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1. 发明申请

US20180307804A1 IDENTIFYING CHEMICAL SUBSTRUCTURES ASSOCIATED WITH ADVERSE DRUG REACTIONS 审中-公开
公开(公告)号：US20180307804A1
公开(公告)日：2018-10-25
申请号：US15494027
申请日：2017-04-21
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Sanjoy Dey , Achille Belly Fokoue-Nkoutche , Jianying Hu , Heng Luo , Ping Zhang
IPC分类号： G06F19/00 , G06N3/08 , G06N3/04
CPC分类号： G06F19/707 , G06N3/04 , G06N3/08
摘要： Embodiments of the present invention are directed to a computer-implemented method for generating a framework for analyzing adverse drug reactions. A non-limiting example of the computer-implemented method includes receiving to a processor, a plurality of drug chemical structures. The non-limiting example also includes receiving, to the processor, a plurality of known drug-adverse drug reaction associations. The non-limiting example also includes constructing, by the processor, a deep learning framework for each of a plurality of adverse drug reactions based at least in part upon the plurality of drug chemical structures and the plurality of known adverse-drug reaction associations.

2. 发明授权

US09715560B2 Optimizing sparse schema-less data in data stores 有权
公开(公告)号：US09715560B2
公开(公告)日：2017-07-25
申请号：US13929129
申请日：2013-06-27
申请人： International Business Machines Corporation
发明人： Mihaela Ancuta Bornea , Julian 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： Various embodiments of the invention relate to optimizing storage of schema-less data. At least one of a schema-less dataset including a plurality of resources one or more query workloads associated with the plurality of resources is received. Each resource is associated with at least a plurality of properties. At least one set of co-occurring properties from the plurality of properties is identified. A graph including a plurality of nodes is generated. Each of the nodes represents a unique property in the set of co-occurring properties. The graph further includes an edge connecting each node representing a pair of co-occurring properties. A schema is generated based on the graph that assigns a column identifier from a table to each unique property represented by one of the nodes in the graph.

3. 发明申请

US20150193478A1 Method and Apparatus for Determining the Schema of a Graph Dataset 有权
标题翻译：用于确定图形数据集模式的方法和装置
公开(公告)号：US20150193478A1
公开(公告)日：2015-07-09
申请号：US14151768
申请日：2014-01-09
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Marcelo Arenas , Gonzalo Diaz , Achille Belly Fokoue-Nkoutche , Anastasios Kementsietsidis , Kavitha Srinivas
IPC分类号： G06F17/30
CPC分类号： G06F17/30292 , G06F17/30339 , G06F17/30595 , G06F17/30958
摘要： A schema for a dataset is identified by identifying a dataset comprising data and relationships between data pairs. An original schema is identified for the dataset. This original schema comprises an organizational structure. An initial fit between the dataset and the original schema is determined. The initial fit quantifying a conformity of the data in the dataset to the organizational structure of the original schema. A plurality of additional schemas are identified. Each additional schema is a distinct organizational schema. The dataset is partitioned into a plurality of subsets. Each subset comprises a modified fit quantifying a modified conformity of subset data in each subset to one of the original schema and the additional schemas. The modified fit is greater than the original fit.
摘要翻译：通过识别包含数据和数据对之间的关系的数据集来识别数据集的模式。为数据集标识原始模式。该原始模式包括组织结构。确定数据集与原始模式之间的初始拟合。初始拟合量化数据集中的数据与原始模式的组织结构的一致性。识别多个附加模式。每个附加模式是不同的组织架构。数据集被划分成多个子集。每个子集包括将每个子集中的子集数据的修改的一致性量化为原始模式和附加模式之一的经修改的拟合。修改的拟合大于原始拟合。

4. 发明申请

US20180218265A1 SET-CENTRIC SEMANTIC EMBEDDING 审中-公开
公开(公告)号：US20180218265A1
公开(公告)日：2018-08-02
申请号：US15420971
申请日：2017-01-31
申请人： International Business Machines Corporation
发明人： Gonzalo Ignacio Diaz Caceres , Achille Belly Fokoue-Nkoutche , Mohammad Sadoghi Hamedani , Oktie Hassanzadeh , Mariano Rodriguez Muro
IPC分类号： G06N5/02 , H04L12/24 , G06N99/00
CPC分类号： G06N5/02
摘要： A semantic embedding model using geometrical set-centric approach to capture both ABox and TBox representational models is disclosed. The model transforms a semantic-rich knowledge graph into a set of overlapping, disjoint, and/or subsumed n-dimensional spheres that captures and represents semantics embedded in the knowledge graph.

