Abstract: Techniques for predicting an impact of one or more events on service demand are disclosed. Some embodiments include first and second sets of data characterising properties of historic events using metadata tags, and demand for services that are then filtered to distinguish ordinary demand from extra-ordinary demand. Machine learning is used to determine correlations between metadata tags and extra-ordinary demand to produce a third data set operable for predictive determinations of future event impact on service demand.

Abstract: The present disclosure relates to a method for a weighting graph comprising nodes representing entities and edges representing relationships between entities in accordance with one or more domains. The method comprises: pre-processing the graph comprising assigning weights to the nodes and/or the edges of the graph in accordance with a specific domain of the domains, wherein the weight indicates a domain specific data quality problem of attribute values representing an edge of the edges and/or an entity involved in that edge. The weighted graph may be provided for enabling a processing of the graph in accordance with the specific domain.

Abstract: In an approach, a processor receives an unstructured text document. A processor extracts at least one unrecognized token from the unstructured text document. A processor identifies at least one structured data element in a predefined set of data sources, where the at least one structured data element is related to the at least one extracted unrecognized token from the unstructured text document. A processor relates a label associated with the identified at least one structured data element to the unstructured text document.

Abstract: Methods, computer program products and/or systems are provided that perform the following operations: obtaining a first graph comprising first nodes representing first entities and first edges representing relationships between first entities, the first nodes being associated with first entity attributes descriptive of the first entities represented by the first nodes, the first edges being associated with first edge attributes descriptive of the relationships represented by the first edges; determining a first subgraph for a certain node of the first nodes of the first graph, the first subgraph including the certain node and at least one neighboring node of the certain node; and determining a data quality issue regarding the certain node based, at least in part, on applying one or more applicable rules of a set of data quality rules to first entity attribute values and first edge attribute values of the first subgraph.

Abstract: Embodiments of the present invention determines duplicates in a graph. The graph comprises nodes representing entities and edges representing relationships between the entities. The method comprises: identifying at least two nodes in the graph. A neighborhood subgraph may be determined for each of the two nodes. The neighborhood subgraph includes the respective node. The method further comprises determining whether the two nodes are duplicates with respect to each other, based on a result of a comparison between the two subgraphs.

Abstract: Techniques for predicting an impact of one or more events on service demand are disclosed. Some embodiments include first and second sets of data characterising properties of historic events using metadata tags, and demand for services that are then filtered to distinguish ordinary demand from extra-ordinary demand. Machine learning is used to determine correlations between metadata tags and extra-ordinary demand to produce a third data set operable for predictive determinations of future event on service demand.

Abstract: Methods, computer program products and/or systems are provided that perform the following operations: obtaining a first graph comprising first nodes representing first entities and first edges representing relationships between first entities, the first nodes being associated with first entity attributes descriptive of the first entities represented by the first nodes, the first edges being associated with first edge attributes descriptive of the relationships represented by the first edges; determining a first subgraph for a certain node of the first nodes of the first graph, the first subgraph including the certain node and at least one neighboring node of the certain node; and determining a data quality issue regarding the certain node based, at least in part, on applying one or more applicable rules of a set of data quality rules to first entity attribute values and first edge attribute values of the first subgraph.

Abstract: A method, system and computer program product for classifying a data collection of data of a predefined domain. A hierarchical representation scheme describing terms of the domain and one or more relationships between the terms is provided. At least one classifier may be applied on the data collection, resulting in a set of term assignments. Each term assignment of the term assignments associates a term candidate with a respective confidence value to the collection or to one or more data items of the collection. At least one of the term assignments may be refined based on the representation scheme and the set of term assignments.

Abstract: A computer device identifies a set of documents for classification. The computing device classifies documents of a first subset of the set of documents based, at least in part, on a text analysis of the documents of the first subset. The computing device trains a document classifier using, as training data: (i) results of the classifying of the documents of the first subset, and (ii) metadata associated with the documents of the first subset. The computing device classifies documents of a second subset of the set of documents by providing metadata of the documents of the second subset to the trained document classifier.

Abstract: The present disclosure relates to a method for a weighting graph comprising nodes representing entities and edges representing relationships between entities in accordance with one or more domains. The method comprises: pre-processing the graph comprising assigning weights to the nodes and/or the edges of the graph in accordance with a specific domain of the domains, wherein the weight indicates a domain specific data quality problem of attribute values representing an edge of the edges and/or an entity involved in that edge. The weighted graph may be provided for enabling a processing of the graph in accordance with the specific domain.

Abstract: Embodiments of the present invention determines duplicates in a graph. The graph comprises nodes representing entities and edges representing relationships between the entities. The method comprises: identifying at least two nodes in the graph. A neighborhood subgraph may be determined for each of the two nodes. The neighborhood subgraph includes the respective node. The method further comprises determining whether the two nodes are duplicates with respect to each other, based on a result of a comparison between the two subgraphs.

