International Business Machines Corporation

Tomtom Global Assets B.v.

Wanli Min

Laura Wynter

Yasuo Amemiya

Kathryn Allyn Bassin

Bonnie Kathryn Ray

Padmanabhan Santhanam

Jonathan R M Hosking

Benjamin G Morris

Hendrik F Hamann

Aleksandra Mojsilovic

Feng Cheng

Gang Luo

Bala Ramachandran

Raymond Lloyd

David Gamarnik

Jonathan Miles Collin Rosenoer

A method for providing a forecast includes providing a multi-dimensional database storing data at a lowest level in a first dimension, calculating a first forecast at a level that is higher than the lowest level of a first dimension in the database, calculating a forecast for each category within the lowest level of the first dimension, aggregating a second forecast across a category at the lowest level of the first dimension based upon an aggregation of the calculated forecast for the category within the lowest level of the first dimension, determining a difference between the first forecast and the second forecast, creating a dummy category including a new category at the lowest level of the first dimension, and storing the difference in the dummy category at the lowest level of the first dimension.

Method and system for forecasting using an online analytical processing database

A method (and system) for providing a forecast, the method including providing a multi-dimensional database storing data at a lowest level in a first dimension, calculating a first forecast at a level that is higher than the lowest level of a first dimension in the database, calculating a forecast for each category within the lowest level of the first dimension, aggregating a second forecast across all categories at the lowest level of the first dimension based upon an aggregation of the calculated forecasts for each category within the lowest level of the first dimension, determining a difference between the first forecast and the second forecast, and storing the difference in a dummy category at the lowest level of the first dimension.

A method and apparatus for predicting traffic on a transportation network where real time data points are missing. In one embodiment, the missing data is estimated using a calibration model comprised of historical data that can be periodically updated, from select links constituting a relationship vector. The missing data can be estimated off-line whereafter it can be used to predict traffic for at least a part of the network, the traffic prediction being calculated by using a deviation from a historical traffic on the network. The invention further discloses a method for in-vehicle navigation; and a method for traffic prediction for a single lane.

Method and apparatus for providing navigational guidance using the states of traffic signal

A system, method and computer program product for estimating a vehicle arrival time. The system receives information representing prior travel times of vehicles between pre-determined vehicle stops along a vehicle route. The system receives real-time data representing a current journey. The current journey refers to a movement of a vehicle currently traveling along the route. The system calculates a regular trend representing the current journey based on the received prior travel times information and the received real-time data. The system computes a deviation from the regular trend in the current journey. The system determines a future traffic status in subsequent vehicle stops in the current journey. The system estimates, for the vehicle, each arrival time of each subsequent vehicle stop based on the calculated regular trend, the computed deviation and the determined future traffic status.

Vehicle arrival prediction using multiple data sources including passenger bus arrival prediction

Method and structure for vehicular traffic prediction with link interactions and missing real-time data

Techniques for data center analysis are provided. In one aspect, a method for modeling thermal distributions in a data center is provided. The method includes the following steps. Vertical temperature distribution data is obtained for a plurality of locations throughout the data center. The vertical temperature distribution data for each of the locations is plotted as an s-curve, wherein the vertical temperature distribution data reflects physical conditions at each of the locations which is reflected in a shape of the s-curve. Each of the s-curves is represented with a set of parameters that characterize the shape of the s-curve, wherein the s-curve representations make up a knowledge base model of predefined s-curve types from which thermal distributions and associated physical conditions at the plurality of locations throughout the data center can be analyzed.

Knowledge-based models for data centers

A method of thresholding of a database of customer purchasing history using a computer, includes providing a customer purchase history database including data regarding customer satisfaction, awareness of vendor brands, previous purchasing history, and size of customer budget, providing a predetermined threshold regarding the data, establishing, in the computer, boundaries surrounding the predetermined threshold, splitting the data, in the computer, to maximize the differences in the data across the split; generating, in the computer, a model of the data, in the computer, based upon the split, and allocating marketing resources based upon the model.

Most informative thresholding of heterogeneous data

Risk in business management is analyzed based on a probabilistic network approach which quantifies the impact of operational risk on financial metrics such as Value-at-Risk (VAR) and/or Potential Losses (PL). This approach provides further capability to determine the optimal placement of one or more countermeasures within a system to minimize the impact of operational risks.

Method and apparatus for operational risk assessment and mitigation

A method and structure for predicting traffic on a network, includes a receiver which receives data related to traffic on at least a portion of a network. A calculator calculates a traffic prediction for at least a part of the network, the traffic prediction being calculated by using a deviation from a historical traffic on the network.

Method and structure for vehicular traffic prediction with link interactions

A method and system estimates future software support requirements based on statistical models of previous observations of support requests, either for the same product or for a different product having features previously identified as correlated with features of a new product. The estimates include an estimated volume of support requests and an estimated type of support requests. The estimated types include the activity occurring at the time of the failure, an identifier as to whether a defect in the software was previously known, and the like. The estimates are used to estimate and allocate support resources prior to support requests being received, and prior to a software product being released.

Process for software support resource allocation based on analysis of categorized field problems

A method of subject-adaptive, real-time sleep stage classification to classify electroencephalogram sleep recordings into sleep stages to determine whether a subject exhibits a sleep disorder includes performing subject adaptation to improve classification accuracy for a new subject with limited training data, the performing subject adaptation comprises using linear-chain conditional random fields and potential functions, training the linear-chain conditional random fields using the training data, continuously receiving the electroencephalogram waves, continuously extracting features from the electroencephalogram waves, the extracting features comprising transforming each of the electroencephalogram waves to capture information embedded in the electroencephalogram waves, and continuously classifying the sleep stages according to extracted features and learned parameters from the linear-chain conditional random fields.

Growing community of inventors

Mount Kisco, NY, United States of America

Wanli Min