Abstract: Methods, systems, and computer program products for categorizing log records at run-time are provided herein. A computer-implemented method includes generating one or more template signatures to be associated with each of multiple templates, wherein each of the multiple templates comprises a concatenation of one or more words; processing each of multiple log records derived from a data stream to determine a composition of each of the multiple log records; matching one or more of the generated template signatures to each of the multiple log records based on the determined composition of each of the multiple log records; and outputting an identification of (i) each of the multiple log records and (ii) the one or more generated template signatures matched thereto.

Abstract: Methods, systems, and computer program products for organizing on-disk layout of index structures are provided herein. A method includes organizing an on-disk corpus of data index structures; partitioning each data index structure into an active and/or latest state data partition and an archived data partition; sub-partitioning each of the archived data partitions into sub-partitions based on exact lifespan of each data item; executing a search query that includes temporal predicates and keyword predicates across the corpus by: pruning a collection of identified items of data from the corpus that contain the keyword predicates using range metadata associated with the temporal predicates to generate a pruned list of data items; and performing a list intersection operation on the data index structures to generate a list of common data items from the pruned list; retrieving the common data items from the active and/or latest state data partitions and the archived data sub-partitions.

Abstract: Entity mappings that produce matching entities for a first data asset having attributes and a second data asset having attributes are generated by: generating entity mappings that produce matching entities for a first data asset having attributes with attribute values and a second data asset having attributes with attribute values by: matching the attribute values of the attributes of the first data asset with the attribute values of the attributes of the second data asset, using the matching attribute values to generate matching attribute pairs, and using the matching attribute pairs to identify entity mappings; computing an entity mapping score for each of the entity mappings based on a combination of factors; ranking the entity mappings based on each entity mapping score; and using some of the ranked entity mappings to determine whether a same real-world entity is described by the first data asset and the second data asset.

Abstract: Methods, systems, and computer program products for securely processing range predicates on cloud databases are provided herein. A computer-implemented method includes separately encrypting a set of plain text data using two or more encryption functions, thereby producing an encrypted domain comprising at least two distinct groups of encrypted data items; converting a range query over plain text data items into a query over at least one of the distinct groups of encrypted data items; and combining results from the query over the distinct groups of encrypted data items, thereby generating a final encrypted result to the range query.

Abstract: Methods and arrangements for discovering entity types for a set of records. A set of records is input, with each record comprising attributes with associated attribute values. The records are grouped into candidate entity types in view of at least one of: the attribute values of the records, at least one domain ontology and at least one dimension hierarchy. An interestingness measure of each candidate entity type is calculated, via estimating interestingness based on at least one factor selected from the group consisting of: a correlation between attribute values of records, a number of attributes, a log of queries issued to a server, and an average group size for candidate entity types. At least one candidate entity type is validated based on the calculated interestingness measures. Other variants and embodiments are broadly contemplated herein.

Abstract: Entity mappings that produce matching entities for a first data asset having attributes and a second data asset having attributes are generated by: generating entity mappings that produce matching entities for a first data asset having attributes with attribute values and a second data asset having attributes with attribute values by: matching the attribute values of the attributes of the first data asset with the attribute values of the attributes of the second data asset, using the matching attribute values to generate matching attribute pairs, and using the matching attribute pairs to identify entity mappings; computing an entity mapping score for each of the entity mappings based on a combination of factors; ranking the entity mappings based on each entity mapping score; and using some of the ranked entity mappings to determine whether a same real-world entity is described by the first data asset and the second data asset.

Abstract: Techniques, systems, and articles of manufacture for collaborative analytics with edge devices. A method includes identifying multiple items of data pertaining to a user from one or more user actions implemented across multiple user devices, identifying one or more rules associated with one or more user preferences, exchanging the multiple items of data across the multiple user devices, and applying the one or more rules to the multiple items of data across the multiple user devices to generate an output via at least one of the multiple user devices.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for identifying matching products relative to a reference product. A reference product is identified from a received product query and a query is generated based on the reference product. A generated query comprises of an ontology, at least one word appearing in a title of the reference product, and a set of key words appearing in social media data associated with the reference product. A database is searched using the generated query to find matching product sets and the results are returned and filtered. Results are filtered by calculating a relationship score between the reference product and one or more matching products in the set of matching products, and/or by filtering a subset of the set of matching products based on a customer profile. The filtered subset of results are communicated to a recipient.

Abstract: A method for supplementing structured information within a data system for entities based on unstructured data analyzes a document with unstructured data and extracts attribute values from the unstructured data for one or more entities of the data system. Entity records with structured information are retrieved from the data system based on the extracted attribute values. Entity references for corresponding entities of the data system are constructed based on a comparison of the retrieved entity records and the extracted attribute values. The entity references are linked to the corresponding entities within the data system, with the entity references including extracted attributes from the unstructured data for corresponding linked entities.