Abstract: A method, system and computer program product for classifying a data collection of data of a predefined domain. A hierarchical representation scheme describing terms of the domain and one or more relationships between the terms is provided. At least one classifier may be applied on the data collection, resulting in a set of term assignments. Each term assignment of the term assignments associates a term candidate with a respective confidence value to the collection or to one or more data items of the collection. At least one of the term assignments may be refined based on the representation scheme and the set of term assignments.

Abstract: An access system for a vehicle may include a controller. The controller may be configured to respond to receiving an unlock signal indicative of an unlock request by causing a compartment closure to unlock for a predetermined time. Or the controller may be configured to respond to receiving an unlock signal indicative of an unlock request and a vehicle operation signal indicative of a vehicle secure state by causing a compartment closure to unlock for a predetermined time. Upon expiration of the predetermined time, the controller may cause the compartment closure to lock. The controller may be configured to respond to receiving an unlatch signal indicative of an unlatch request during the predetermined time by causing the compartment closure to unlatch.

Abstract: A device for monitoring signal levels of signals that are generated, for the purpose of detecting a magnetic field, by a plurality of Hall sensors includes a first, second, and third input and a diagnostic device. The first input is configured to receive a first signal from a first Hall sensor. A first electrical resistor is connected between the first input and a central point. The second input is configured to receive a second signal from a second Hall sensor. A second electrical resistor is connected between the second input and the central point. The third input is configured to receive a third signal from a third Hall sensor. A third electrical resistor is connected between the third input and the central point. The diagnostic device is connected to the central point and is configured to determine a position of the detected magnetic field using an average value.

Abstract: An access system for a vehicle may include a controller. The controller may be configured to respond to receiving an unlock signal indicative of an unlock request by causing a compartment closure to unlock for a predetermined time. Or the controller may be configured to respond to receiving an unlock signal indicative of an unlock request and a vehicle operation signal indicative of a vehicle secure state by causing a compartment closure to unlock for a predetermined time. Upon expiration of the predetermined time, the controller may cause the compartment closure to lock. The controller may be configured to respond to receiving an unlatch signal indicative of an unlatch request during the predetermined time by causing the compartment closure to unlatch.

Abstract: A method, computer program product, and system for information governance crowd sourcing by, responsive to receiving a data quality exception identifying one or more data quality errors in a data store, identifying a performance level required to correct the data quality errors, selecting, from a crowd hierarchy, a first one or more crowds meeting the defined performance level, wherein the crowd hierarchy ranks the performance of one or more crowds, and routing, by operation of one or more computer processors, the one or more data quality errors to the selected crowds for correction.

Abstract: Embodiments relate to cache handling in a database system. An aspect includes controlling operations of a set of caches in the database system and determining whether a value of a cache quality parameter of a first cache out of the set of caches meets a cache image creation criterion relating to the first cache. Moreover, an aspect includes selecting at least one cache entry from the first cache, if a value of a related cache entry parameter meets a cache entry criterion, and if the value of the cache quality parameter of the first cache exceeds the predefined value of the cache image creation criterion, and creating a cache image based on the selected at least one cache entry and storing the cache image for further use.

Abstract: A method, computer program product, and system for information governance crowd sourcing by, responsive to receiving a data quality exception identifying one or more data quality errors in a data store, identifying a performance level required to correct the data quality errors, selecting, from a crowd hierarchy, a first one or more crowds meeting the defined performance level, wherein the crowd hierarchy ranks the performance of one or more crowds, and routing, by operation of one or more computer processors, the one or more data quality errors to the selected crowds for correction.

Abstract: A device for monitoring signal levels of signals that are generated, for the purpose of detecting a magnetic field, by a plurality of Hall sensors includes a first, second, and third input and a diagnostic device. The first input is configured to receive a first signal from a first Hall sensor. A first electrical resistor is connected between the first input and a central point. The second input is configured to receive a second signal from a second Hall sensor. A second electrical resistor is connected between the second input and the central point. The third input is configured to receive a third signal from a third Hall sensor. A third electrical resistor is connected between the third input and the central point. The diagnostic device is connected to the central point and is configured to determine a position of the detected magnetic field using an average value.

Abstract: A method for monitoring the signal levels of signals that are generated, for the purpose of detecting a magnetic field, by a plurality of Hall sensors, includes determining an average value of the signal levels. The method further includes comparing a progression of the average value with an expected progression of the average value. The expected progression includes a characteristic temporal sequence of a first value and at least a second value that differs from the first value. An error message is provided if the average value deviates from the expected progression by more than a tolerance range.