5. 发明申请

US20160203236A1 Method and Apparatus for Identifying the Optimal Schema to Store Graph Data in a Relational Store 审中-公开
标题翻译：用于识别最佳模式以在关系存储中存储图形数据的方法和装置
公开(公告)号：US20160203236A1
公开(公告)日：2016-07-14
申请号：US15078931
申请日：2016-03-23
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： G06F16/9024 , G06F16/211
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。

6. 发明申请

US20150052134A1 Method and Apparatus for Storing Sparse Graph Data as Multi-Dimensional Cluster 有权
标题翻译：将稀疏图数据存储为多维集群的方法和装置
公开(公告)号：US20150052134A1
公开(公告)日：2015-02-19
申请号：US13967261
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： G06F17/30592 , G06F17/30312 , G06F17/30339 , G06F17/30424 , G06F17/30598 , G06F17/30958
摘要： A system for storing graph data as a multi-dimensional cluster having a database with a graph dataset containing data and relationships between data pairs and a schema list of storage methods that use a table with columns and rows associated with data or relationships. An analyzer module to collect statistics of a graph dataset and a dimension identification module to identify a plurality of dimensions that each represent a column in the table. A schema creation and loading module creates a modified storage method and having a plurality of distinct table blocks and a plurality of table block indexes, one index for each table block and arranges the data and relationships in the given graph dataset in accordance with the modified storage method to create the multi-dimensional cluster.
摘要翻译：用于将图形数据存储为具有数据库的图形数据的系统，该数据库具有包含数据和数据对之间的关系的图形数据集，以及使用具有与数据或关系相关联的列和行的表的存储方法的模式列表。分析器模块，用于收集图形数据集和维度识别模块的统计信息，以识别每个表示表中的列的多个维度。模式创建和加载模块创建经修改的存储方法并且具有多个不同的表块和多个表块索引，每个表块的一个索引，并且根据修改的存储器将数据和关系布置在给定图形数据集中方法来创建多维集群。

7. 发明申请

US20210342710A1 PROBLEM MANIPULATORS FOR LANGUAGE-INDEPENDENT COMPUTERIZED REASONING 有权
公开(公告)号：US20210342710A1
公开(公告)日：2021-11-04
申请号：US16864090
申请日：2020-04-30
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Cristina Cornelio , Achille Belly Fokoue-Nkoutche , Ibrahim Abdelaziz , Aldo Pareja , Michael John Witbrock
IPC分类号： G06N5/04 , G06N5/02 , G06N20/00 , G06F16/2453 , G06F16/22 , G06F16/248
摘要： A method of improving computing efficiency of a computing device for language-independent problem solving and reasoning includes receiving a query from a user, which is decomposed into one or more sub-queries arranged according to a tree structure. The one or more sub-queries are executed in a knowledge base. The results of the executed one or more sub-queries are received and composed into a query response. The query response is transmitted to the user.

8. 发明申请

US20210287103A1 INFUSING KNOWLEDGE INTO NATURAL LANGUAGE PROCESSING TASKS USING GRAPH STRUCTURES 有权
公开(公告)号：US20210287103A1
公开(公告)日：2021-09-16
申请号：US16814830
申请日：2020-03-10
申请人： International Business Machines Corporation
发明人： Pavan Kapanipathi Bangalore , Kartik Talamadupula , Veronika Thost , Siva Sankalp Patel , Ibrahim Abdelaziz , Avinash Balakrishnan , Maria Chang , Kshitij Fadnis , Chulaka Gunasekara , Bassem Makni , Nicholas Mattei , Achille Belly Fokoue-Nkoutche
IPC分类号： G06N5/02 , G06F40/40
摘要： One embodiment of the invention provides a method for natural language processing (NLP). The method comprises extracting knowledge outside of text content of a NLP instance by extracting a set of subgraphs from a knowledge graph associated with the text content. The set of subgraphs comprises the knowledge. The method further comprises encoding the knowledge with the text content into a fixed size graph representation by filtering and encoding the set of subgraphs. The method further comprises applying a text embedding algorithm to the text content to generate a fixed size text representation, and classifying the text content based on the fixed size graph representation and the fixed size text representation.

9. 发明授权

US10509804B2 Method and apparatus for storing sparse graph data as multi-dimensional cluster 有权
公开(公告)号：US10509804B2
公开(公告)日：2019-12-17
申请号：US15080011
申请日：2016-03-24
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： G06F16/22 , G06F16/28 , G06F16/245 , G06F16/901
摘要： A system for storing graph data as a multi-dimensional cluster having a database with a graph dataset containing data and relationships between data pairs and a schema list of storage methods that use a table with columns and rows associated with data or relationships. An analyzer module to collect statistics of a graph dataset and a dimension identification module to identify a plurality of dimensions that each represent a column in the table. A schema creation and loading module creates a modified storage method and having a plurality of distinct table blocks and a plurality of table block indexes, one index for each table block and arranges the data and relationships in the given graph dataset in accordance with the modified storage method to create the multi-dimensional cluster.

10. 发明授权

US08984019B2 Scalable summarization of data graphs 有权
标题翻译：数据图的可缩放总结
公开(公告)号：US08984019B2
公开(公告)日：2015-03-17
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。

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