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1. 发明授权

US06408300B1 Multidimensional indexing structure for use with linear optimization queries 失效
标题翻译：用于线性优化查询的多维索引结构
公开(公告)号：US06408300B1
公开(公告)日：2002-06-18
申请号：US09360366
申请日：1999-07-23
申请人： Lawrence David Bergman , Vittorio Castelli , Yuan-Chi Chang , Chung-Sheng Li , John Richard Smith
发明人： Lawrence David Bergman , Vittorio Castelli , Yuan-Chi Chang , Chung-Sheng Li , John Richard Smith
IPC分类号： G06F1730
CPC分类号： G06F17/30333 , Y10S707/99934 , Y10S707/99942 , Y10S707/99945 , Y10S707/99948
摘要： Linear optimization queries, which usually arise in various decision support and resource planning applications, are queries that retrieve top N data records (where N is an integer greater than zero) which satisfy a specific optimization criterion. The optimization criterion is to either maximize or minimize a linear equation. The coefficients of the linear equation are given at query time. Methods and apparatus are disclosed for constructing, maintaining and utilizing a multidimensional indexing structure of database records to improve the execution speed of linear optimization queries. Database records with numerical attributes are organized into a number of layers and each layer represents a geometric structure called convex hull. Such linear optimization queries are processed by searching from the outer-most layer of this multi-layer indexing structure inwards. At least one record per layer will satisfy the query criterion and the number of layers needed to be searched depends on the spatial distribution of records, the query-issued linear coefficients, and N, the number of records to be returned. When N is small compared to the total size of the database, answering the query typically requires searching only a small fraction of all relevant records, resulting in a tremendous speedup as compared to linearly scanning the entire dataset.
摘要翻译：通常在各种决策支持和资源规划应用中出现的线性优化查询是检索满足特定优化标准的前N个数据记录（其中N是大于零的整数）的查询。优化标准是最大化或最小化线性方程。查询时给出线性方程的系数。公开了用于构建，维护和利用数据库记录的多维索引结构以提高线性优化查询的执行速度的方法和装置。具有数值属性的数据库记录被分为多个层，每个层表示一个称为凸包的几何结构。通过从该多层索引结构的最外层向内搜索来处理这样的线性优化查询。每层至少一个记录将满足查询条件，需要搜索的层数取决于记录的空间分布，查询发出的线性系数，N，要返回的记录数。当N与数据库的总大小相比较小时，回答查询通常只需要搜索所有相关记录的一小部分，与线性扫描整个数据集相比，导致了巨大的加速。

2. 发明授权

US06529916B2 Multidimensional indexing structure for use with linear optimization queries 失效
公开(公告)号：US06529916B2
公开(公告)日：2003-03-04
申请号：US10047129
申请日：2002-01-15
申请人： Lawrence David Bergman , Vittorio Castelli , Yuan-Chi Chang , Chung-Sheng Li , John Richard Smith
发明人： Lawrence David Bergman , Vittorio Castelli , Yuan-Chi Chang , Chung-Sheng Li , John Richard Smith
IPC分类号： G06F1730
CPC分类号： G06F17/30333 , Y10S707/99934 , Y10S707/99942 , Y10S707/99945 , Y10S707/99948
摘要： Linear optimization queries, which usually arise in various decision support and resource planning applications, are queries that retrieve top N data records (where N is an integer greater than zero) which satisfy a specific optimization criterion. The optimization criterion is to either maximize or minimize a linear equation. The coefficients of the linear equation are given at query time. Methods and apparatus are disclosed for constructing, maintaining and utilizing a multidimensional indexing structure of database records to improve the execution speed of linear optimization queries. Database records with numerical attributes are organized into a number of layers and each layer represents a geometric structure called convex hull. Such linear optimization queries are processed by searching from the outer-most layer of this multi-layer indexing structure inwards. At least one record per layer will satisfy the query criterion and the number of layers needed to be searched depends on the spatial distribution of records, the query-issued linear coefficients, and N, the number of records to be returned. When N is small compared to the total size of the database, answering the query typically requires searching only a small fraction of all relevant records, resulting in a tremendous speedup as compared to linearly scanning the entire dataset.

