International Business Machines Corporation

Udit Sharma

L Venkata Subramaniam

Hima Prasad Karanam

Shajith I Mohamed

Sumit Neelam

Santosh Srivastava

Ramasuri Narayanam

Gyana Ranjan Parija

Manish Kataria

Sumit Bhatia

Rakesh Rameshrao Pimplikar

Systems and techniques that facilitate question answering via tailored knowledge induction are provided. In various embodiments, a system can access a natural language question. In various aspects, the system can identify an answer for the natural language question, based on a tailored knowledge graph iteratively generated from a set of structured sub-queries associated with the natural language question.

Question answering via tailored knowledge induction

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.

Extracting query-related temporal information from unstructured text documents

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.

Partitioning and parallel loading of property graphs with constraints

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.

System and method for approximate reasoning using ontologies and unstructured data

Methods, systems, and computer program products for a collaborative cognition platform for creating and hosting social machines are provided herein. A computer-implemented method includes creating a social machine for collaborative tasks, wherein the social machine comprises (i) one or more human agents, (ii) one or more machine-based agents, (iii) an algorithm, and (iv) a set of rules prescribed for executing the collaborative tasks. The method also includes generating one or more collaborative resolutions for the collaborative tasks by executing, in an automated fashion, the collaborative tasks via implementation of the algorithm, wherein the algorithm facilitates, in accordance with the set of rules, systematic iterations of collaboration among (i) the one or more human agents and (ii) the one or more machine-based agents. Further, the method includes outputting the one or more collaborative resolutions to at least one user.

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Udit Sharma