Abstract: A method for migrating an application includes representing the application as a vector including metadata about the application and at least one customer constraint, scoring a deviation of data consistency for the application related to each of a plurality of clouds, including a cloud in which the application is currently deployed and a plurality of potential target clouds, selecting one of the potential target clouds based on the scoring, wherein the selected cloud has an improved score over the cloud in which the application is current deployed, and migrating the application to the selected cloud.

Abstract: An approach for tuning a data management system is provided. A processor retrieves one or more samples pairs of record data. A processor determines an error rate regarding the performance of a matching operation of a data management system based on the one or more sample pairs. In response to the error rate being above a value, a processor adjusts at least one threshold value associated with the matching operation of the data management system.

Abstract: A multilevel clustered data set for multidimensional vectors is created by defining a plurality of clusters based on each of the signed dimensions of the vectors, each dimension functioning as an axis. Vectors are assigned to each cluster by measuring cosine similarity between a vector and each axis. Sub-clusters are defined as ranges of cosine similarity values within a cluster, and each vector is assigned into the appropriate range based on their cosine similarity value with the axis of the cluster. Searching for a matching vector to a new vector is efficiently achieved in near-constant time by measuring cosine similarity for the new vector with each axis to identify the closest cluster, reusing the cosine similarity of the new vector and axis to determine which sub-cluster corresponds to the appropriate range of values, and then comparing each vector within the sub-cluster until a match is found or ruled out.

Abstract: A method for migrating an application includes representing the application as a vector including metadata about the application and at least one customer constraint, scoring a deviation of data consistency for the application related to each of a plurality of clouds, including a cloud in which the application is currently deployed and a plurality of potential target clouds, selecting one of the potential target clouds based on the scoring, wherein the selected cloud has an improved score over the cloud in which the application is current deployed, and migrating the application to the selected cloud.

Abstract: A voice command can be received from a user. One or more voice command devices (VCDs) that the voice command is targeting can be determined. A visual indicator of each of the one or more targeted VCDs can be displayed on an XR device worn by the user, wherein each visual indicator visually indicates a respective targeted VCD the voice command is directed to on the XR device.

Abstract: Indexing and matching records in a data management system by defining entity indexing attributes associated with system records, receiving an incoming data entity, selecting a set of entity candidates according to the entity indexing attributes, matching the incoming entity to an entity candidate, generating an analysis of the entity candidate selection according to entity attribute effectiveness, and revising the entity indexing attributes according to the analysis.

Abstract: Matching records in an entity resolution system by defining entity attribute feature vectors, determining an entity attribute matching score according to a distance between two entity attribute feature vectors, assigning a statistical weight to an entity attribute matching score, adjusting the entity attribute matching score according to the statistical weight and an entity attribute frequency of occurrence, and determining an aggregate entity attribute matching score.

Abstract: A method provides for a field of view (FOV) of a smart contact lens of a user, such that the FOV includes a plurality of segments of the FOV. A device is identified from object recognition performed on image data from the smart contact lens and viewed within a first segment of the FOV. A key is transmitted to the device that includes credentials of the user of the smart contact lens to authenticate the user to the device that is viewed within the first segment of the FOV. A first level of access to the device is provided, based on viewing the device in the first segment of the FOV, and in response to changing the viewing of the device to a second segment of the FOV, providing a second level of access to the device associated with viewing the device in the second segment of the FOV.

Abstract: A method, apparatus, computer system, and computer program product for managing information. A set of bucket hashes and comparison information for a data record are identified by a computer system. The set of bucket hashes is generated from the comparison information, wherein the set of bucket hashes and the comparison information form a metadata record. A number of candidate metadata records in a metadata database is identified by the computer system using the set of bucket hashes, wherein the number of candidate metadata records comprises a set of candidate bucket hashes and candidate comparison information. An entity membership is identified by the computer system for the data record from a comparison of the comparison information in the metadata record with the candidate comparison information in the number of candidate metadata records.

Abstract: Embodiments include a computer-implemented method including identifying, by a primary computer device, a plurality of records, each record having one or more attributes; standardizing, by the primary computer device, each of the plurality of records; assigning, by the primary computer device, an index to one or more of the one or more attributes; providing, by the primary computer device, instructions for clustering the standardized plurality of records in parallel into one or more clusters, each cluster including records having the same index, the one or more clusters being in a group; receiving, by the primary computer device, one or more groups, each group including one or more clusters sharing a same index; and linking one or more of the plurality of records in a cluster with another one or more of the plurality of records in another cluster within a same group.