Abstract: Methods, systems, and computer program products for securely processing range predicates on cloud databases are provided herein. A computer-implemented method includes separately encrypting a set of plain text data using two or more encryption functions, thereby producing an encrypted domain comprising at least two distinct groups of encrypted data items; converting a range query over plain text data items into a query over at least one of the distinct groups of encrypted data items; and combining results from the query over the distinct groups of encrypted data items, thereby generating a final encrypted result to the range query.

Abstract: Methods, systems, and computer program products for distributed iceberg cubing over ordered dimensions are provided herein. A method includes calculating, from input data derived from a search query, a set of multiple cube measures for one or more combinations of multiple non-ordered dimensions; pruning the set of multiple cube measures based on one or more iceberg conditions to generate a sub-set of the cube measures; and determining a range for a set of ordered dimensions over a distributed processing platform based on (i) the sub-set of the cube measures and (ii) the one or more iceberg conditions.

Abstract: Methods and arrangements for measuring similarity with respect to moving object trajectories. First and second moving object trajectories are input, each trajectory being defined by at least two spatial dimensions and a temporal dimension. At least one segment is defined with respect to each trajectory, each segment being defined between two defining points. At least one segment from the first trajectory is matched with at least one segment from the second trajectory. A spatial distance and temporal distance are each computed between the at least one segment from the first trajectory and the at least one segment from the second trajectory. The spatial distance and temporal distance are combined to provide a measure of a spatio-temporal distance between the at least one segment from the first trajectory and the at least one segment from the second trajectory. Other variants and embodiments are broadly contemplated herein.

Abstract: Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalities across software products.

Abstract: Methods, systems, and computer program products for categorizing log records at run-time are provided herein. A computer-implemented method includes generating one or more template signatures to be associated with each of multiple templates, wherein each of the multiple templates comprises a concatenation of one or more words; processing each of multiple log records derived from a data stream to determine a composition of each of the multiple log records; matching one or more of the generated template signatures to each of the multiple log records based on the determined composition of each of the multiple log records; and outputting an identification of (i) each of the multiple log records and (ii) the one or more generated template signatures matched thereto.

Abstract: Entity mappings that produce matching entities for a first data asset having attributes and a second data asset having attributes are generated by: generating entity mappings that produce matching entities for a first data asset having attributes with attribute values and a second data asset having attributes with attribute values by: matching the attribute values of the attributes of the first data asset with the attribute values of the attributes of the second data asset, using the matching attribute values to generate matching attribute pairs, and using the matching attribute pairs to identify entity mappings; computing an entity mapping score for each of the entity mappings based on a combination of factors; ranking the entity mappings based on each entity mapping score; and using some of the ranked entity mappings to determine whether a same real-world entity is described by the first data asset and the second data asset.

Abstract: Entity mappings that produce matching entities for a first data asset having attributes and a second data asset having attributes are generated by: generating entity mappings that produce matching entities for a first data asset having attributes with attribute values and a second data asset having attributes with attribute values by: matching the attribute values of the attributes of the first data asset with the attribute values of the attributes of the second data asset, using the matching attribute values to generate matching attribute pairs, and using the matching attribute pairs to identify entity mappings; computing an entity mapping score for each of the entity mappings based on a combination of factors; ranking the entity mappings based on each entity mapping score; and using some of the ranked entity mappings to determine whether a same real-world entity is described by the first data asset and the second data asset.

Abstract: Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalties across software products.

Abstract: Methods, systems, and computer program products for organizing on-disk layout of index structures are provided herein. A method includes organizing an on-disk corpus of data index structures; partitioning each data index structure into an active and/or latest state data partition and an archived data partition; sub-partitioning each of the archived data partitions into sub-partitions based on exact lifespan of each data item; executing a search query that includes temporal predicates and keyword predicates across the corpus by: pruning a collection of identified items of data from the corpus that contain the keyword predicates using range metadata associated with the temporal predicates to generate a pruned list of data items; and performing a list intersection operation on the data index structures to generate a list of common data items from the pruned list; retrieving the common data items from the active and/or latest state data partitions and the archived data sub-partitions.

Abstract: Provided are techniques for providing personalized recommendations. One or more transactions are received from one or more customer interaction channels. The received one or more transactions are stored in an incremental data store. One or more predictive rules are generated based on the received one or more transactions and based on one or more transactions previously stored in the incremental data store. In real-time, one or more personalized recommendations specific to a user and to the received one or more transactions are generated using the one or more generated predictive rules.

Abstract: Techniques for segregating one or more logs of at least one multitasking user to derive at least one behavioral pattern of the at least one multitasking user are provided. The techniques include obtaining at least one of at least one action log, configuration information, domain knowledge, at least one task history and open task repository information, correlating the at least one of at least one action log, configuration information, domain knowledge, at least one task history and open task repository information to determine a task associated with each of one or more actions and segregate the one or more logs based on the one or more actions, and using the one or more logs that have been segregated to derive at least one behavioral pattern of the at least one multitasking user. Techniques are also provided for deriving intelligence from at least one activity log of at least one multitasking user to provide information to the at least one user.