Abstract: A dialogue complexity assessment method, system, and computer program product for introducing the notion of dialogue complexity to understand and compare dialogues in a repository, calculating the dialogue complexity, use the dialogue complexity to understand customer interactions in a variety of domains using public and proprietary data, and demonstrate the dialogue complexity usage to improve a service management operation.

Abstract: A dialogue complexity assessment method, system, and computer program product including calculating a complexity utilizing domain-dependent terms and domain-independent terms of a dialogue, where the dialogue includes dialogue data from contact centers of service providers.

Abstract: Various embodiments are provided for integrating multiple domain learning and personalization in a dialog system for a user in a computing environment by a processor. One or more problem instances may be defined for multiple domains according to a problem instance template, identified user intent, links to one or more problem solvers associated with the multiple domains, or a combination thereof. A dialog plan may be determined to further define the one or more problem instances in response to user input. A solution may be provided to the user for the one or more problem instances.

Abstract: A computer-implemented dynamic road stretch dividing method, the method comprising: determining a current lane distribution of partitions of a road stretch; calculating a new lane distribution of the road stretch to ameliorate traffic based on a pragmatic factor; changing an alignment of the partitions of the current lane distribution to obtain the new lane distribution; and updating the pragmatic factor based on at least one of an external policy and a constraint input by a user.

Abstract: Techniques are provided for assigning a bias rating to a service based on bias and/or anti-bias testing. For example, unbiased data can be input to the service to, e.g., determine whether the service introduces elements of bias. As another example, biased data can be input to the service to determine whether the service provides elements of anti-bias. In one example, a computer-implemented method comprises selecting, by a device operatively coupled to a processor, source data configured according to a bias specification indicating a criterion that defines bias. The computer-implemented method can comprise determining whether bias exists in output data of the service and determining a bias rating based on the determining whether bias exists in the output data. The computer-implemented method can further comprise assigning the bias rating to the service.

Abstract: Various embodiments are provided for using a dialog system for integrating multiple domain learning and problem solving for a user in a computing environment by a processor. One or more problem instances may be defined for one or more selected domains in a multi-domain database according to a problem instance template, identified user intent, links to one or more problem solvers associated with the one or more selected domains, or a combination thereof. A dialog plan may be determined for the one or more problem instances using a dialog system associated with the multi-domain database, wherein each record in the multi-domain database corresponds to a selected database for the one or more selected domains. A solution may be provided to the user for the one or more problem instances. One or more preferences of a user may be learned according to the solution.

Abstract: A personal digital assistant device includes: a memory storing an interactive personal digital assistant program and a processor configured to execute the interactive personal digital assistant program. The interactive personal digital assistant program performs an operation to determine whether the service provider is automated or is not automated. The interactive personal digital assistant program is configured to issue a command to the service provider on behalf of a user of the device, when it is determined that the service provider is automated. The interactive personal digital assistant program is configured to issue an alert on the device when it is determined that the service provider is not automated. The interactive personal digital assistant program may continue until the goal of the interaction is met or human help is sought.

Abstract: Embodiments of the present invention provide a system for implementing multi-turn dialogs. The system performs a method that includes receiving a series of user utterances, generating a series of responsive system utterances, and labeling the series of responsive system utterances to generate training data for training a dialog management policy. The labeling includes executing a reward function at each turn of a dialog, in which for each turn of the dialog the reward function is configured to output a reward value that is based at least in part on an accuracy of the responsive system utterance of the turn and on number of dialog turns elapsed.

Abstract: Methods, systems and computer program products for generating hypergraph representations of dialog are provided herein. A computer-implemented method includes analyzing at least one dialog to identify one or more topics and one or more contributions by one or more persons to the one or more topics, tracking evolution of the identified topics over time in the at least one dialog, generating a hypergraph representation of the at least one dialog utilizing the identified topics, the identified contributions and the tracked evolution of the identified topics, and providing an interactive visualization tool based on the hypergraph representation of the at least one dialog.

Abstract: Methods and arrangements for document quality assessment. Documents are accepted and a quality specification containing predetermined quality criteria is assimilated. Each document is assessed based on the predetermined quality criteria, and a quality score is assigned to each document, the quality score being a function of positive and negative attributes assessed for each document.