Abstract: A computer-implemented method increases the efficiency of matching records from two sources. The method includes identifying a first source and a second source wherein each of the sources include one or more records and each record includes one or more attributes. The method further includes determining, based on a corpus, the one or more attributes and generating, based on the attributes, a set of feature vectors which vectors represent the one or more attributes. The method includes comparing each record in the first source against each record in the second source. The method further includes generating, in response to the comparing, a link confidence. The method also includes linking, in response to the link confidence being above a linking threshold, the associated records. The method includes determining a first feature vector of the set of feature vectors used in the linking, and outputting a set of results.

Abstract: Analyzing entity matching systems by determining autolink (AL) and clerical review (CR) threshold values according to record pair compare method scores, defining a score region of interest adjacent to at least one of the AL or CR thresholds, identifying anomalous pairs in at least one region of interest, and providing at least one anomalous record pair to a user for review.

Abstract: Methods, computer program products and/or systems are provided that perform the following operations: obtaining payload attribute fields; determining potential matching fields from the payload attribute fields; determining a matching function for each of the potential matching fields; determining an attribute score for each of the potential matching fields based on the matching function; obtaining a score list for a reference data set; determining a correlation of the attribute score for each of the potential matching fields with the reference data set score list; selecting new matching fields from the potential matching fields based at least in part on the correlation; determining an optimal weight for each of the selected new matching fields; selecting attribute fields for matching from the selected new matching fields based on a threshold rate for false positives and false negatives; and providing the attribute fields for matching and the associated optimal weight for the attribute fields.

Abstract: The present disclosure relates to a method for a secure storage, matching and linking of data records. The method comprises: receiving a current data record having one or more attributes, each attribute having an attribute value. For each attribute of at least part of the attributes a predefined set of variations of the attribute value of the attribute may be generated. The received attribute values may be encrypted resulting in an encrypted record and the generated sets of variations may be encrypted. The encrypted record may be stores in a storage system in association with the respective encrypted sets of variations.

Abstract: A method provides for a field of view (FOV) of a smart contact lens of a user, such that the FOV includes a plurality of segments of the FOV. A device is identified from object recognition performed on image data from the smart contact lens and viewed within a first segment of the FOV. A key is transmitted to the device that includes credentials of the user of the smart contact lens to authenticate the user to the device that is viewed within the first segment of the FOV. A first level of access to the device is provided, based on viewing the device in the first segment of the FOV, and in response to changing the viewing of the device to a second segment of the FOV, providing a second level of access to the device associated with viewing the device in the second segment of the FOV.

Abstract: Matching records in an entity resolution system by defining entity attribute feature vectors, determining an entity attribute matching score according to a distance between two entity attribute feature vectors, assigning a statistical weight to an entity attribute matching score, adjusting the entity attribute matching score according to the statistical weight and an entity attribute frequency of occurrence, and determining an aggregate entity attribute matching score.

Abstract: Techniques for data evaluation are provided. A plurality of data records is received, and a first comparison vector is generated by comparing a first and a second data record of the plurality of data records, where the first comparison vector indicates differences between the first and second data records. A machine learning model is trained based at least in part on the first comparison vector. The plurality of data records is evaluated using the machine learning model, and at least two of the plurality of data records are linked based on the evaluation.

Abstract: Securely matching encrypted entities by receiving data, segmenting the data into a plurality of categories, selecting encryption key(s) according to a data category of the plurality of data categories, encrypting the data of the data category using the encryption key(s), and comparing the encrypted data to previously encrypted data of the data category.

Abstract: A multilevel clustered data set for multidimensional vectors is created by defining a plurality of clusters based on each of the signed dimensions of the vectors, each dimension functioning as an axis. Vectors are assigned to each cluster by measuring cosine similarity between a vector and each axis. Sub-clusters are defined as ranges of cosine similarity values within a cluster, and each vector is assigned into the appropriate range based on their cosine similarity value with the axis of the cluster. Searching for a matching vector to a new vector is efficiently achieved in near-constant time by measuring cosine similarity for the new vector with each axis to identify the closest cluster, reusing the cosine similarity of the new vector and axis to determine which sub-cluster corresponds to the appropriate range of values, and then comparing each vector within the sub-cluster until a match is found or ruled out.

Abstract: A method for relating different types of records. The method may include providing comparison functions, wherein each comparison function corresponds to a semantical class, and wherein a computational cost is associated with each comparison function. The method may include determining one or more attribute pairs between the different types of records. The method may include sorting the comparison functions according to a determined accuracy. The method may include selecting a set of comparison functions associated with semantical classes according to a predefined rule. The method may include determining a total computational cost based on the computational cost of the selected set of comparison functions. The method may include determining whether two or more records are related using the selected set of comparison functions. The method may include relating the two or more records. The method may include determining a rate of false negative records.