Abstract: An array of registered entity property-value pairs representing a registered entity are stored in a data storage system. Each of the pairs includes a property label representing a property and a value range of the property. For each identifier property-value, an identifier property label, uniquely identifying the registered entity, and an identifier value representing a value of the identifier property are stored. A dataset is acquired with dataset property-value pairs for each of a first set of acquired dataset entities, where each pair includes a property label representing a property and a value representing a value range of the property. An identifier property-value pair matching an acquired dataset property-value pair for the acquired dataset entity is identified and then the acquired dataset property-value pairs are consolidated into the array of registered entity property-value pairs.

Abstract: A microservice-based data processing apparatus, including: a type register, storing a list of types, a type being a semantic concept expression; and microservices each comprising an annotation of an input type and output types from the list; processing logic transforming input data expressed by the input type into output data expressed by the output types; and a messaging mechanism for inputting data, via a message, to a microservice, the mechanism defining a message format for structuring the messages. The format includes a first field specifying the data being input; and a second field specifying a type, from the list of types, semantically expressing the concept instantiated by the data. Each microservice includes a controller to receive a message from the mechanism having the format, and to respond by executing the logic when the type specified by the second field matches the input type of the microservice.

Abstract: A data processing apparatus including a library, storing software services, each executing a data processing function; a user interface receiving commands, expressed in a language and defining a data processing target and a data processing request; and a parser. The parser extracting from each command: the request from the language; and the target. A knowledge base maintaining a record of the request and the target; a scheduler obtaining the request from the parser, and compiling a schedule to fulfill the request; a controller controlling execution of the schedule, the target being the input data to the execution, and to output a result; and a result processor obtaining the result, and, based on records of requests and targets, to identify a request candidate, and to output to the user as a selectable command in the language, via the user interface, the candidate with the result defined as a data processing target.

Abstract: A data property recognition apparatus, includes a storage unit; a model data acquisition processor acquiring a plurality of model sets of data entries, each data entry individually representing an identified property common to the model set and being of a data type common to the model set; a feature vector generation processor receiving an input set of data entries, recognizing a data type common to the input set of data entries from among a plurality of supported data types, selecting a set of statistical characteristics representing the input set of data entries in dependence upon the recognised data type, generating a value of each of the selected set of statistical characteristics from the input set of data entries, and outputting a feature vector composed of the generated values of statistical characteristics.

Abstract: An apparatus, method and program for generating a multiple-event pattern query for use in the retrieval of event information. The apparatus comprises: an inputter to receive an input query from a user; a retriever to analyze the received input query, and to retrieve an event query template from an event template database on the basis of the analysis; a pattern query formulation unit to receive the retrieved event query template, and to modify the event query template using the received input query to formulate the multiple-event pattern query; and a transmitter to transmit the multiple-event pattern query to an event information source, such that events matching the multiple-event pattern query may be identified.

Abstract: A data storage system a process including: storing an array of registered entity property-value pairs representing the registered entity where each of the pairs includes a property label representing a property and a value range of the property; storing an entry of one identifier property-value pair where each pair includes an identifier property label uniquely identifying the registered entity, and an identifier value representing a value of the identifier property; acquiring a dataset having acquired dataset property-value pairs for each of a first set of acquired dataset entities, where each pair includes a property label representing a property and a value representing a value range of the property; identifying an identifier property-value pair matching an acquired dataset property-value pair for the acquired dataset entity; and consolidating the acquired dataset property-value pairs into the array of registered entity property-value pairs.

Abstract: An event learner using machine intelligence includes an inputter to receive sample event patterns; an information retriever to retrieve terms information and to identify entities and predicates from the terms information; and a comparator to compare the identified entities and predicates against the sample event patterns, to generate a plurality of refined event patterns using the identified entities and predicates and the sample event patterns. An event extractor includes a selector to select raw information from a plurality of heterogeneous sources; a reformatter to identify entities and predicates in the raw information, and to generate reformatted information indicating the entities and predicates; and an analyser to analyse the reformatted information using the plurality of refined event patterns and, when an event matching a refined event pattern is identified, to store the event.

Abstract: An apparatus, method and program categorizing extracted events using a plurality of refined event patterns, and storing events matching a pattern in event storage; retrieving that match a pattern from the storage, to identify entities in the events, an event time of occurrence, and determine if events relate to the same occurrence, if the reconciliation determines that events relate to the same occurrence, reconciling the events retaining only a single event relating to an occurrence; receiving a query from a user, to reformat the query into a multiple-event pattern query, and semantically annotating the retained events, such that no information from the plural stored events relating to the same occurrence is lost, and receiving the pattern query to identify events matching the pattern query, and storing the events as a multiple event query response in a multiple event storage.

Abstract: A data property recognition apparatus, includes a reference data storage unit storing a plurality of model sets of data entries, each data entry individually representing a property common to the model set, stored in association with a reference feature vector and a descriptor of the property; a query processor obtaining a query set of data entries; a feature vector generation processor generating a value of each of the set of statistical characteristics for the query set, and outputting a query feature vector composed of the generated values of statistical characteristics; a comparison processor executing vector comparisons between the query feature vector and the plurality of stored reference feature vectors, and ranking the descriptors; a property descriptor selection processor selecting a best match descriptor based on the ranking of the descriptors; and a reconciled data manager adding the query set to a reconciled data storage unit.

Abstract: A data processing apparatus including a library, storing software services, each executing a data processing function; a user interface receiving commands, expressed in a language and defining a data processing target and a data processing request; and a parser. The parser extracting from each command: the request from the language; and the target. A knowledge base maintaining a record of the request and the target; a scheduler obtaining the request from the parser, and compiling a schedule to fulfill the request; a controller controlling execution of the schedule, the target being the input data to the execution, and to output a result; and a result processor obtaining the result, and, based on records of requests and targets, to identify a request candidate, and to output to the user as a selectable command in the language, via the user interface, the candidate with the result defined as a data processing target.

Abstract: A data property recognition apparatus, includes a storage unit; a model data acquisition processor acquiring a plurality of model sets of data entries, each data entry individually representing an identified property common to the model set and being of a data type common to the model set; a feature vector generation processor receiving an input set of data entries, recognizing a data type common to the input set of data entries from among a plurality of supported data types, selecting a set of statistical characteristics representing the input set of data entries in dependence upon the recognised data type, generating a value of each of the selected set of statistical characteristics from the input set of data entries, and outputting a feature vector composed of the generated values of statistical characteristics.

Abstract: A microservice-based data processing apparatus, including: a type register, storing a list of types, a type being a semantic concept expression; and microservices each comprising an annotation of an input type and output types from the list; processing logic transforming input data expressed by the input type into output data expressed by the output types; and a messaging mechanism for inputting data, via a message, to a microservice, the mechanism defining a message format for structuring the messages. The format includes a first field specifying the data being input; and a second field specifying a type, from the list of types, semantically expressing the concept instantiated by the data. Each microservice includes: a controller to receive a message from the mechanism having the format, and to respond by executing the logic when the type specified by the second field matches the input type of the microservice.