Abstract: The present invention relates to a system and method for generating business decisions. Embodiments of this system and method receive customer transaction data and additional information (cumulatively referred to as ‘modeling data’). This data is utilized to generate a product decision tree which models consumer purchasing decisions as a tree structure. The product decision tree may be utilized by the system to analyze demand for a given leaf (product) in association with other related products. In some embodiments, customers are segmented into groupings of customers who have similar attributes, including similar shopping behaviors. Customer insights are generated for the customer segments. The customer insights and the product decision tree are used to generate business plans, which may then be provided to a store for implementation. These plans may include a product assortment plan, an everyday pricing plan, a promotional plan, and a markdown plan.

Abstract: Methods and systems for forecasting demand are described. A method may include determining a demand pattern for each respective item of at least some items of a plurality of items. The method may also include clustering the plurality of items into a plurality of clusters based on the determined demand patterns. The method may further include determining a composite demand pattern for each cluster. The method may additionally include forecasting a demand for an item of the plurality of items based on the composite demand pattern of the cluster to which the item belongs.

Abstract: Systems and methods for improved data conversion and distribution are provided. A data subscription unit is configured to receive data and information from a plurality of data source devices in a plurality of data formats. The data subscription unit is in communication with a virtual machine configured to generate projected data for sparse electronic data. The virtual machine and a data distribution device distribute the projected data to remote user devices.

Abstract: Computer implemented sales prediction system collects data relating to events of visitors showing an interest in a client company from plural data sources, an organization module which organizes collected data into different event types and separates collected event counts in each event type between non-recent and recent events occurring within a predetermined time period, a first processing module which periodically calculates weighting for each event type based on recent and non-recent events for the event type compared to totals for other selected event types, a second processing module which periodically calculates sales prediction scores for each visitor and companies with which visitors are associated based on accumulated event data and weighting, and a reporting and data extract module which is configured to detect variation in sales prediction scores over time to identify spikes which can predict upcoming sales and to provide predicted sales information and leads to the client company.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a universal relevance service framework for ranking and personalizing items.

Abstract: A method and system for managing inventory of a product in at least one store. The method comprises: determining, for each store, a seed inventory of the product based at least on distribution data for the product; and generating, for each store, an estimated current inventory of the product based on the respective seed inventory and at least one heuristic.

Abstract: A system, method, apparatus, and processor readable non-transitive storage media are described for matching items in large datasets based on non-invasive fingerprints of users so that collected metric data for advertisements (media) and behavioral data may be reconciled and analyzed. Since user fingerprints may not generate a unique one to one correspondence or mapping under certain constraints, the various embodiments employ a sampling method that optimally matches the output of a random sampling of non-invasive fingerprints. The use of non-invasive fingerprints and specialized sampling enables the various embodiments to provide advanced analytics for advertising content and metric data in targeted behavior advertising campaigns. To compare impressions with user profile data, the various embodiments employ in part the time stamp dimension of user profiles to generate temporally unique persistent non-invasive fingerprints.

Abstract: In one embodiment, a method is provided. The method includes receiving forecast information from sales people in a computer. The method further includes receiving comments on specific entries of the forecast information from non-sales people in the computer. The method also includes receiving changes of the forecast information from the non-sales people in the computer. The method additionally includes providing a display of the comments and the changes to the sales people in an interface to the computer.

Abstract: Described is a system for event prediction on microblogs. In operation, the system receives a social media post stream from a social network to generate and maintain a social network database and an audit trail database. New social media posts are filtered to determine if the new social media posts are related to a possible future event. The new social media posts are compared against the social network database and audit trail database to provide a quality score, the quality score representing a likelihood that at least one of the new social media posts is a true prediction of a future event. If the quality score is determined to be true, the detection is published as a true prediction of a future event.

Abstract: The disclosure includes a system and method for aligning a realogram and a planogram. An alignment module of an image recognition application receives a realogram, the realogram including information about product recognitions, and a planogram corresponding to the realogram. The alignment module also generates a planogram brand chunk in the planogram, the planogram brand chunk grouping a plurality of planogram product facings belonging to a same brand, and a realogram brand chunk in the realogram based on the planogram brand chunk. The alignment module additionally identifies a planogram product facing in the planogram brand chunk and a realogram product facing in the realogram brand chunk and aligns the planogram product facing with the realogram product facing.

