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基于蜕变测试的面向用户搜索引擎性能分析 被引量:2

User-oriented Performance Analysis of Search Engine Based on Metamorphic Test
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摘要 面对海量的互联网信息,用户在进行搜索时缺乏客观公认的Oracle验证搜索引擎所返回结果是否正确。为此,将蜕变测试应用于搜索引擎的性能测试。针对搜索引擎Baidu、Bing和360,结合搜索操作符定义相应的蜕变关系,对其检索能力和排序稳定性进行测试,并通过异常率和平均Jaccard系数量化测试结果。分析结果表明,在搜索引擎Baidu、Bing和360中,Bing的异常率最低,Baidu的排序稳定性最高,三者对于不同领域的关键词搜索表现相差不大,但对于不同语言搜索表现存在很大差别。该结果为不同领域用户在选择合适的搜索引擎时提供了参考,同时可帮助搜索引擎的开发人员发现和移除程序中的错误。 Facing a large amount of Internet information,users lack an objective recognized Oracle to verify whether the results returned by the search engine are correct or not.Therefore,the metamorphic test is applied for search engine performance test.For search engines like Baidu,Bing and 360,the corresponding metamorphic relationship is defined by combining search operators.Their retrieval ability and sorting stability are tested,and the test results are quantified by abnormal rate and average Jaccard coefficient.Analysis results show that,among search engines Baidu,Bing and 360,Bing has the lowest abnormal rate and Baidu has the highest ranking stability.Meanwhile,Baidu,Bing and 360 have little difference in keyword search performance in different fields,but there are big differences in search performance of different languages.The results provide a reference for users of different domain when choosing the right search engine,and help search engine developers to find and remove errors in the program.
作者 杨正龙 高建华 YANG Zhenglong;GAO Jianhua(Department of Computer Science and Technology,Shanghai Normal University,Shanghai 200234,China)
出处 《计算机工程》 CAS CSCD 北大核心 2019年第10期52-56,63,共6页 Computer Engineering
基金 国家自然科学基金(61672355)
关键词 搜索引擎 蜕变测试 蜕变关系 Oracle问题 异常率 Jaccard系数 search engine metamorphic test metamorphic relation Oracle problem abnormal rate Jaccard coefficient
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  • 1Schach S R,邓迎春,韩松,徐天顺译.软件工程-面向对象和传统的方法[M].北京:机械工业出版社,2007.
  • 2王梓坤.随机过程论[M].北京:科学出版社,1978..
  • 3Shkapenyuk V, Suel T. Design and Implementation of a High- performance Distributed Web Crawler. In Proceedings of the 18th International Conference on Data Engineering (ICDE'02), San Jose, CA, 2002:357-368
  • 4Cho J, Garcia-Molina H, Page L. Efficient Crawling Through Url Ordering. In 7^th Int. World Wide Web Conference, 1998
  • 5Chakrabarti S, van den Berg M, Dom B. Focused Crawling: A New Approach to Topic-specific Web Resource Discovery. In Proc. of the 8^th Int. World Wide Web Conference (WWW8), 1999
  • 6Rennie J, McCallum A. Using Reinforcement Learning to Spider the Web Efficiently. In Proc. of the Int. Conf. on Machine Learning (ICML),1999
  • 7Spertus E. Parasite: Mining Structural Information on the Web. In : Proc. of the Sixth Int'l World Wide Web Conf. , 1997
  • 8Cho J, Garcia-Molina H. The Evolution of the Web and Implications for an Incremental Crawler. In Proc. of 26th Int. Conf. on Very Large Data Bases, 2000:117-128
  • 9Henzinger M R, Heydon A, Mitzenmacher M, et al. on Near-uniform URL Sampling. In Proc. of the 9^th Int. World Wide Web Conference, 2000
  • 10Raghavan S, Garcia-Molina H. Crawling the Hidden Web. In Proc. of 27^th Int. Conf. on Very Large Data Bases, 2001

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