Patent application number | Description | Published |
20100114931 | FACET, LOGIC AND TEXTUAL-BASED QUERY COMPOSER - Described is a technology for composing queries by user interaction with objects and facets. A facet-based user interface allows users to select facets for use as filtering criteria, and a logic-based user interface allows users to logically combine object data. Query logic that processes the filtering criteria and/or logically combines the object data into a query. The facet-based user interface and logic-based user interface may be accessed via a unified user interface. The unified user interface may also provide a text editor for composing a text-based query. | 05-06-2010 |
20100287220 | Dynamically Encoding Types and Inhabitants in a Relational Database - Described is a technology, such as for representing scientific data and information, in which a database table contains rows of type data representing types, and term data representing terms that inhabit the types. Types include composite types (e.g., that represent entities), and instances of relation types that express relationships between types, between a type and a term, or between terms. Types and/or terms may have multiple relationships with one another, and a relationship may span database tables. A new relationship may be established by adding a new row to the database table to represent a new relation term, along with one or more similar rows to represent the relation role terms associated with that relation term; relationships may be removed by removing rows. As a result, the database table may change its state rapidly, without needing to change the database schema. | 11-11-2010 |
20110202560 | EXPRESSING AND EXECUTING SEMANTIC QUERIES WITHIN A RELATIONAL DATABASE - Semantic queries are expressed and executed within a relational database. This can be done by defining semantic rules applied to execute the semantic queries using table valued functions and common table expressions, and then simply calling the defined table valued functions to execute the queries. | 08-18-2011 |
20110320431 | STRONG TYPING FOR QUERYING INFORMATION GRAPHS - Described herein is using type information with a graph of nodes and predicates, in which the type information may be used to determine validity of (type check) a query to be executed against the graph. In one aspect, each node has a type, and each predicate indicates a valid relationship between two types of nodes. A type checking mechanism uses the type information to determine whether a query is valid, which may be the entire query prior to query processing/compilation time, or as the query is being composed by a user. One or more valid predicates for a given node may be discovered based upon the node type, such as discovered to assist the user during query composition. Also described is using the type information to optimize the query. | 12-29-2011 |
20120131128 | SYSTEM AND METHOD FOR GENERATING A CONSISTENT USER NAME-SPACE ON NETWORKED DEVICES - Implementing a consistent user name-space on networked computing devices includes various components and methods. When a network connection between a local or host computing device and one or more remote computing devices is present, remote items are represented using the same methodology as items located on the host computing device. To the user, remote and local items are indistinguishable. When the network connection is lost or items located on a remote computer are otherwise unavailable, the unavailable items remain represented on the host computing device. Unavailable items are represented in a way that informs the user that the items may not be fully accessed. | 05-24-2012 |
20120158636 | EFFICIENT PROBABILISTIC REASONING OVER SEMANTIC DATA - A semantic reasoning engine is described for performing probabilistic reasoning over a semantic graph in a time-efficient and viable manner. The semantic reasoning engine includes a data store that provides the semantic graph, where the semantic graph is formed by a plurality of concepts connected together via probabilistic assertions. The semantic reasoning engine operates by providing an answer to a query by recursively collapsing the semantic graph based on at least one collapsing rule. | 06-21-2012 |
20120166378 | FORWARD CHAINING AS AN ORCHESTRATION MECHANISM FOR ANALYTICS - A method and system of using a forward chaining application on a computing device to monitor a semantic storage system and invoke computations on scientific data according to declarative rules, while capturing operational provenance data stored alongside the scientific data where all data is stored in a semantic graph is disclosed and described. As the provenance data is stored with the data as nodes in the semantic graph, it will stay with the data and may be searched and queried using the same methods as searching the underlying data. | 06-28-2012 |
20120167108 | Model for Hosting and Invoking Applications on Virtual Machines in a Distributed Computing Environment - The described method/system/apparatus uses intelligence to better allocate tasks/work items among the processors and computers in the cloud. A priority score may be calculated for each task/work unit for each specific processor. The priority score may indicate how well suited a task/work item is for a processor. The result is that tasks/work items may be more efficiently executed by being assigned to processors in the cloud that are better prepared to execute the tasks/work items. | 06-28-2012 |
20120226710 | EXPRESSING AND EXECUTING SEMANTIC QUERIES WITHIN A RELATIONAL DATABASE - Semantic queries are expressed and executed within a relational database. This can be done by defining semantic rules applied to execute the semantic queries using table valued functions and common table expressions, and then simply calling the defined table valued functions to execute the queries. | 09-06-2012 |