data and evaluate the performance of the proposed model. The test results demonstrate that the proposed CIQ model reduces disk space requirements and searching time by more than 24%, and attains a 100% agreement when compared with an uncompressed model.
机译:在本文中,作者介绍了一种新的Web搜索引擎模型,即压缩索引查询(CIQ)Web搜索引擎模型。该模型包含在后端处理器(服务器)端实现的两个位级压缩层,一层驻留在索引器之后,该索引器充当第二压缩层以生成双压缩索引(索引压缩器),第二层驻留在索引器之后用于查询压缩的查询解析器(查询压缩器)以启用位级压缩的索引查询搜索。该模型中使用的数据压缩算法是基于汉明码的数据压缩(HCDC)算法,这是一种不对称,无损的位级算法,允许进行CIQ搜索。新Web模型的不同组件在原型CIQ测试工具(CIQTT)中实现,该工具用作测试平台以验证检索到的数据的准确性和完整性并评估所提出模型的性能。测试结果表明,与未压缩的模型相比,所提出的CIQ模型将磁盘空间需求和搜索时间减少了24%以上,并达到了100%的一致性。

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