Abstract: A method detects conflicts between a power supply guarantee request (PSGR) and an outage request (OR) in a power grid. The method comprises receiving a first outage device set including OR related devices and a power supply guarantee device set including PSGR related devices. Geographic information about devices in the power grid is used to determine a second outage device set, which includes devices in the first outage device set and accompanying outage devices that need to be in outage together with devices in the first outage device set. Power grid topology information is used to determine a power grid outage scale in which all devices in the second outage device set can be in outage. For each device in the power supply guarantee device set, the method detects whether the device is included in the power grid outage scale, to determine any conflict between the PSGR and OR.

Abstract: A computer implemented method for clustering customers includes receiving a source set of customer records, wherein each customer record represents one customer, and each customer record includes at least one data attribute, and each data attribute has an attribute value; pre-processing the source set of customer records to generate a pre-processed set of customer records; executing a clustering algorithm on the pre-processed set of customer records to group the pre-processed set of customer records into clusters of a pre-defined number. The pre-processing comprises: determining the type of a customer in the source set of customer records; using a type attribute value to indicate the type of the customer in its customer record; normalizing data attribute values and type attribute values; weighting to the data attribute values and the type attribute values respectively to obtain weighted attribute values of the data attribute and weighted attribute values of the type attribute.

Abstract: A computer implemented method for clustering customers includes receiving a source set of customer records, wherein each customer record represents one customer, and each customer record includes at least one data attribute, and each data attribute has an attribute value; pre-processing the source set of customer records to generate a pre-processed set of customer records; executing a clustering algorithm on the pre-processed set of customer records to group the pre-processed set of customer records into clusters of a pre-defined number. The pre-processing comprises: determining the type of a customer in the source set of customer records; using a type attribute value to indicate the type of the customer in its customer record; normalizing data attribute values and type attribute values; weighting to the data attribute values and the type attribute values respectively to obtain weighted attribute values of the data attribute and weighted attribute values of the tune attribute.

Abstract: A method and system for integrating multiple factors into a unified optimization model for retail network configuration, in one aspect, obtains input data for modeling store configuration. The input data may include demand of each merchandise category from each customer segment in each facility, geographic distribution of stores in an area, current revenue of stores, and physical cost of reconfiguring stores. A trade area is generated as a function of store location, store format, and store capacity. The method and system also generates trade area demand summation representing predicted total demand of all stores for all merchandise categories for all customer segments in the trade area, as a function of store location, store format, store capacity, merchandise category, and customer segment associated with the trade area. An objective function is constructed as a function of said trade area demand summation, current revenue of stores, and physical cost of reconfiguring stores.

Abstract: A method and system for customer segmentation using adaptive spectral clustering may include determining initial segmentation labels, determining new customer behavior data, formulating a single objective minimization function that integrates the initial segmentation labels with the new customer behavior data, and determining best fit to both the initial segmentation labels and the new customer behavior data simultaneously by minimizing the single objective minimization function.

Abstract: A method and apparatus for end-to-end retail store one-stop site configuration integrates multiple data sources, identifying key customers, forecasting merchandise demand. Site configuration is formulated as a mathematical optimization problem with both in-store and external data as input to the problem whose solution provides proper suggestions for retail store transformation.

Abstract: A method for predicting sales for a new store in a certain geographical area is disclosed, the method comprising geographic and non-geographic information and customer segmentation in the area to estimate sales and optionally the impact on existing competitor stores.

Abstract: A computer searching technique identifies high quantitative patterns in data. A spatial indexing technique, such as an R-tree is used to represent the data. Then a pattern searching algorithm is used to identify anchor points that define the componentwise minimum patterns. High quantitative patterns are found responsive to the componentwise minimum patterns. The search strategy is demonstrated relevant to the problem of finding suitable locations for a retail business with reference to environments of prior successful retail businesses.

Abstract: A system, method and computer program product for providing the ability for retailers to devise a current channel strategy (e.g., adaptive price setting) that considers competitors in a dynamic competing environment, and that enables computing a competitive advantage of a channel. To estimate a price for selling a product j in a commerce channel comprises: a) receiving, at a processor device, real market data including sales and price history data of a product j sold by one or more retailers over one or alternate sales channels t; generating, by the processor device, a competitive advantage parameter value based on the sales and price history data; and, computing, utilizing the competitive advantage parameter value, an optimum price for a particular product to be marketed in one of the one or alternate sales channel.

