Abstract: Methods, systems, and computer program products for extracting query-related temporal information from unstructured text documents are provided herein. A computer-implemented method includes obtaining at least one user query comprising one or more temporal components; converting at least a portion of the at least one user query into one or more logic form representations; mapping at least a portion of the one or more logic form representations to one or more portions of at least one source of unstructured text data; extracting temporal information, specific to the at least one user query, from one or more portions of the at least one source of unstructured text data based on the mapping; generating at least one response to the at least one user query based on the extracted temporal information; and performing one or more automated actions based on the at least one generated response.

Abstract: Methods, systems, and computer program products for partitioning and parallel loading of property graphs with constraints are provided herein. A computer-implemented method includes obtaining graph-related input data and corresponding constraint data, wherein the graph-related input data and corresponding constraint data are at least one of user-defined and input data model-based; generating at least one in-memory graph based at least in part on processing at least a portion of the obtained graph-related input data; partitioning the at least one in-memory graph into two or more sub-graphs by processing the at least one in-memory graph using one or more polynomial time partition algorithms; and generating at least one property graph by allocating, at least a portion of the two or more partitioned sub-graphs which satisfy the obtained constraint data, to two or more threads that run in parallel.

Abstract: In a method for deriving existential rules from knowledge graph data, a processor represents a knowledge graph using a geometric embedding. A processor transforms the geometric embedding to a syllogism logic representation using a geometric relationship. And a processor derives existential rules using standard transformation rules present in the syllogism logic representation.

Abstract: Methods, systems and computer program products for query processing are provided herein. A computer-implemented method includes receiving a first query from a user, determining whether the first query is capable of being answered using symbolic reasoning performed on data of a symbolic knowledge base, and executing the symbolic reasoning to generate a first query answer in response to a determination that the first query is capable of being answered using the symbolic reasoning. Axioms are extracted from a plurality of documents when it is determined that a second query is not capable of being answered using the symbolic reasoning. The method further includes determining whether the axioms are consistent with the symbolic knowledge base, and generating a second query answer based on the axioms in response to a determination that the one or more axioms are consistent with the symbolic knowledge base.

Abstract: Methods, systems, and computer program products for tracking missing data using provenance traces and data simulation are provided herein. A computer-implemented method includes generating, for each of multiple stages in a data curation sequence, a machine learning model of the data curation sequence, wherein the model is based on historical input records within the data curation sequence, historical output records within the data curation sequence, and provenance data within the data curation sequence; creating a simulated output record based on a detected anomaly corresponding to the data curation sequence; predicting the content of absent input records that precede the simulated output record in the data curation sequence and provenance data corresponding to the simulated output record; and outputting, to a user, in response to a query pertaining to the detected anomaly, the predicted input records and information relating the predicted input records to the detected anomaly.

Abstract: One embodiment provides a method, including utilizing at least one processor to execute computer code that performs the steps of: receiving, from a user, one or more keywords, wherein the one or more keywords identify, within a social media data set, a subset of social media data; determining, based on social media statistical information, an estimated volume of the subset of the social media data; determining, based on the social media statistical information, an estimated relevance of the subset of social media data to the user; and updating the one or more keywords, to improve the estimated volume and estimated relevance. Other aspects are described and claimed.

Abstract: Methods, systems and computer program products for query processing are provided herein. A computer-implemented method includes receiving a first query from a user, determining whether the first query is capable of being answered using symbolic reasoning performed on data of a symbolic knowledge base, and executing the symbolic reasoning to generate a first query answer in response to a determination that the first query is capable of being answered using the symbolic reasoning. Axioms are extracted from a plurality of documents when it is determined that a second query is not capable of being answered using the symbolic reasoning. The method further includes determining whether the axioms are consistent with the symbolic knowledge base, and generating a second query answer based on the axioms in response to a determination that the one or more axioms are consistent with the symbolic knowledge base.

Abstract: Methods, systems, and computer program products for tracking missing data using provenance traces and data simulation are provided herein. A computer-implemented method includes generating, for each of multiple stages in a data curation sequence, a machine learning model of the data curation sequence, wherein the model is based on historical input records within the data curation sequence, historical output records within the data curation sequence, and provenance data within the data curation sequence; creating a simulated output record based on a detected anomaly corresponding to the data curation sequence; predicting the content of absent input records that precede the simulated output record in the data curation sequence and provenance data corresponding to the simulated output record; and outputting, to a user, in response to a query pertaining to the detected anomaly, the predicted input records and information relating the predicted input records to the detected anomaly.

Abstract: One embodiment provides a method, including utilizing at least one processor to execute computer code that performs the steps of: receiving, from a user, one or more keywords, wherein the one or more keywords identify, within a social media data set, a subset of social media data; determining, based on social media statistical information, an estimated volume of the subset of the social media data; determining, based on the social media statistical information, an estimated relevance of the subset of social media data to the user; and updating the one or more keywords, to improve the estimated volume and estimated relevance. Other aspects are described and claimed.

Abstract: Systems and associated methods for address standardization and applications related thereto are described. Embodiments exploit a common context in a taxonomy and a given address to detect and correct deviations in the address. Embodiments establish a possible path from a root of the taxonomy to a leaf in the taxonomy that can possibly generate a given address. Given a new address, embodiments use complete addresses, and/or segments or elements thereof, to compute the representations of the elements and find a closest matching leaf in the taxonomy. Embodiments then traverse the path to a root node to detect the agreement and disagreement between the path and the address entry. Taxonomical structured is thus used to detect, segregate and standardize the expected fields.

Abstract: A clustering-based approach to data standardization is provided. Certain embodiments take as input a plurality of addresses, identify one or more features of the addresses, cluster the addresses based on the one or more features, utilize the cluster(s) to provide a data-based context useful in identifying one or more synonyms for elements contained in the address(es), and standardize the address(es) to an acceptable format, with one or more synonyms and/or other elements being added to or taken away from the input address(es) as part of the standardization process.

Abstract: Systems and associated methods for address standardization and applications related thereto are described. Embodiments exploit a common context in a taxonomy and a given address to detect and correct deviations in the address. Embodiments establish a possible path from a root of the taxonomy to a leaf in the taxonomy that can possibly generate a given address. Given a new address, embodiments use complete addresses, and/or segments or elements thereof, to compute the representations of the elements and find a closest matching leaf in the taxonomy. Embodiments then traverse the path to a root node to detect the agreement and disagreement between the path and the address entry. Taxonomical structured is thus used to detect, segregate and standardize the expected fields.