Abstract: Data records are linked across a plurality of datasets. Each dataset contains at least one data record, and each data record is associated with an entity and includes one or more attributes of that entity and a value for each attribute. Values associated with attributes are compared across datasets, and matching attributes having values that satisfy a predetermined similarity threshold are identified. In addition, linkage points between pairs of datasets are identified. Each linkage point links one or more pairs of data records. Each data record in the pair of data records is contained in one of a given pair of datasets, and each pair of data records is associated with a common entity having matching attributes in the given pair of datasets. Data records associated with the common entities are linked across datasets using the identified linkage points.

Abstract: Data records are linked across a plurality of datasets. Each dataset contains at least one data record, and each data record is associated with an entity and includes one or more attributes of that entity and a value for each attribute. Values associated with attributes are compared across datasets, and matching attributes having values that satisfy a predetermined similarity threshold are identified. In addition, linkage points between pairs of datasets are identified. Each linkage point links one or more pairs of data records. Each data record in the pair of data records is contained in one of a given pair of datasets, and each pair of data records is associated with a common entity having matching attributes in the given pair of datasets. Data records associated with the common entities are linked across datasets using the identified linkage points.

Abstract: Methods, systems, and computer program products for entity structured representation and variant generation are provided herein. A computer-implemented method includes automatically parsing instances of a given entity type into semantic components by implementing a parser based at least in part on (i) the given entity type and (ii) items of information relevant to the given entity type; generating, based at least in part on (i) the semantic components and (ii) information pertaining to one or more valid component-specific variants, one or more variants of the semantic components; creating, based at least in part on the one or more variants of the one or more semantic components, one or more variants of at least one instance of an entity associated with the given entity type; and outputting, to at least one user, the one or more variants of the at least one instance of the entity.

Abstract: Methods, systems, and computer program products for entity structured representation and variant generation are provided herein. A computer-implemented method includes automatically parsing instances of a given entity type into semantic components by implementing a parser based at least in part on (i) the given entity type and (ii) items of information relevant to the given entity type; generating, based at least in part on (i) the semantic components and (ii) information pertaining to one or more valid component-specific variants, one or more variants of the semantic components; creating, based at least in part on the one or more variants of the one or more semantic components, one or more variants of at least one instance of an entity associated with the given entity type; and outputting, to at least one user, the one or more variants of the at least one instance of the entity.

Abstract: Described herein are methods, systems and computer program products for entity resolution. Entity resolution, also known as entity matching or record linkage, seeks to identify equivalent data objects between or among datasets. An example method includes creating a deterministic model by defining an entity to be resolved, selecting two datasets for comparison, defining matching predicates for attributes of the datasets to select a set of candidate matches, and defining a precedence rule for the candidate matches to select a subset of the candidate matches. The method includes running the deterministic model on the two datasets. Running the deterministic model includes applying the matching predicates and the precedence rule to data in the datasets that correspond to the attributes. The method also includes applying a cardinality rule to results of the running, and outputting the matching candidates for which the cardinality rule is satisfied.

Abstract: Embodiments of the present invention relate to a declarative framework for efficient incremental information integration. In one embodiment, a method of and computer program product for information integration is provided. An integration rule is received. A first data set is accessed. A first representation of the first data is generated set based on the plurality of integration rules. The first representation is flat and includes a plurality of records. At least one index is generated. The index encodes at least one hierarchical relationship among the plurality of records. A second representation is generated of the first representation based on the at least one index. The second representation comprising nested data.

Abstract: Embodiments relate to entity resolution. One aspect includes creating a deterministic model by defining an entity to be resolved, selecting two datasets for comparison, defining matching predicates for attributes of the datasets to select a set of candidate matches, and defining a precedence rule for the candidate matches to select a subset of the candidate matches. An aspect further includes running the deterministic model on the two datasets. Running the deterministic model includes applying the matching predicates and the precedence rule to data in the datasets that correspond to the attributes. An aspect also includes applying a cardinality rule to results of the running, and outputting the matching candidates for which the cardinality rule is satisfied.

Abstract: Embodiments of the present invention relate to a declarative framework for efficient incremental information integration. In one embodiment, a method of and computer program product for information integration is provided. An integration rule is received. A first data set is accessed. A first representation of the first data is generated set based on the plurality of integration rules. The first representation is flat and includes a plurality of records. At least one index is generated. The index encodes at least one hierarchical relationship among the plurality of records. A second representation is generated of the first representation based on the at least one index. The second representation comprising nested data.

Abstract: A method and system for specifying, in a schema mapping framework, a mapping between a source schema and a target schema. The source and target schemas are schemas included in respective groups of registered, heterogeneous schemas. The source and target schemas may be of different types. Serialized versions of the source and target schemas include source objects and target objects, respectively. A mapping model is serialized into mapping objects that include logical references representing the source objects and logical references representing the target objects. The logical references are resolved to the source objects and target objects, thereby storing pointers to the source objects and to the target objects. After resolving the logical references, the mapping model includes the logical references and the pointers to the source and target objects.

Abstract: A method and system for generating a query implementing a schema mapping. A mapping M is provided from a schema S to a schema T, where M relates S to T, and M includes a plurality of constraints. Schemas S and T each include one or more elements, and T includes at least one set type element. Mapping M is expressed in terms of at least one nested tuple-generating dependency. A query Q is generated where Q is capable of applying M to an input instance I to result in an output instance J, where I conforms to S, J conforms to T, and I and J satisfy the plurality of constraints. Instance J is in partitioned normal form (i.e., satisfies minimal union semantics) and includes no duplicate element instances.

Abstract: Techniques are provided for viewing mappings between objects. A main view is displayed, wherein the main view shows one or more source objects, one or more target objects, and zero or more mappings between the one or more source objects and the one or more target objects. Input selecting a type of view to be displayed in the main view is received, wherein each type of view provides a different amount of detail regarding the mappings. In response to receiving the input, the selected type of view is created, and the created view is displayed. Additionally, techniques are provided for viewing objects. One or more objects along with mappings between the one or more objects are displayed. View filters are provided that may be applied to the one or more objects, wherein the view filters enable hiding at least one of mapped or unmapped objects. Moreover, techniques are provided for viewing nodes. A structure is displayed that includes one or more nodes.

Abstract: Various embodiments of a method, system and article of manufacture to discover relationships among a first set of elements and a second set of elements are provided. At least one metric algorithm is identified based on a metric selection parameter. A raw result is determined based on the at least one metric algorithm, a first specified structural description of the first set of elements and a second specified structural description of the second set of elements. The raw result comprises a plurality of relationship measurements and the raw result is ordered. In some embodiments, a balanced result is produced based on the raw result and a matching strategy algorithm. In other embodiments, the matching strategy algorithm is identified based on a matching strategy selection parameter.