Abstract: Generating a data model may include receiving a raw data set and generating a first repository based on a first set of features of the raw data set, a second repository having a second set of features based on an aggregation of features of the first repository, and a third repository having a third set of features based on the first and second features sets. The data model may be generated based on a tradeoff between accuracy and provenance of the model.

Abstract: A mobile unit in a housing facility for mobile units may be tracked by activating a first reading device at a first location of the housing facility upon detecting a first mobile unit arriving at or departing from the first location, wherein the first mobile unit has a first tag having an identification code (ID) readable by the first reading device. A set of readings may be performed by the first reading device to read a set of tag IDs during a time interval. Upon an ending of the time interval, tag IDs, in the set of tag IDs, that correspond to the first tag ID are identified based on the set of readings. A record is updated to associate the first tag ID with the first location.

Abstract: A method and apparatus for data processing. The method calculates correlations between a plurality of attributes in a dataset. The attributes are factors involved in transaction processing. The method generates a relationship graph by using the plurality of attributes and the correlations between the plurality of attributes; and extracts a sub-graph from the relationship graph to represent a hypothesis. The hypothesis describes the impacts of the factors on the transaction processing. Also provided is an apparatus for implementing the above data processing method.

Abstract: The invention provides a method and apparatus for obtaining hierarchical information of planar data. The method comprises mapping at least one data item from a same data set in the planar data to at least one node in a tree structure formed by a structured terminology system. The method also comprises obtaining at least one sub tree structure in the tree structure, each of the at least one sub tree structure taking the at least one node as all of its leaf node. The method also comprises selecting a target tree structure from the at least one sub tree structure and obtaining hierarchical information in the target tree structure. An apparatus corresponding to the above method is also provided. With the above method and apparatus, hierarchical information of data items may be obtained from planar organized data to facilitate subsequent and further analysis and management.

Abstract: An apparatus for visualizing data includes memory for storing sensor data and a processor. The processor is configured to generate a map of a geographic area, and to display at a first location on the map at least one icon graphically representing a measurement of the sensor at the first location over a period of time and graphically representing the period of time.

Abstract: A method for visualizing data includes generating on a display device a map including a first location and generating on the display device at least one icon graphically representing measurements of the sensor at the first location over a period of time and graphically representing the period of time.

Abstract: A method for visualizing data includes generating on a display device a map including a first location and generating on the display device at least one icon graphically representing measurements of the sensor at the first location over a period of time and graphically representing the period of time.

Abstract: An apparatus for visualizing data includes memory for storing sensor data and a processor. The processor is configured to generate a map of a geographic area, and to display at a first location on the map at least one icon graphically representing a measurement of the sensor at the first location over a period of time and graphically representing the period of time.

Abstract: A dependency graph of rule predicates without strongly connected sub-graph is obtained. The dependency graph indicates the dependency among the rule predicates. An update frequency of node in the dependency graph is calculated, and a query frequency of node in the dependency graph is also calculated. Furthermore, a runtime query cost value and a materialization cost value of the node are calculated based on the query frequency and update frequency. Node to be materialized are determined based on the runtime query cost value and the materialization cost value. A rule predicate corresponding to the node to be materialized is the rule predicate to be materialized. In at least some instances, an exemplary technical effect is that the return time of result of runtime query is saved and the affect by the data update is reduced when a query is performed in relation data reasoning system constructed with rule predicates.

Abstract: Query requests for RDF triples are obtained, wherein the query request(s) contain(s) at least one triple pattern; for each triple pattern, the corresponding elementary pattern is determined, and each triple pattern is converted to a weighted elementary pattern. The occurrence frequency of each elementary pattern is computed based on the weighted elementary patterns; at least one elementary pattern is chosen at least according to the occurrence frequency; and the RDF triples corresponding to the chosen at least elementary pattern are prefetched into the buffer. The corresponding apparatus is also provided. With the above method and apparatus, the frequently accessed RDF triples can be determined and prefetched into the buffer, which improves the query efficiency.