Abstract: Embodiments of the present invention provide a system for implementing multi-turn dialogs. The system performs a method that includes receiving a series of user utterances, generating a series of responsive system utterances, and labeling the series of responsive system utterances to generate training data for training a dialog management policy. The labeling includes executing a reward function at each turn of a dialog, in which for each turn of the dialog the reward function is configured to output a reward value that is based at least in part on an accuracy of the responsive system utterance of the turn and on number of dialog turns elapsed.

Abstract: Techniques facilitating estimating and visualizing entity to agent collaboration to facilitate automated plan generation are provided. In one example, a computer-implemented method comprises generating, by a device operatively coupled to a processor, a plan based on receiving first input data associated with an instance model. The computer-implemented method also comprises generating, by the device, a revised plan based on receiving second input data, associated with a revised instance model, from an entity. Furthermore, the computer-implemented method comprises, tracking, by the device, a contribution of the entity as a function of a modification from the instance model to the revised instance model.

Abstract: Methods and arrangements for forecasting at least one attribute of a future event based on a repository of historical event data associated with historical events comparable to the future event. A plurality of event data points are obtained from the repository of historical event data. The plurality of event data points are grouped in accordance with at least one category and a plurality of subcategories to create at least one data tree. Certain of the grouped event data points are designated to form a set of candidate data attributes, and the designated set of candidate data attributes are compared to a set of data attributes from the at least one data tree associated with the future event. Based on the comparing, there is identified a data attribute missing from the set of data attributes from the at least one data tree associated with the future event, and a value for the missing data attribute is forecast. Other variants and embodiments are broadly contemplated herein.

Abstract: Embodiments of the present invention provide a system for implementing multi-turn dialogs. The system performs a method that includes receiving a series of user utterances, generating a series of responsive system utterances, and labeling the series of responsive system utterances to generate training data for training a dialog management policy. The labeling includes executing a reward function at each turn of a dialog, in which for each turn of the dialog the reward function is configured to output a reward value that is based at least in part on an accuracy of the responsive system utterance of the turn and on number of dialog turns elapsed.

Abstract: A dialogue complexity assessment method, system, and computer program product for introducing the notion of dialogue complexity to understand and compare dialogues in a repository, calculating the dialogue complexity, use the dialogue complexity to understand customer interactions in a variety of domains using public and proprietary data, and demonstrate the dialogue complexity usage to improve a service management operation.

Abstract: A dialogue complexity assessment method, system, and computer program product for introducing the notion of dialogue complexity to understand and compare dialogues in a repository, calculating the dialogue complexity, use the dialogue complexity to understand customer interactions in a variety of domains using public and proprietary data, and demonstrate the dialogue complexity usage to improve a service management operation.

Abstract: A dialogue complexity assessment method, system, and computer program product for introducing the notion of dialogue complexity to understand and compare dialogues in a repository, calculating the dialogue complexity, use the dialogue complexity to understand customer interactions in a variety of domains using public and proprietary data, and demonstrate the dialogue complexity usage to improve a service management operation.

Abstract: Embodiments for learning personalized actionable domain models by a processor. A domain model may be generated according to a plurality of actions, extracted from one or more online data sources, of a plurality of cluster representatives. The plurality of actions achieve a goal. A hierarchical action model may be generated based on probabilities of the domain model and the plurality of actions. The hierarchical action model comprises a sequence of actions of the plurality of actions for achieving the goal. The hierarchical action model may be personalized by filtering to a selected set of actions according to weighted actions of the plurality of actions.

Abstract: Systems and associated methods for automated and semi-automated building of domain models for documents are described. Embodiments provide an approach to discover an information model by mining documentation about a particular domain captured in the documents. Embodiments classify the documents into one or more types corresponding to concepts using indicative words, identify candidate model elements (concepts) for document types, identify relationships both within and across document types, and consolidate and learn a global model for the domain.

Abstract: A personal digital assistant device includes: a memory storing an interactive personal digital assistant program and a processor configured to execute the interactive personal digital assistant program. The interactive personal digital assistant program performs an operation to determine whether the service provider is automated or is not automated. The interactive personal digital assistant program is configured to issue a command to the service provider on behalf of a user of the device, when it is determined that the service provider is automated. The interactive personal digital assistant program is configured to issue an alert on the device when it is determined that the service provider is not automated. The interactive personal digital assistant program may continue until the goal of the interaction is met or human help is sought.