Abstract: In an approach to generating and using a sentence model for answer generation, one or more computer processors ingest a first corpus of a plurality of text sentences. One or more computer processors convert the plurality of text sentences into a plurality of sentence vectors. One or more computer processors group the plurality of sentence vectors into a plurality of sentence clusters, wherein a sentence cluster is composed of sentences that are semantically similar. One or more computer processors receive a second corpus. One or more computer processors determine, for each sentence cluster of the plurality of sentence clusters, a frequency each sentence cluster appears in the second corpus. Based on the determined frequency, one or more computer processors calculate a probability of each sentence cluster of the plurality of sentence clusters. Based on the calculated probabilities, one or more computer processors generate a first sentence model.

Abstract: A system for inspecting flexible pipelines comprises a data analyzer, a data collector and an ultrasonic transducer. Further, the ultrasonic transducer is adapted to propagate shear wave into the annulus of the flexible pipeline. The data collector further comprises a data store and a communicator. Further, the system is capable of differentiating flooding and non-flooding condition of the annulus of the flexible pipeline which is subjected to high pressure. Using the system, an indicator of a flooded or non-flooded condition within the flexible pipeline may be calculated using transmitted and detected reflective waves or the lack of detected reflective waves.

Abstract: A method, system, and computer-usable medium are disclosed for identifying areas to improve an interactive conversational system, such as a chatbot. A stream of stream of conversational interactions C (C1, C2, . . . , Cn) between users and the interactive conversational system is received. An intent clustering model is periodically applied to the stream to form an incremental clustering based on a set of derived intents to form a mapping from a first set of conversational characteristics to a first set of intents and a second set of conversational characteristics to a first set of unclear intents. Information is provided related to the second set of conversation characteristics.

Abstract: An approach is provided that receives a question at a question-answering (QA) system. A number of passages are identified that are relevant to the received question. A question knowledge graph is generated that corresponds to the question and a set of passage knowledge graphs are also generated with each passage knowledge graph corresponding to one of the identified passages. Each of the passage knowledge graphs are compared to the question knowledge graph with the comparison resulting in a set of knowledge graph candidate answers (kgCAs). A set of candidate answers (CAs) is computed by the QA with at least one of the CAs being based on one of the kgCAs.

Abstract: The invention relates to the field of special purpose robotic systems to conduct external functions such as cleaning, monitoring and inspection of structures such as tubular assets in a splash zone. The splash zone is defined as the section of a marine structure that is periodically in and out of water due to the action of waves or tides, usually falling within (+)10m to (?)20m water depth. In embodiments, splash zone inspection robot system 1 comprises station 300, submersible saddle 350, submersible robot 400, and subsea robot controller 308. A predetermined set of controllable clamps selectively secure submersible robot 400 to submersible saddle 350 or structure 2 and allow incremental traversal along submersible saddle 350 or structure 2.

Abstract: Seal assembly 100, useful for repairing an uncontrolled surface such as pipeline 110, comprises seal 102 which is subjected to pressure and temperature and remains operable under, e.g., subsea conditions. Seal assembly 100 is capable of sealing pipelines of diameters up to 48 inches. Seal assembly 100 is actuated/energized by axially compressing/loading seal assembly 100 between one or more controlled surfaces and an uncontrolled surface and can be used for repairing and providing sealing in flowline or pipelines of either subsea or other petrochemical industries where the pipelines. Spool assembly 700 comprising seal assembly 100 may be used to repair a damaged pipeline section after the damaged section is removed to provide a sealed replacement fluid path for the pipeline.

Abstract: Seal assembly 100, useful for repairing an uncontrolled surface such as pipeline 110, comprises seal 102 which is subjected to pressure and temperature and remains operable under, e.g., subsea conditions. Seal assembly 100 is capable of sealing pipelines of diameters up to 48 inches. Seal assembly 100 is actuated/energized by axially compressing/loading seal assembly 100 between one or more controlled surfaces and an uncontrolled surface and can be used for repairing and providing sealing in flowline or pipelines of either subsea or other petrochemical industries where the pipelines. Spool assembly 700 comprising seal assembly 100 may be used to repair a damaged pipeline section after the damaged section is removed to provide a sealed replacement fluid path for the pipeline.

Abstract: Embodiments are directed to a system, a computer program product, and a method for identification of linguistically related elements, and more specifically to prediction of a linguistically related element. A linguistic algorithm forms a cluster representation of corpus entries. A linguistic term is identified and applied to the cluster representation to identify proximally related linguistic terms. Associative relationships between the proximally related terms and category metadata are iteratively investigated. One or more linguistic terms related across the two more metadata categories is identified and designated as the linguistically related element.

Abstract: In an approach to generating and using a sentence model for answer generation, one or more computer processors ingest a first corpus of a plurality of text sentences. One or more computer processors convert the plurality of text sentences into a plurality of sentence vectors. One or more computer processors group the plurality of sentence vectors into a plurality of sentence clusters, wherein a sentence cluster is composed of sentences that are semantically similar. One or more computer processors receive a second corpus. One or more computer processors determine, for each sentence cluster of the plurality of sentence clusters, a frequency each sentence cluster appears in the second corpus. Based on the determined frequency, one or more computer processors calculate a probability of each sentence cluster of the plurality of sentence clusters. Based on the calculated probabilities, one or more computer processors generate a first sentence model.

