Abstract: An information processing system, a computer readable storage medium, and a computer-implemented method, collect tables from a corpus of documents, convert the collected tables to flattened table format and organized to be searchable by schema-less queries. A method collects tables, extracts feature values from collected table data and collected table meta-data for each collected table. A table classifier classifies each collected table as being a type of table. Based on the classifying, the collected table is converted to a flattened table including table values that are the table data and the table meta-data of the collected table. Dependencies of the data values are mapped. The flattened table and mapped dependencies are stored in a triple store searchable by schema-less queries. The table classifier learns and improves its accuracy and reliability. Dependency information is maintained among a plurality of database tables. The dependency information can be updated at variable update frequency.

Abstract: A system and a computer-implemented method for ranking tabular data entities by likelihood of comprising answers for (natural language) queries, based on multimodal descriptions of the tabular data entities, comprising separate representations, which represent different aspects of the tabular data entities. The ranking is based on joint representations, generated from the query representation and separate representations of the tabular data entities' aspects, using gated multimodal units. The computer-implemented method may be used for applications such as web searches, data aggregation, and research tasks.

Abstract: A resource exploitation management system, method and a computer program product therefor. A description of new geological evidence for a geological resource is received, e.g., as one or more triples describing the evidence. Keywords in the description are matched against keywords in representations in a geological resource database. Geological relations are inferred from the descriptions and matched against predefined geological relations from the geological resource database. Consistent triple matches are merged with the geological resource database. The confidence level for merged matches is updated in the geological resource database.

Abstract: A system for ranking machine learning base models for transfer learning purposes is described. The system receives image data in the form an image or an image set and extracts image tags from the images. The image tags are expanded into a set of associated terms using a word embedding database and model. The associated terms are used to query a knowledge database for parent or categorical terms used to rank various matching machine learning base models that may be improved or trained by the image data.

Abstract: Mechanisms are provided for conducting a natural language dialogue between the automatic dialogue system and a user of a client computing device. An automatic dialogue system receives natural language text corresponding to a user input from the user via the client computing device, the natural language text having an ambiguous portion of natural language text. The automatic dialogue system analyzes user profile information corresponding to the user to identify an anomaly in the user profile information and predicts a user intent associated with the anomaly. The automatic dialogue system disambiguates the ambiguous portion of the natural language text based on the predicted user intent and generates a response to the user input based on the disambiguated natural language text which is output to the client computing device to thereby conduct the natural language dialogue.

Abstract: Mechanisms are provided for customizing responses to future questions based on identified anomalies in user profile information. An automated dialogue system monitors information associated with a plurality of entities, where the information includes quantities for variable values associated with the entities. The automated dialogue system, in response to determining that a quantity of a variable value associated with an entity in the plurality of entities has changed by an amount equal to or exceeding a corresponding threshold value, generates response information associated with a quantity of the variable value and an entity to respond to at least one future question. In addition, the automated dialogue system stores the responsive information in association with the entity for later retrieval in response to initiation of a dialogue session with the automated dialogue system. Time thresholds may be established for determining when to stop using the responsive information for responding to questions.

Abstract: A method, apparatus and computer program product for responding to an indirect utterance in a dialogue between a user and a conversational system is described. An indirect utterance is received. A parse structure of the indirect utterance is generated. The indirect utterance is an utterance which does not match a user goal expressed as elements of a knowledge graph. The parse structure is connected through the knowledge graph to a user goal to issue a user request which is not stated in the indirect utterance. The parse structure is connected using a matching process which matches the parse structure with the connected user goal in the knowledge graph according to a similarity of the parse structure and a portion of the knowledge graph including the connected user goal. A system response is performed based on the connected user goal.

Abstract: An information processing system, a computer readable storage medium, and a computer-implemented method, collect tables from a corpus of documents, convert the collected tables to flattened table format and organized to be searchable by schema-less queries. A method collects tables, extracts feature values from collected table data and collected table meta-data for each collected table. A table classifier classifies each collected table as being a type of table. Based on the classifying, the collected table is converted to a flattened table including table values that are the table data and the table meta-data of the collected table. Dependencies of the data values are mapped. The flattened table and mapped dependencies are stored in a triple store searchable by schema-less queries. The table classifier learns and improves its accuracy and reliability. Dependency information is maintained among a plurality of database tables. The dependency information can be updated at variable update frequency.

Abstract: An information processing system, a computer readable storage medium, and a computer-implemented method, collect tables from a corpus of documents, convert the collected tables to flattened table format and organized to be searchable by schema-less queries. A method collects tables, extracts feature values from collected table data and collected table meta-data for each collected table. A table classifier classifies each collected table as being a type of table. Based on the classifying, the collected table is converted to a flattened table including table values that are the table data and the table meta-data of the collected table. Dependencies of the data values are mapped. The flattened table and mapped dependencies are stored in a triple store searchable by schema-less queries. The table classifier learns and improves its accuracy and reliability. Dependency information is maintained among a plurality of database tables. The dependency information can be updated at variable update frequency.

Abstract: An information processing system, a computer readable storage medium, and a computer-implemented method, collect tables from a corpus of documents, convert the collected tables to flattened table format and organized to be searchable by schema-less queries. A method collects tables, extracts feature values from collected table data and collected table meta-data for each collected table. A table classifier classifies each collected table as being a type of table. Based on the classifying, the collected table is converted to a flattened table including table values that are the table data and the table meta-data of the collected table. Dependencies of the data values are mapped. The flattened table and mapped dependencies are stored in a triple store searchable by schema-less queries. The table classifier learns and improves its accuracy and reliability. Dependency information is maintained among a plurality of database tables. The dependency information can be updated at variable update frequency.