3. 发明授权

US06925453B1 Methods and apparatus for distributed resource discovery using examples 失效
标题翻译：使用示例的分布式资源发现的方法和设备
公开(公告)号：US06925453B1
公开(公告)日：2005-08-02
申请号：US09614141
申请日：2000-07-13
申请人： Lawrence David Bergman , Vittorio Castelli , Yuan-Chi Chang , Matthew L. Hill , Chung-Sheng Li , John Richard Smith
发明人： Lawrence David Bergman , Vittorio Castelli , Yuan-Chi Chang , Matthew L. Hill , Chung-Sheng Li , John Richard Smith
IPC分类号： G06F15/18 , G06N5/02
CPC分类号： G06N5/022
摘要： Distributed resource discovery is an essential step for information retrieval and/or providing information services. This step is usually used for determining the location of an information or data repository which has relevant information. The most fundamental challenge is the usual lack of semantic interoperability of the requested resource. In accordance with the invention, a method is disclosed where distributed repositories achieve semantic interoperability through the exchange of examples and, optionally, classifiers. The outcome of the inventive method can be used to determine whether common labels are referring to the same semantic meaning.
摘要翻译：分布式资源发现是信息检索和/或提供信息服务的重要步骤。此步骤通常用于确定具有相关信息的信息或数据存储库的位置。最根本的挑战是通常缺乏所请求资源的语义互操作性。根据本发明，公开了一种方法，其中分布式存储库通过交换示例和可选地分类器来实现语义互操作性。本发明方法的结果可用于确定通用标签是指相同的语义含义。

4. 发明授权

US07373359B2 Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data 失效
标题翻译：从多维序列数据中提取和跟踪对象的方法和装置
公开(公告)号：US07373359B2
公开(公告)日：2008-05-13
申请号：US11034288
申请日：2005-01-12
申请人： Matthew L. Hill , Yuan-Chi Chang , Chung-Sheng Li , Vittorio Castelli , Lawrence David Bergman
发明人： Matthew L. Hill , Yuan-Chi Chang , Chung-Sheng Li , Vittorio Castelli , Lawrence David Bergman
IPC分类号： G06F17/30 , G06F15/16
CPC分类号： G06K9/32 , G06T7/20 , Y10S707/915 , Y10S707/99933 , Y10S707/99943
摘要： An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.
摘要翻译：提供了一种对象跟踪技术，其给出：（i）潜在的大数据集; （ii）已订购数据的一组尺寸; 和（iii）用于测量数据元素之间的相似性的一组函数，产生一组对象。这些对象中的每一个由数据元素的列表定义。该列表中的每个数据元素都包含数据元素是对象一部分的概率。该方法通过自适应的基于知识的搜索功能产生这些列表，其引导搜索高概率数据元素。这用于减少评估的数据元素组合的数量，同时在定义包括对象的数据元素的关联方面保持最大的灵活性。

5. 发明授权

US06876999B2 Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data 失效
标题翻译：从多维序列数据中提取和跟踪对象的方法和装置
公开(公告)号：US06876999B2
公开(公告)日：2005-04-05
申请号：US09841949
申请日：2001-04-25
申请人： Matthew L. Hill , Yuan-Chi Chang , Chung-Sheng Li , Vittorio Castelli , Lawrence David Bergman
发明人： Matthew L. Hill , Yuan-Chi Chang , Chung-Sheng Li , Vittorio Castelli , Lawrence David Bergman
IPC分类号： G06T7/20 , G06F17/30
CPC分类号： G06K9/32 , G06T7/20 , Y10S707/915 , Y10S707/99933 , Y10S707/99943
摘要： An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.
摘要翻译：提供了一种对象跟踪技术，其给出：（i）潜在的大数据集; （ii）已订购数据的一组尺寸; 和（iii）用于测量数据元素之间的相似性的一组函数，产生一组对象。这些对象中的每一个由数据元素的列表定义。该列表中的每个数据元素都包含数据元素是对象一部分的概率。该方法通过自适应的基于知识的搜索功能产生这些列表，其引导搜索高概率数据元素。这用于减少所评估的数据元素组合的数量，同时在定义包括对象的数据元素的关联方面保持最大的灵活性。

6. 发明申请

US20050138023A1 Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data 失效
公开(公告)号：US20050138023A1
公开(公告)日：2005-06-23
申请号：US11034288
申请日：2005-01-12
申请人： Matthew Hill , Yuan-Chi Chang , Chung-Sheng Li , Vittorio Castelli , Lawrence Bergman
发明人： Matthew Hill , Yuan-Chi Chang , Chung-Sheng Li , Vittorio Castelli , Lawrence Bergman
IPC分类号： G06T7/20 , G06F17/30
CPC分类号： G06K9/32 , G06T7/20 , Y10S707/915 , Y10S707/99933 , Y10S707/99943
摘要： An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.

7. 发明授权

US10242406B2 Analytics integration workbench within a comprehensive framework for composing and executing analytics applications in business level languages 有权
公开(公告)号：US10242406B2
公开(公告)日：2019-03-26
申请号：US12559407
申请日：2009-09-14
申请人： Manoj Kumar , Yuan-Chi Chang , Chung-Sheng Li
发明人： Manoj Kumar , Yuan-Chi Chang , Chung-Sheng Li
IPC分类号： G06F17/30 , G06Q40/06 , G06F17/00
摘要： Systems, methods and articles of manufacture are disclosed for building and executing analytics solutions. Such a solution may provide a comprehensive analytics solution (e.g., a risk assessment, fraud detection solution, dynamic operational risk evaluations, regulatory compliance assessments, etc.). The analytics solution may perform an analytics task using operational data distributed across a variety of independently created and governed data repositories in different departments of an organization. A framework is disclosed which allows a user (e.g., a risk analyst) to compose analytical tools that can access data from a variety of sources (both internal and external to an enterprise) and perform a variety of analytic functions.