Abstract: A method for determining a future financial requirement of a business entity. The method includes obtaining a propensity model. The propensity model models how data of the business entity relates to a future financial requirement of the business entity. Also, the method includes gathering the data of the business entity. The data is created based on a platform utilized by the business entity, and the data of the business entity matches at least a subset of the propensity model. In addition, the method includes scoring the business entity by applying the propensity model to the data of the business entity. The method also includes generating, based on the score of the business entity, a classification of the future financial requirement of the business entity. Further, the method includes transmitting a message to the business entity based on the classification of the future financial requirement of the business entity.

Abstract: A method for guiding a user of an electric vehicle to a charging facility includes: searching for charging facilities existing within a predetermined distance from the current position of the electric vehicle; when a high-output charging facility and a low-output charging facility in a predetermined positional relationship with the high-output charging facility are searched, calculating the estimated value of a remaining charged capacity of a battery of the electric vehicle; calculating the estimated value of a charging time if charging the battery of the electric vehicle from the estimated value of the remaining charged capacity of the battery to a predetermined charged capacity at each of the searched charging facilities; and when the difference between the estimated value of the charging times at the high-output charging facility and the low-output charging facility is a predetermined value or less, presenting the low-output charging facility to the user of the electric vehicle.

Abstract: A system includes a contact center to provide an interaction between a consumer and an agent workstation of the contact center, where the consumer conducts a transaction with a provider through a third party marketplace. A database stores information about a relationship between the consumer, the provider and the marketplace. The contact center to routes the consumer to the agent workstation based on the relationship.

Abstract: An online system receives information describing a target group of online system users from a third party system and determines whether to store the information describing the target group. Online system users included in the target group are identified and scores are determined for each of the identified user. A score associated with a user represents the online system's effectiveness in targeting content to the user via targeting criteria maintained by the online system. Based on the scores, the online system determines a group score associated with the target group and stores the information describing the target group if the group score satisfies one or more criteria. If the information describing the target group is stored, the online system may determine whether to continue storing the information describing the target group based on revenue obtained by the online system from presenting content based on the target group.

Abstract: Rendering graphical user interfaces to display current and future data to users, the graphical user interfaces generated in response to search queries comprises a flight search system and an airline system. The flight search system receives current flight data and future flight data for the group of flights from an airline system and stores the data on a database. When the flight search system receives a flight search request comprising desired flight data from a user computing device, the system compares the desired flight search data with the stored data to identify one or more flights of the group of flights that match one or more features of the desired flight data. The system presents the current flight data and the future flight data on a graphical user interface to the user when it is likely that the flight data is going to change.

Abstract: A system and method for compiling search results is presented herein. A method can include gathering user behavior data, filtering the user behavior data, performing update calculations on the filtered user behavior data, using a decaying function to aggregate the filtered user behavior data; and facilitating the presentation of aggregated user behavior data. The user behavior data can include the user history for a plurality of users at an Internet-accessible site. The site can be an eCommerce site and the user history can include purchase and browsing history that can be used to determine a popularity of items sold by the eCommerce site. Facilitating the presentation can include displaying products in order of popularity. Other embodiments are also disclosed herein.

Abstract: An online system receives information describing a target group of online system users from a third party system and stores the information describing the target group. The online system subsequently uses the target group to select content for presentation to one or more users. For example, users included in the target group are identified as eligible to be presented with content items. Based on revenue obtained by the online system from presenting content based on the target group, the online system determines a monetization value for the target group. The online system determines whether to continue storing the information describing the target group based on the monetization value.

Abstract: There is disclosed apparatuses and methods for performing stepwise regression analysis on industry data. These apparatuses include a processor and memory which comprise circuits and software for performing the instructions on a storage medium comprising accessing a set of data specific to a business environment wherein the set of data comprises a set of values for a set of variables that describe a business environment; receiving a selection of a first variable from the set of variables; generating a correlation table, wherein the correlation table is generated by determining a correlation between the first variable and each remaining variable in the set of variables; and rank-ordering each of the remaining variables in the set of variables based on the correlation; and displaying the correlation table.

Abstract: Embodiments of the present invention provide a system, method and computer program product for forecasting a time series based on actuals and a plan. A method comprises generating a first and a second sequence of segments that rise and fall alternately based on a first and a second sequence of data values over time, respectively. The first and second sequence of data values represent actual data for an ongoing project and estimated data for a planned project, respectively. The method further comprises aligning at least one segment of the second sequence of segments with at least one segment of the first sequence of segments, and adjusting the estimated data by replacing at least one segment of the second sequence of segments with a scaled version of at least one corresponding aligned segment of the first sequence of segments. The scaled version maintains an estimated total for the planned project.