Abstract: A method, system, and computer-usable medium are disclosed for identifying areas to improve an interactive conversational system, such as a chatbot. A stream of stream of conversational interactions C (C1, C2, . . . , Cn) between users and the interactive conversational system is received. An intent clustering model is periodically applied to the stream to form an incremental clustering based on a set of derived intents to form a mapping from a first set of conversational characteristics to a first set of intents and a second set of conversational characteristics to a first set of unclear intents. Information is provided related to the second set of conversation characteristics.

Abstract: A computer-implemented method of executing a virtual agent bot includes receiving, via a computer server, at least one input query from a user, and analyzing the at least one input query to extract at least one input term. The method further comprises determining a semantic skill set of the virtual agent bot among a plurality of different candidate skill sets based at least in part on the at least one input term; and invoking the virtual agent bot to provide a semantic topic response corresponding to the semantic skill set to provide an answer to the at least one input query.

Abstract: A system for inspecting flexible pipelines comprises a data analyzer, a data collector and an ultrasonic transducer. Further, the ultrasonic transducer is adapted to propagate shear wave into the annulus of the flexible pipeline. The data collector further comprises a data store and a communicator. Further, the system is capable of differentiating flooding and non-flooding condition of the annulus of the flexible pipeline which is subjected to high pressure. Using the system, an indicator of a flooded or non-flooded condition within the flexible pipeline may be calculated using transmitted and detected reflective waves or the lack of detected reflective waves.

Abstract: A system for inspecting flexible pipelines comprises a data analyzer, a data collector and an ultrasonic transducer. Further, the ultrasonic transducer is adapted to propagate shear wave into the annulus of the flexible pipeline. The data collector further comprises a data store and a communicator. Further, the system is capable of differentiating flooding and non-flooding condition of the annulus of the flexible pipeline which is subjected to high pressure. Using the system, an indicator of a flooded or non-flooded condition within the flexible pipeline may be calculated using transmitted and detected reflective waves or the lack of detected reflective waves.

Abstract: A system for inspecting flexible pipelines comprises a data analyzer, a data collector and an ultrasonic transducer. Further, the ultrasonic transducer is adapted to propagate shear wave into the annulus of the flexible pipeline. The data collector further comprises a data store and a communicator. Further, the system is capable of differentiating flooding and non-flooding condition of the annulus of the flexible pipeline which is subjected to high pressure. Using the system, an indicator of a flooded or non-flooded condition within the flexible pipeline may be calculated using transmitted and detected reflective waves or the lack of detected reflective waves.

Abstract: A computer-implemented method of executing a virtual agent bot includes receiving, via a computer server, at least one input query from a user, and analyzing the at least one input query to extract at least one input term. The method further comprises determining a semantic skill set of the virtual agent bot among a plurality of different candidate skill sets based at least in part on the at least one input term; and invoking the virtual agent bot to provide a semantic topic response corresponding to the semantic skill set to provide an answer to the at least one input query.

Abstract: An approach is provided that selects an original entity from an original knowledge graph. The approach then accesses a data source that is external to the original knowledge graph, such as an online encyclopedia. An entity in the data source is identified based on the entity matching the original entity. A new relation is then identified in the data source between the identified entity and a new entity with the new entity being absent from the original knowledge graph. An expanded knowledge graph is then generated with the expanded knowledge graph formed by adding the new entity to the original knowledge graph.

Abstract: An approach is provided that receives a question at a question-answering (QA) system. A number of passages are identified that are relevant to the received question. A question knowledge graph is generated that corresponds to the question and a set of passage knowledge graphs are also generated with each passage knowledge graph corresponding to one of the identified passages. Each of the passage knowledge graphs are compared to the question knowledge graph with the comparison resulting in a set of knowledge graph candidate answers (kgCAs). A set of candidate answers (CAs) is computed by the QA with at least one of the CAs being based on one of the kgCAs.

Abstract: An approach is provided that receives a question at a question answering (QA) system. The question includes a number of words. The approach operates by calculating weights that correspond to search terms included in the plurality of words. The search terms include the plurality of words and may include terms that are one or more sequences of adjacent words included in the question. Based on the calculated weights and the words in the question, the approach generates a query that is used to search a corpus that is managed by the QA system with the search resulting in one or more search results.

Abstract: An approach is provided that receives a question at a question answering (QA) system. The question includes a number of words. The approach operates by calculating weights that correspond to search terms included in the plurality of words. The search terms include the plurality of words and may include terms that are one or more sequences of adjacent words included in the question. Based on the calculated weights and the words in the question, the approach generates a query that is used to search a corpus that is managed by the QA system with the search resulting in one or more search results.

Abstract: Embodiments are directed to a system, computer program product, and method for identification of linguistically related elements, and more specifically to prediction of a linguistically related element. A linguistic algorithm forms a cluster representation of corpus entries. A linguistic term is identified and application to the cluster representation to identified proximally related linguistic terms. Associative relationships between the proximally related terms and category metadata are iteratively investigated. One or more linguistic terms related across the two more metadata categories is identified and designated at the linguistically related element.