8. 发明申请

US20100145931A1 SYSTEM AND METHOD FOR INDEXING, SEARCHING AND RETRIEVING SEMANTIC OBJECTS 有权
标题翻译：用于索引，搜索和检索语义对象的系统和方法
公开(公告)号：US20100145931A1
公开(公告)日：2010-06-10
申请号：US12706345
申请日：2010-02-16
申请人： Yuan-Chi Chang , Matthew L. Hill , Chung-Sheng Li
发明人： Yuan-Chi Chang , Matthew L. Hill , Chung-Sheng Li
IPC分类号： G06F17/30
CPC分类号： G06F17/30241 , Y10S707/954 , Y10S707/955
摘要： A method and structure for storing information for one or more semantic objects derived from raw data. A semantic object extracted from the raw data and classified to comprise the semantic object is received, the received semantic object having one or more attributes. A summary of attributes of the semantic object by calculating one or more statistics of one or more of the one or more attributes of the received semantic object, a confidence level of the received semantic object that quantifies a degree of certainty that the received semantic object has been correctly classified and/or labeled; and a compact representation of raw data of the received semantic object are generated. Indexing information for one or more of the summary of attributes and the compact representation of the semantic object is generated. The semantic object, along with its associated summary of attributes, confidence level, compact representation, and indexing information, stored in a semantic object database associated with a database storing the raw data.
摘要翻译：一种用于存储从原始数据导出的一个或多个语义对象的信息的方法和结构。从原始数据提取并分类为包含语义对象的语义对象被接收，所接收的语义对象具有一个或多个属性。通过计算接收到的语义对象的一个或多个属性中的一个或多个属性的一个或多个统计信息，所接收的语义对象的置信水平，其量化接收到的语义对象具有的确定性程度，来对语义对象的属性进行概括被正确分类和/或标记; 并生成接收到的语义对象的原始数据的紧凑表示。生成一个或多个属性摘要的索引信息和语义对象的紧凑表示。存储在与存储原始数据的数据库相关联的语义对象数据库中的语义对象及其相关联的属性摘要，置信水平，紧凑表示和索引信息。

9. 发明授权

US07289981B2 Using text search engine for parametric search 有权
标题翻译：使用文本搜索引擎进行参数搜索
公开(公告)号：US07289981B2
公开(公告)日：2007-10-30
申请号：US10316312
申请日：2002-12-10
申请人： Yuan-Chi Chang , Howard C. Chin , Chung-Sheng Li , Carsten E. Mytroen
发明人： Yuan-Chi Chang , Howard C. Chin , Chung-Sheng Li , Carsten E. Mytroen
IPC分类号： G06F17/30
CPC分类号： G06F17/30 , Y10S707/99931 , Y10S707/99933
摘要： A method, system, and computer program for enabling parametric searches on source data using text search engine. The invention is generally divided into a build-time process and a run-time process. During the build-time process, a crawler extracts data units from source data. A data translator then translates data units into keyword parametric entries that are submitted to the text search engine. During the run-time process, a query translator translates parametric search queries into keyword search entries. A metadata refiner then filters intermediate search results from the search engine based on the parametric search query.
摘要翻译：一种使用文本搜索引擎对源数据进行参数搜索的方法，系统和计算机程序。本发明通常分为建立时程序和运行时程序。在构建时间过程中，爬网程序从源数据中提取数据单元。然后，数据转换器将数据单元转换成提交到文本搜索引擎的关键字参数条目。在运行时过程中，查询翻译器将参数搜索查询转换为关键字搜索条目。然后，元数据精炼器基于参数搜索查询对来自搜索引擎的中间搜索结果进行过滤。

10. 发明申请

US20050120013A1 Systems and method for indexing, searching and retrieving semantic objects 有权
标题翻译：索引，搜索和检索语义对象的系统和方法
公开(公告)号：US20050120013A1
公开(公告)日：2005-06-02
申请号：US10724897
申请日：2003-12-02
申请人： Yuan-Chi Chang , Matthew Hill , Chung-Sheng Li
发明人： Yuan-Chi Chang , Matthew Hill , Chung-Sheng Li
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30241 , Y10S707/954 , Y10S707/955
摘要： A method and system for storing a semantic object includes summarizing the attributes of a semantic object, indexing the summary of attributes, and storing the summary of attributes and the index of the summary of attributes.
摘要翻译：用于存储语义对象的方法和系统包括概括语义对象的属性，索引属性的概要，以及存储属性的总结以及属性的总结的索引。

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