Abstract: Methods and systems for performing database transactions include executing a first transaction request in a preplay mode that locks the requested data with a prefetch-lock and reads one or more requested data items from storage into a main memory buffer; locking the requested data items with a read/write lock after said data items are read into the main memory buffer; and performing the requested transaction on the data items in the main memory buffer using a processor.

Abstract: Mechanisms are provided for customizing responses to future questions based on identified anomalies in user profile information. An automated dialogue system monitors information associated with a plurality of entities, where the information includes quantities for variable values associated with the entities. The automated dialogue system, in response to determining that a quantity of a variable value associated with an entity in the plurality of entities has changed by an amount equal to or exceeding a corresponding threshold value, generates response information associated with a quantity of the variable value and an entity to respond to at least one future question. In addition, the automated dialogue system stores the responsive information in association with the entity for later retrieval in response to initiation of a dialogue session with the automated dialogue system. Time thresholds may be established for determining when to stop using the responsive information for responding to questions.

Abstract: A resource exploitation management system, method and a computer program product therefor. A description of new geological evidence for a geological resource is received, e.g., as one or more triples describing the evidence. Keywords in the description are matched against keywords in representations in a geological resource database. Geological relations are inferred from the descriptions and matched against predefined geological relations from the geological resource database. Consistent triple matches are merged with the geological resource database. The confidence level for merged matches is updated in the geological resource database.

Abstract: A system comprises a memory that stores computer-executable components; and a processor, operably coupled to the memory, that executes the computer-executable components. The system includes a receiving component that receives a corpus of data; a relation extraction component that generates noisy knowledge graphs from the corpus; and a training component that acquires global representations of entities and relation by training from output of the relation extraction component.

Abstract: Mechanisms are provided for conducting a natural language dialogue between the automatic dialogue system and a user of a client computing device. An automatic dialogue system receives natural language text corresponding to a user input from the user via the client computing device, the natural language text having an ambiguous portion of natural language text. The automatic dialogue system analyzes user profile information corresponding to the user to identify an anomaly in the user profile information and predicts a user intent associated with the anomaly. The automatic dialogue system disambiguates the ambiguous portion of the natural language text based on the predicted user intent and generates a response to the user input based on the disambiguated natural language text which is output to the client computing device to thereby conduct the natural language dialogue.

Abstract: A method, apparatus and computer program product for responding to an indirect utterance in a dialogue between a user and a conversational system is described. An indirect utterance is received. A parse structure of the indirect utterance is generated. The indirect utterance is an utterance which does not match a user goal expressed as elements of a knowledge graph. The parse structure is connected through the knowledge graph to a user goal to issue a user request which is not stated in the indirect utterance. The parse structure is connected using a matching process which matches the parse structure with the connected user goal in the knowledge graph according to a similarity of the parse structure and a portion of the knowledge graph including the connected user goal. A system response is performed based on the connected user goal.

Abstract: Mechanisms are provided for conducting a natural language dialogue between the automatic dialogue system and a user of a client computing device. An automatic dialogue system receives natural language text corresponding to a user input from the user via the client computing device, the natural language text having an ambiguous portion of natural language text. The automatic dialogue system analyzes user profile information corresponding to the user to identify an anomaly in the user profile information and predicts a user intent associated with the anomaly. The automatic dialogue system disambiguates the ambiguous portion of the natural language text based on the predicted user intent and generates a response to the user input based on the disambiguated natural language text which is output to the client computing device to thereby conduct the natural language dialogue.

Abstract: A policy violation detection computer-implemented method, system, and computer program product, includes extracting a policy activity from a policy, the policy activity including an actor in the policy, an object of the policy, an action of the policy, and policy scope metadata, capturing a transaction by a user including metadata of the transaction, translating the transaction by the user into an actor in the transaction, an action of the transaction, and an object of the transaction, and alerting the user of a policy violation by navigating a knowledge graph is-a hierarchy to relate the actor in the transaction to the actor in the policy, the object of the transaction to an object of the policy, and the action of the transaction to an action of the policy activity.

Abstract: A method, apparatus and computer program product for responding to an indirect utterance in a dialog between a user and a conversational system is described. An indirect utterance is received. A parse structure of the indirect utterance is generated. The indirect utterance is an utterance which does not match a user goal expressed as elements of a knowledge graph. The parse structure is connected through the knowledge graph to a user goal to issue a request which is not stated in the indirect utterance. A system response is performed, where the system response is a dialog system response based on a combination of the parse structure and the connected user goal.

Abstract: A policy violation detection computer-implemented method, system, and computer program product, includes extracting a policy activity from a policy, the policy activity including an actor in the policy, an object of the policy, an action of the policy, and policy scope metadata, capturing a transaction by a user including metadata of the transaction, translating the transaction by the user into an actor in the transaction, an action of the transaction, and an object of the transaction, and alerting the user of a policy violation by navigating a knowledge graph is-a hierarchy to relate the actor in the transaction to the actor in the policy, the object of the transaction to an object of the policy, and the action of the transaction to an action of the policy activity.