International Business Machines Corporation

Yahoo! Inc.

Excalibur Ip, LLC

Michele Berlingerio

Adi Ionel Botea

Francesco Calabrese

Olivier Verscheure

Eric P Bouillet

Francesco Bonchi

Aristides Gionis

Stefano Braghin

Marco Luca Sbodio

Lea A Deleris

Pranay Anchuri

Björn Bringmann

Donna Leigh Gresh

Aris Gkoulalas-Divanis

Radu Marinescu

Oznur Alkan

Dimitrios Mavroeidis

Michele Gazzetti

Xiaowen Dong

Giusy Di Lorenzo

A system, computer program product, and method is described to propose a method to automatically suggest a visualization providing the best insight for a given dataset, by maximizing an utility function computed on properties of the input data, and previously used visualizations by the same user and for the same data. In one example method for recommending a data visualization in a computer system includes receiving at least one input dataset and at least one set of previous visualizations. A utility function is accessed. A set of potential visualizations is computed using the input dataset and the set of previous visualizations. A recommendation is selected for a proposed visualization from the set of potential visualizations by maximizing a value of the utility function, whereby the proposed visualization is a new visualization not in the set of previous visualizations.

Data visualizations selection

A method, computer system, and a computer program product for sequential pattern mining is provided. The present invention may include receiving a data mining parameter. The present invention may also include computing a plurality of frequent sequences without temporal annotations based on the received parameters. The present invention may then include extracting a subsequence with temporal annotations for each frequent sequence based on the computed plurality of frequent sequences. The present invention may further include clustering a plurality of temporal intervals using a time window based on the extracted subsequence. The present invention may also include producing an output based on the cluster of plurality of temporal intervals.

Sequential pattern mining

Embodiments for determining routes by one or more processors are described. A first set of route parameters is received. A second set of route parameters is received. At least one of the first set of route parameters and the second set of route parameters includes a route sharing parameter. A first route and a second route are determined based on the first set of route parameters and the second set of route parameters. The first route includes a first shared portion, and the second route comprises a second shared portion. The first shared portion of the first route is within a predetermined distance of the second shared portion of the second route based on the route sharing parameter.

Methods and systems for determining shared routes

Embodiments for implementing a fault tolerant color palette in a device having potential hardware faults by a processor. A fault tolerant color palette, assistive of user color interpretation for a display, may be generated according to a set of colors in a predetermined color palette and one or more user preferences.

Implementing a fault tolerant color palette

A mechanism is provided in a data processing system for extracting subgraphs from a multigraph with approximation. The mechanism receives a multigraph and a relevance function and a pattern generation component executing within the data processing system searches the multigraph for occurrences of at least one pattern based on an approximation function. A relevance computation component executing within the data processing system determines a relevance measure for the multigraph based on the relevance function and the occurrences of the at least one pattern. The mechanism provides output of relevant patterns based on the occurrences of the at least one pattern.

Mining relevant approximate subgraphs from multigraphs

Embodiments of the disclosure include a method for journey planning including receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.

Hedging risk in journey planning

A network's evolution is characterized by graph evolution rules. A graph, formed by merging multiple graphs representing the multiple snapshots of the network, that represents an evolutionary network is mined to identify evolutional patterns of the network. A pattern is selected from the identified patterns. Graph evolution rules are generated using identified evolutional patterns. The generated graph evolution rules represent the evolutional patterns of the network, the rules indicating that any occurrence of a child pattern of the selected pattern implies a corresponding occurrence of the selected pattern.

Network graph evolution rule generation

Embodiments of the disclosure include a computer system for journey planning, the computer system includes a journey planning server configured to perform a method. The method includes receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.

A system and method for detecting, monitoring and ranking incidents from social media streams comprises detecting incidents from social media streams and continuously monitoring the incidents, calculating a current-score for each of the incidents, determining a projected-score indicating an expected evolution for each of the incidents, ranking the incidents based on the current-scores of the incidents, predicting ranking of the incidents based on the projected-score of the incidents, and updating the predicted ranking responsive to new input detected about the incidents from the social media streams. In one aspect, the current-score is computed in accordance with characteristics of the incident comprising one or more of social impact assessment, dynamic location of users, human perception, and social network features. In one aspect, the current-score is calculated using one or more diffusion models based on one of a type of the incident, and similar incidents for which their evolution is known.

System for identifying, monitoring and ranking incidents from social media

Embodiments of the disclosure include a method for journey planning including receiving a journey planning request. The request includes an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan based on the journey planning request and a route map corresponding to the transportation network and identifying a potential event in the transportation. The method further includes monitoring the transportation network for the potential event and based on detecting an execution of the potential event, calculating an improved journey plan.

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Noicattaro, Italy

Michele Berlingerio