公开(公告)号：US20150149440A1

公开(公告)日：2015-05-28

申请号：US14088574

申请日：2013-11-25

申请人： International Business Machines Corporation

发明人： Mihaela A. Bornea ,  Julian Dolby ,  Achille B. Fokoue-Nkoutche ,  Anastasios Kementsietsidis ,  Kavitha Srinivas

IPC分类号： G06F17/30

CPC分类号： G06F17/30469 ,  G06F17/30442 ,  G06F17/30477 ,  G06F17/3053 ,  G06F17/30935 ,  G06F17/30958

摘要： Systems and methods for optimizing a query, and more particularly, systems and methods for finding optimal plans for graph queries by casting the task of finding the optimal plan as an integer programming (ILP) problem. A method for optimizing a query, comprises building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern, determining a plurality of flows of query variables between the plurality of components, and determining a combination of the plurality of flows between the plurality of components that results in a minimum cost to execute the query.

摘要翻译： 用于优化查询的系统和方法，更具体地，涉及通过将找到最优计划作为整数规划（ILP）问题的任务来找到图查询的最佳计划的系统和方法。 一种用于优化查询的方法，包括建立用于查询的数据结构，所述数据结构包括多个组件，其中所述多个组件中的每一个对应于至少一个图形模式，确定所述查询变量的多个流 多个组件，以及确定导致执行查询的最小成本的多个组件之间的多个流的组合。

公开(公告)号：US20150052175A1

公开(公告)日：2015-02-19

申请号：US13967031

申请日：2013-08-14

申请人： International Business Machines Corporation

发明人： Mihaela Ancuta Bornea ,  Julian Timothy Dolby ,  Achille Belly Fokoue-Nkoutche ,  Anastasios Kementsietsidis ,  Kavitha Srinivas

IPC分类号： G06F17/30

CPC分类号： G06F17/30958 ,  G06F17/30292

摘要： A system for identifying a schema for storing graph data includes a database containing a graph dataset of data and relationships between data pairs and a list of storage methods that each are a distinct structural arrangement of the data and relationships from the graph data set. An analyzer module collects statistics for the graph dataset, and a data classification module uses the collected statistics to calculate metrics describing the data and relationships in the graph dataset, uses the calculated metrics to group the data and relationships into a plurality of graph dataset subsets and. associates each graph dataset subset with one of the plurality of storage methods. The resulting group of storage methods associated with the plurality of graph dataset subsets includes a unique storage method for each graph dataset subset. The data and relationships in each graph dataset subset are arranged in accordance with associated storage methods.

摘要翻译： 用于识别用于存储图形数据的模式的系统包括数据库，该数据库包含数据的图形数据集和数据对之间的关​​系以及存储方法的列表，每个存储方法是与图形数据集的数据和关系的不同结构布置。 分析器模块收集图形数据集的统计信息，数据分类模块使用收集的统计信息来计算描述图形数据集中的数据和关系的度量，使用计算的度量将数据和关系分组为多个图形数据集子集，以及 。 将每个图形数据集子集与多个存储方法之一相关联。 与多个图形数据集子集相关联的所得到的存储方法组包括用于每个图形数据集子集的唯一存储方法。 每个图形数据集子集中的数据和关系按照相关的存储方法进行排列。

公开(公告)号：US20140143280A1

公开(公告)日：2014-05-22

申请号：US13682245

申请日：2012-11-20

申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION

发明人： Songyun Duan ,  Achille Belly Fokoue-Nkoutche ,  Anastasios Kementsietsidis ,  Wangchao Le ,  Feifei Li ,  Kavitha Srinivas

IPC分类号： G06F17/30

CPC分类号： G06F17/30292

摘要： Keyword searching is used to explore and search large Resource Description Framework datasets having unknown or constantly changing structures. A succinct and effective summarization is built from the underlying resource description framework data. Given a keyword query, the summarization lends significant pruning powers to exploratory keyword searches and leads to much better efficiency compared to previous work. The summarization returns exact results and can be updated incrementally and efficiently.

摘要翻译： 关键字搜索用于探索和搜索具有未知或不断变化的结构的大型资源描述框架数据集。 从底层资源描述框架数据构建一个简洁有效的总结。 给出一个关键词查询，总结可以显着的修剪关键词搜索的修剪权力，并且与以前的工作相比，效率要好得多。 总结返回精确的结果，并可以逐步和有效地更新。

公开(公告)号：US08560483B2

公开(公告)日：2013-10-15

申请号：US13625931

申请日：2012-09-25

申请人： International Business Machines Corporation

发明人： Achille Fokoue ,  Aditya Kalyanpur ,  Kavitha Srinivas

IPC分类号： G06N5/04

CPC分类号： G06N5/025 ,  G06F19/00

摘要： Techniques for facilitating learning of one or more ontological rules of a resource description framework database are provided. The techniques include obtaining ontology vocabulary from a resource description framework database, generating a rule hypothesis by incrementally building upon a previously learnt rule from the database by adding one or more predicates to the previously learnt rule, performing a constraint check on the generated rule hypothesis by determining compatibility with each previously learnt rule to ensure that a complete rule set including each previously learnt rule and the generated rule hypothesis is consistent, validating the rule hypothesis as a rule using one or more association rule mining techniques to determine validity of the rule hypothesis against the database, and applying the rule to the database to infer one or more facts from the database to facilitate learning of one or more additional ontological rules.

摘要翻译： 提供了一种便于学习资源描述框架数据库的一个或多个本体论规则的技术。 这些技术包括从资源描述框架数据库中获取本体词汇，通过向先前学习的规则添加一个或多个谓词，通过逐步建立在先前学习的规则上，从数据库生成规则假设，通过以下方式对生成的规则假设执行约束检查： 确定与每个先前学习的规则的兼容性，以确保包括每个先前学习的规则和生成的规则假设的完整规则集合是一致的，使用一个或多个关联规则挖掘技术来将规则假设作为规则验证，以确定规则假设的有效性 数据库，以及将规则应用于数据库以从数据库推断一个或多个事实，以便于学习一个或多个附加本体规则。