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1. 发明申请

US20100125594A1 Method and Apparatus for Improving Performance of Approximate String Queries Using Variable Length High-Quality Grams 有权
标题翻译：用于提高使用可变长度高质量克的近似字符串查询性能的方法和装置
公开(公告)号：US20100125594A1
公开(公告)日：2010-05-20
申请号：US12334471
申请日：2008-12-14
申请人： Chen Li , Bin Wang , Xaochun Yang , Alexander Behm , Shengyue Ji , Jiaheng Lu
发明人： Chen Li , Bin Wang , Xaochun Yang , Alexander Behm , Shengyue Ji , Jiaheng Lu
IPC分类号： G06F17/30
CPC分类号： G06F17/30985
摘要： A computer process, called VGRAM, improves the performance of these string search algorithms in computers by using a carefully chosen dictionary of variable-length grams based on their frequencies in the string collection. A dynamic programming algorithm for computing a tight lower bound on the number of common grams shared by two similar strings in order to improve query performance is disclosed. A method for automatically computing a dictionary of high-quality grams for a workload of queries. Improvement on query performance is achieved by these techniques by a cost-based quantitative approach to deciding good grams for approximate string queries. An approach for answering approximate queries efficiently based on discarding gram lists, and another is based on combining correlated lists. An indexing structure is reduced to a given amount of space, while retaining efficient query processing by using algorithms in a computer based on discarding gram lists and combining correlated lists.
摘要翻译：称为VGRAM的计算机进程通过使用经过仔细选择的基于字符串集合中的频率的可变长度的字典来提高计算机中这些字符串搜索算法的性能。公开了一种动态编程算法，用于计算由两个相似的字符串共享的共同数目的紧密下限，以提高查询性能。一种用于为查询工作量自动计算高质量克词典的方法。通过这些技术，通过基于成本的定量方法来确定查询性能的改进来确定近似字符串查询的好克数。一种基于丢弃克列表来有效回答近似查询的方法，另一种是基于相关列表的组合。索引结构减少到给定的空间，同时通过使用计算机中的算法保留有效的查询处理，基于丢弃克列表并组合相关列表。

2. 发明授权

US07996369B2 Method and apparatus for improving performance of approximate string queries using variable length high-quality grams 有权
标题翻译：使用可变长度高质量克改善近似字符串查询性能的方法和装置
公开(公告)号：US07996369B2
公开(公告)日：2011-08-09
申请号：US12334471
申请日：2008-12-14
申请人： Chen Li , Bin Wang , Xaochun Yang , Alexander Behm , Shengyue Ji , Jiaheng Lu
发明人： Chen Li , Bin Wang , Xaochun Yang , Alexander Behm , Shengyue Ji , Jiaheng Lu
IPC分类号： G06F17/00
CPC分类号： G06F17/30985
摘要： A computer process, called VGRAM, improves the performance of these string search algorithms in computers by using a carefully chosen dictionary of variable-length grams based on their frequencies in the string collection. A dynamic programming algorithm for computing a tight lower bound on the number of common grams shared by two similar strings in order to improve query performance is disclosed. A method for automatically computing a dictionary of high-quality grams for a workload of queries. Improvement on query performance is achieved by these techniques by a cost-based quantitative approach to deciding good grams for approximate string queries. An approach for answering approximate queries efficiently based on discarding gram lists, and another is based on combining correlated lists. An indexing structure is reduced to a given amount of space, while retaining efficient query processing by using algorithms in a computer based on discarding gram lists and combining correlated lists.
摘要翻译：称为VGRAM的计算机进程通过使用经过仔细选择的基于字符串集合中的频率的可变长度的字典来提高计算机中这些字符串搜索算法的性能。公开了一种动态编程算法，用于计算由两个相似的字符串共享的共同数目的紧密下限，以提高查询性能。一种用于为查询工作量自动计算高质量克词典的方法。通过这些技术，通过基于成本的定量方法来确定查询性能的改进来确定近似字符串查询的好克数。一种基于丢弃克列表来有效回答近似查询的方法，另一种是基于相关列表的组合。索引结构减少到给定的空间，同时通过使用计算机中的算法保留有效的查询处理，基于丢弃克列表并组合相关列表。

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