Abstract: Method, apparatus and system for location evaluation and site selection, capable of effectively configuring the site network and evaluating the facility location by scientifically modeling and incorporating human knowledge are provided. In one aspect, geographic and demographic data associated with a plurality of locations and human knowledge comprising partial rating knowledge and pair-wise preference knowledge are used in a regression algorithm to construct a location evaluation model. The regression algorithm is further refined using active learning that identifies a plurality of pairs of locations to improve precision of the regression algorithm.

Abstract: A data integration module is operable to integrate a plurality of data sources, a customer preference module builds a model representing preference to different channels in merchandise category for each customer segment. A customer satisfaction module creates a model representing customer satisfaction metrics. A joint multi-channel optimization module is operable to use an optimization model that utilizes the customer preference model and the customer satisfaction model and maximize retailer's profit and customer satisfaction.

Abstract: A method and system are provided for detecting conflicts between a power supply guarantee request (PSGR) and an outage request (OR) in a power grid.

Abstract: A method, and system employing the method, for service channel reconfiguration at a service outlet includes generating service transaction data of a service outlet, generating queue management system (QMS) data of the service outlet, and generating cost and profit data for the service outlet. Data is extracted from the service transaction data and the QMS data relating to specified parameters including customer experience data, and customer demand data. The service transaction data and the QMS data is integrated with the cost and profit data providing a unified objective function. Stochastic service processes and customer behavior data are modeled. The unified objective function is evaluated using the stochastic service processes and customer behavior data model, and the service channel function of the service outlet is reconfigured using the unified objective function.

Abstract: System, method and computer program product for adjusting a representation of a merchandise hierarchy associated with an entity such as a retailer or wholesaler of products. Product correlation information discovered in that entity's customers' shopping records are obtained and incorporated into an existing merchandise hierarchy with a constraint on the consistency with the existing hierarchy.

Abstract: A topology structure of a power system is acquired. At least one unification set in the power system is identified based on the topology structure. Devices belonging to the same unification set have the same outage state. The at least one unification set is recorded, so as to concurrently maintain devices belonging to the same unification set. Advantageously, one or more embodiments reduce number of outages caused by power system device maintenance.

Abstract: A method and system for customer segmentation using adaptive spectral clustering may include determining initial segmentation labels, determining new customer behavior data, formulating a single objective minimization function that integrates the initial segmentation labels with the new customer behavior data, and determining best fit to both the initial segmentation labels and the new customer behavior data simultaneously by minimizing the single objective minimization function.

Abstract: A method and system for determining highlighting colors for topic elements in a chart. The method includes acquiring contrast elements and topic elements which need to be highlighted; acquiring colors of the contrast elements and layout information of the topic elements and the contrast elements in the chart; determining a plurality of combinatorial contrast policies for the colors of the contrast elements according to a color contrast standard; calculating weights of the combinatorial contrast policies using the layout information; and determining highlighting colors of the topic elements according to the combinatorial contrast policies and their weights. A system for executing the above method is also provided. A highlighting color can be selected automatically for the information that needs attention, so that the user can determine information that should be specially noted without having professional knowledge about color, saving time and energy.

Abstract: A method and system for integrating multiple factors into a unified optimization model for retail network configuration, in one aspect, obtains input data for modeling store configuration. The input data may include demand of each merchandise category from each customer segment in each facility, geographic distribution of stores in an area, current revenue of stores, and physical cost of reconfiguring stores. A trade area is generated as a function of store location, store format, and store capacity. The method and system also generates trade area demand summation representing predicted total demand of all stores for all merchandise categories for all customer segments in the trade area, as a function of store location, store format, store capacity, merchandise category, and customer segment associated with the trade area. An objective function is constructed as a function of said trade area demand summation, current revenue of stores, and physical cost of reconfiguring stores.

Abstract: Method, apparatus and system for location evaluation and site selection, capable of effectively configuring the site network and evaluating the facility location by scientifically modeling and incorporating human knowledge are provided. In one aspect, geographic and demographic data associated with a plurality of locations and human knowledge comprising partial rating knowledge and pair-wise preference knowledge are used in a regression algorithm to construct a location evaluation model. The regression algorithm is further refined using active learning that identifies a plurality of pairs of locations to improve precision of the regression algorithm.

Abstract: A method and apparatus for end-to-end retail store one-stop site configuration integrates multiple data sources, identifying key customers, forecasting merchandise demand. Site configuration is formulated as a mathematical optimization problem with both in-store and external data as input to the problem whose solution provides proper suggestions for retail store transformation.