Abstract: A computer-implemented system and method for translating a SPARQL query. The system includes: a parser/lexer for parsing the SPARQL query; a hidden negative pattern detector for detecting a hidden negative pattern in the parsed SPARQL query; a hidden negative pattern translator for translating the detected hidden negative pattern into an explicit negative pattern; a separator for separating the explicit negative pattern from a positive pattern in the parsed SPARQL query; a negative pattern translator for translating the explicit negative pattern into a negative portion of an SQL statement; a positive pattern translator for translating the positive pattern into a positive portion of the SQL statement; and an SQL statement combiner for combining the negative portion of the SQL statement with the positive portion of the SQL statement.

Abstract: The invention provides a method and apparatus for obtaining hierarchical information of planar data. The method comprises mapping at least one data item from a same data set in the planar data to at least one node in a tree structure formed by a structured terminology system. The method also comprises obtaining at least one sub tree structure in the tree structure, each of the at least one sub tree structure taking the at least one node as all of its leaf node. The method also comprises selecting a target tree structure from the at least one sub tree structure and obtaining hierarchical information in the target tree structure. An apparatus corresponding to the above method is also provided. With the above method and apparatus, hierarchical information of data items may be obtained from planar organized data to facilitate subsequent and further analysis and management.

Abstract: Query requests for RDF triples are obtained, wherein the query request(s) contain(s) at least one triple pattern; for each triple pattern, the corresponding elementary pattern is determined, and each triple pattern is converted to a weighted elementary pattern. The occurrence frequency of each elementary pattern is computed based on the weighted elementary patterns; at least one elementary pattern is chosen at least according to the occurrence frequency; and the RDF triples corresponding to the chosen at least elementary pattern are prefetched into the buffer. The corresponding apparatus is also provided. With the above method and apparatus, the frequently accessed RDF triples can be determined and prefetched into the buffer, which improves the query efficiency.

Abstract: A method and apparatus for providing the information of adverse drug effects. The method includes: extracting at least a first information and a second information in basic information of a drug from a drug information source; matching the drug with a particular drug-related concept in a structured and normalized terminology system according to the first and the second information; extracting, from the drug information source, the information of Adverse Drug Effects associated with the drug; and matching the information of Adverse Drug Effects with a particular disorder-related concept in the structured and normalized terminology system; wherein the matching is along different paths in at least two disorder-related classified hierarchies. The invention can extract, standardize, and normalize information relating to adverse drug effects to help the integration, search, calculation, and propagation thereof.

Abstract: A dependency graph of rule predicates without strongly connected sub-graph is obtained. The dependency graph indicates the dependency among the rule predicates. An update frequency of node in the dependency graph is calculated, and a query frequency of node in the dependency graph is also calculated. Furthermore, a runtime query cost value and a materialization cost value of the node are calculated based on the query frequency and update frequency. Node to be materialized are determined based on the runtime query cost value and the materialization cost value. A rule predicate corresponding to the node to be materialized is the rule predicate to be materialized. In at least some instances, an exemplary technical effect is that the return time of result of runtime query is saved and the affect by the data update is reduced when a query is performed in relation data reasoning system constructed with rule predicates.

Abstract: A computer-implemented system and method for translating a SPARQL query. The system includes: a parser/lexer for parsing the SPARQL query; a hidden negative pattern detector for detecting a hidden negative pattern in the parsed SPARQL query; a hidden negative pattern translator for translating the detected hidden negative pattern into an explicit negative pattern; a separator for separating the explicit negative pattern from a positive pattern in the parsed SPARQL query; a negative pattern translator for translating the explicit negative pattern into a negative portion of an SQL statement; a positive pattern translator for translating the positive pattern into a positive portion of the SQL statement; and an SQL statement combiner for combining the negative portion of the SQL statement with the positive portion of the SQL statement.