International Business Machines Corporation

Pu Huang

Ying Li

Richard Thomas Goodwin

Dharmashankar Subramanian

Markus Ettl

Ta-Hsin Li

Richard B Segal

Kaan Kudsi Katircioglu

Karthik Sourirajan

Axel Martens

Krishna Chaitanya Ratakonda

Hui Lei

Rakesh Mohan

Lipyeow Lim

Thomas Robert Ervolina

Feng Cheng

Lianjun An

Laurence Allan Phillips

T K Balachandran

Lisa A Smith

Jie Xu

Soumyadip Ghosh

Alan Jonathan King

Roman Kapuscinski

A method includes obtaining from an online social media site a plurality of instances of images of objects associated with a person; analyzing with a data processor the plurality of instances of the images with a plurality of predetermined style classifiers to obtain a score for each image for each style classifier; and determining with the data processor, based on the obtained scores, a likely preference of the person for a particular style of object. The plurality of instances of images of objects associated with the person can be images that were posted, shared or pinned by person, and images that the person expressed a preference for. In a non-limiting embodiment the object is clothing, and the style can include a fashion style or fashion genre including color preferences. A system and a computer program product to perform the method are also disclosed.

System and method for creating a preference profile from shared images

A service engagement map may be generated based on data collected associated with the service transition and delivery processes. The service engagement map may be refined iteratively by discovering additional data associated with the service transition and delivery processes and updating the service engagement map according to the additional data. Engagement metrics may be computed based on the service engagement map and presented. The service engagement map may also be presented visually.

Metrics management and monitoring system for service transition and delivery management

Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.

Scheduling for service projects via negotiation

The system and method of the present disclosure allow the user to enumerate a set of risk factors for each financial metric time-profile projection, and respond to a set of questions that is linear in the number of risk factors. In one embodiment, the risk elicitation on each risk factor uses user input of likelihood of risk and impact and/or severity. On each of the risk factors for any given nominal, financial projection estimate, the inputs are systematically converted into a net impact distribution for that nominal, financial estimate.

Method and system for estimating risk in the financial metrics of a business case

A method, system and computer program product for measuring a risk of an asset portfolio. The system estimates a &#x3b2;-level CVaR (Conditional Value-at-Risk) of the asset portfolio by modeling interdependencies between assets in the asset portfolio. The modeling is based on Gaussian copula model.

Fast and accurate method for estimating portfolio CVaR risk

The adaptive product conditioning is a computer-implemented method for identifying product configurations that can be provided to customers in reaction to supply imbalances. The methodology uses data mining techniques to collect and analyze business level meta data to coordinate supply and sales goals in terms of optimizing profits or managing product and technology transitions.

Adaptive product configuration model

A computer program product stored on machine readable media including machine readable instructions for selecting a project portfolio from available projects, the instructions for implementing a method include inputting an investment cost and a return for each available project and user-specified constraints; creating a formulation, the formulation comprising the investment cost and the return for each available project, the constraints and variables, the variables comprising for each available project a threshold probability of success and a selection decision; solving the formulation to select the project portfolio and to determine the threshold probability of success for each available project; and outputting the project portfolio and the threshold probability of success for each available project.

Method and system for risk-hedging in project management

A method and system for managing inventory under price protection plan determine an inventory replenishment plan for one or more goods considering a price protection agreement including at least length of price protection between at least two supply chain partners in a supply chain having decentralized control over a predetermined time period.

Method for managing inventory under price protection

A metric network provides a descriptive model that explicitly expresses the relationships among all metrics of a business enterprise. Performance of each single business entity in the operational level is measured by a set of primitive metrics, each of which measures a specific aspect of the business entity. The primitive metrics construct the base on which the whole metric network is built.

Method, apparatus and system for business performance monitoring and analysis using metric network

An apparatus including a calculator to determine an optimal solution to a stochastic linear programming problem or a stochastic mixed-ineteger linear programming problem with conditional value at risk constraints (CVaRs). The optimal solution is determined by generating a sequence of solutions that converge to the optimal solution.

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Yorktown Heights, NY, United States of America

Pu Huang