Abstract: A cognitive commuter assistant may provide alerts regarding sensitive conversation topics and smart excuse route suggestions. The cognitive commuter assistant may store user preferences and historical data related to past conversations between passengers and navigators. The cognitive commuter assistant may identify current location and destinations, and may further identify local information, such as news and cultural information, based on the current location and destination. The cognitive commuter assistant may monitor and analyze the conversation between a passenger and navigator to determine a first route to the destination. The cognitive commuter assistant may generate, based on user preferences, local information, the first route, and historical data, alternative route suggestions.

Abstract: Methods, systems and computer program products for automatic extraction and testing of constraints are provided herein. A computer-implemented method includes obtaining a first set of documents describing constraints and a second set of documents describing properties of entities, building a first dictionary of entity types and a second dictionary of relations among the entity types, extracting constraint triples representing the set of constraints from the first set of documents, and extracting fact triples from the second set of documents utilizing the first dictionary and the second dictionary. The method also includes receiving a query to evaluate whether at least one of the set of constraints is satisfied, determining whether the at least one constraint is satisfied by evaluating a constraint satisfaction formula utilizing the constraint triples and the fact triples, and providing a response to the query that indicates whether the at least one constraint is satisfied.

Abstract: Methods, systems and computer program products for automatic extraction and testing of constraints are provided herein. A computer-implemented method includes obtaining a first set of documents describing constraints and a second set of documents describing properties of entities, building a first dictionary of entity types and a second dictionary of relations among the entity types, extracting constraint triples representing the set of constraints from the first set of documents, and extracting fact triples from the second set of documents utilizing the first dictionary and the second dictionary. The method also includes receiving a query to evaluate whether at least one of the set of constraints is satisfied, determining whether the at least one constraint is satisfied by evaluating a constraint satisfaction formula utilizing the constraint triples and the fact triples, and providing a response to the query that indicates whether the at least one constraint is satisfied.

Abstract: Methods, systems and computer program products for automatic extraction and testing of constraints are provided herein. A computer-implemented method includes obtaining a first set of documents describing constraints and a second set of documents describing properties of entities, building a first dictionary of entity types and a second dictionary of relations among the entity types, extracting constraint triples representing the set of constraints from the first set of documents, and extracting fact triples from the second set of documents utilizing the first dictionary and the second dictionary. The method also includes receiving a query to evaluate whether at least one of the set of constraints is satisfied, determining whether the at least one constraint is satisfied by evaluating a constraint satisfaction formula utilizing the constraint triples and the fact triples, and providing a response to the query that indicates whether the at least one constraint is satisfied.

Abstract: Methods, systems and computer program products for automatic extraction and testing of constraints are provided herein. A computer-implemented method includes obtaining a first set of documents describing constraints and a second set of documents describing properties of entities, building a first dictionary of entity types and a second dictionary of relations among the entity types, extracting constraint triples representing the set of constraints from the first set of documents, and extracting fact triples from the second set of documents utilizing the first dictionary and the second dictionary. The method also includes receiving a query to evaluate whether at least one of the set of constraints is satisfied, determining whether the at least one constraint is satisfied by evaluating a constraint satisfaction formula utilizing the constraint triples and the fact triples, and providing a response to the query that indicates whether the at least one constraint is satisfied.

Abstract: A cognitive commuter assistant may provide alerts regarding sensitive conversation topics and smart excuse route suggestions. The cognitive commuter assistant may store user preferences and historical data related to past conversations between passengers and navigators. The cognitive commuter assistant may identify current location and destinations, and may further identify local information, such as news and cultural information, based on the current location and destination. The cognitive commuter assistant may monitor and analyze the conversation between a passenger and navigator to determine a first route to the destination. The cognitive commuter assistant may generate, based on user preferences, local information, the first route, and historical data, alternative route suggestions.