International Business Machines Corporation

Globalfoundries Inc.

Gilad Mordechai Saadoun

Peter Bak

Avi Yaeli

Alexander Kofman

Harold Jeffrey Ship

Daniel Christopher Berg

Tamar Eilam

Michael H Kalantar

Craig A Statchuk

Fabio A Oliveira

Florian Rosenberg

Xing Zhi Sun

Juerg Von Kaenel

Irina Dumitrescu

Jonathan Bnayahu

Matthias Kormaksson

Asaf Adi

Mordechai Nisenson

Tali Yatzkar-Haham

Guy Sharon

Eli Packer

Dolev Dotan

Yuval Nardi

Julian I Kamil

Sarit Arcushin

Brian James Gamage

John Tarcson

A system for executing a code for training an insurance response system, comprising at least one hardware processor adapted to: using a plurality of insurance attribute values, extracted from a received insurance claim to retrieve: at least one inquiry related to the insurance claim and at least one inquiry result, and historical insurance data related to the insurance claim; computing a similarity value indicative of a difference between the at least one inquiry result and a claim result; identifying in the historical insurance data a plurality of insurance conditions relevant to the claim result and the at least one inquiry result; identifying at least one insurance condition effecting the similarity value by analyzing data comprising the at least one inquiry and the plurality of insurance conditions; and training a protocol model of an insurance response system using the at least one insurance condition and the at least one inquiry.

Training a customer service system

Visualizations of a serial process are provided. A process model of a serial process is constructed using an underlying statististical model. The process model represents each instance of the serial process as a series of interconnected nodes, wherein (i) the serial process includes a plurality of events; (ii) each node is associated with an event and a time at which the associated event occurred in an instance of the serial process; and (iii) connectors link nodes together to form the series of interconnected nodes, the connectors representing stages of serial process. The stages are scored and categorized into various categories based, at least in part, on the process model. One or more of the categories is associated with outlier stages. A visualization of the process model is presented such that the visualization associates the stages of the instances of serial process with respective categories.

Visualization of serial processes

A capability to visualize temporal aspects of serial processes is provided. A process model of a serial process that includes a plurality of events and a plurality of stages is generated. The process model represents each of one or more instances of the serial process as a series of nodes. Each node represents an event and a time at which the event occurred in an instance of the serial process. For each stage of the serial process, a time-coordinate of a first node and a time-coordinate of a second node are altered while maintaining a difference in time between the first and second nodes. A common point lies between the first and second nodes as a result of altering the time-coordinates. A visualization of the process models is presented such that, for each stage of the serial process, a plurality of line segments intersect at the common point.

Visualizing temporal aspects of serial processes

A method and system for generating a map using a computer is based on data and weighted factors to minimize corresponding projection distortions. The method and system includes determining visualization goals from analyzing a set of datasets for a map using the computer. A set of visualization characteristics are calculated for each dataset based on the visualization goals using the computer. The visualization characteristics are analyzed to weight factors for each of the datasets. Each of the weighted factors is adjusted based on the relevance of each of the datasets for visualization of the map. An aggregate vector of weighted factors is calculated based on all of the datasets, and the map for visualization is generated based on the aggregate vector of weighted factors.

Method to optimize the visualization of a map's projection based on data and tasks

Various embodiments create a cross-configuration software module for cross-configuring software entities. In one embodiment, a first set of requirements and at least a second set of requirements are obtained. Each of the first and second set of requirements identify at least one of a set of software entities and a set of hardware components required to be present on at least one system including software entities to be cross-configured. At least one set of operations is obtained. The set of operations includes at least one executable instruction that configures a first software entity with a second software entity. A first configuration definition is generated including at least the first set of requirements and the at least one set of operations. A second configuration definition is generated including at least the second set of requirements. The first and second configuration definitions are stored within a cross-configuration software module.

Designing and cross-configuring software

A computerized visualization method for illustrating multi-dimensional data, comprising: receiving a plurality of location data points, each location data point having a plurality of measured features; choosing at least one location dimension from received said plurality of dimensions; grouping said plurality of location data points into a plurality of location groups according to chosen said at least one location dimension; plotting, by a processor, said plurality of location groups as a plurality of flower charts, each said plurality of flower charts, having a plurality of pie sectors, illustrates remaining said plurality of measured features subsequent to said choosing at least one location dimension; and positioning each said plurality of flower charts, in a visual representation, according to chosen said plurality of location dimensions.

Location info-graphics visualizations

A computerized method for generating monitoring rules, comprising: presenting to a user a spatio-temporal data indicative of a plurality of spatio-temporal attributes of a plurality of image objects in a space during a period; selecting, by a user, at least one of a spatial pattern and a temporal pattern represented in said spatio-temporal data; analyzing said at least one of a spatial pattern and a temporal pattern to identify at least one of a spatial related characteristic of at least some of said plurality of image objects and a temporal related characteristic of at least some of said plurality of image objects; automatically generating at least one monitoring rule to track an occurrence of said at least one of a location related characteristic and a temporal related characteristic.

Visual rules for decision management

An apparatus for visualizing data includes memory for storing sensor data and a processor. The processor is configured to generate a map of a geographic area, and to display at a first location on the map at least one icon graphically representing a measurement of the sensor at the first location over a period of time and graphically representing the period of time.

Spatiotemporal visualization of sensor data

A method for visualizing data includes generating on a display device a map including a first location and generating on the display device at least one icon graphically representing measurements of the sensor at the first location over a period of time and graphically representing the period of time.

Growing community of inventors

Haifa, Israel

Gilad Mordechai Saadoun