Abstract: Systems, methods and computer-readable media for providing e-commerce suppliers an alternative shipping and distribution system based on real-time sales and demand being coupled with iterative machine learning processes. As an example, an e-commerce supplier can contract with a retailer to have products sold in retail locations belonging to the retailer. However, rather than the retailer providing to the e-commerce supplier a quoted price for acquiring the merchandise, the retailer can provide two prices: one for if the e-commerce supplier delivers the merchandise to a distribution center, and another if the e-commerce supplier delivers the merchandise directly to a retail location, from which the retailer will redistribute the merchandise to other retail locations.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a personalized interactive decision support system. A customer profile generator executing within the personalized interactive decision support system determines a set of traits for at least one customer based on at least one user-generated content source. A personalized product recommendation module executing within the personalized interactive decision support system matches the at least one customer to at least one product within a set of products based on a consumption preferences-to-product attribute mapping data structure to form at least one product recommendation.

Abstract: A method, system, and computer program product for weight adjusted composite model for forecasting in anomalous environments are provided in the illustrative embodiments. A base forecasting model and a second forecasting model are combined to form a composite model, the base forecasting model configured to forecast an event in a time series, the second forecasting model configured to represent an anomalous portion of data in the time series. A mixing algorithm is combined with the composite model to adjust a set of weights associated with the composite model. Upon identifying a future period in which the event is to be forecasted, using the mixing algorithm, a subset of the set of weights is adjusted to from a weight adjusted composite model. The weight adjusted composite model is executed to forecast the event in the future period.

Abstract: A method, system, and computer program product for generating database cluster health alerts using machine learning. A first database cluster known to be operating normally is measured and modeled using machine learning techniques. A second database cluster is measured and compared to the learned model. More specifically, the method collects a first set of empirically-measured variables of a first database cluster, and using the first set of empirically-measured variables a mathematical behavior predictor model is generated. Then, after collecting a second set of empirically-measured variables of a second database cluster over a plurality of second time periods, the mathematical behavior predictor model classifies the observed behavior. The classified behavior might be deemed to be normal behavior, or some form of abnormal behavior. The method forms and report alerts when the classification deemed to be anomalous behavior, or fault behavior.

Abstract: Examples disclosed herein relate to a person moving in a physical space. In one aspect, a method is disclosed. The method may include obtaining at least two images of a person from at least two cameras directed at a physical space, where the physical space may include a plurality of designated areas. The method may also include obtaining metadata associated with the images, based on the images and the metadata determining within the plurality of designated areas a set of designated areas visited by the person, for each designated area within the set of designated areas, determining an area information, and updating a database based on the set of designated areas and based on at least a portion of the area information associated with each designated area within the set of designate areas.

Abstract: A method includes determining, at a processor, a difference between a first user interest profile of a first user and a second user interest profile of a second user. The difference is associated with a portion of a first streaming media item. The method further includes transmitting, to a device associated with a third user interest profile of a third user, a first indication associated with the first streaming media item based on the difference. The first user, the second user, and the third user are distinct users.

Abstract: Techniques for generating a forecast associated with an item may be described. For example, the forecast may be generated based on simulations of supply and demand variables associated with the item over a planning horizon. The forecast may include at least one of: a labor forecast or a capacity forecast associated with inventorying units of the item in an inventory over the planning horizon. Further, real-time data associated with realizations of the supply and demand variables during the planning horizon may be monitored. At least a portion of the real-time data may be available from a management system. The management system may be configured to manage orders for the units of the item from the inventory. The forecast may be updated during the planning horizon based on the real-time data. The update may include changing the at least one of: the labor forecast or the capacity forecast.

Abstract: Embodiments are directed to a computer implemented method of selecting a partner marketing communication. The method includes receiving, by a processor circuit, data of a potential visit by a customer to a location. The method further includes making a determination, by the processor, based at least in part on the data of the potential visit by the customer to the location, that the customer or an agent of the customer may travel to the location. The method further includes selecting, by the processor circuit, at least one partner marketing communication from among a plurality of available partner marketing communications based at least in part on the data of the potential visit and the determination that the customer or the agent may travel to the location.

Abstract: Systems and methods are described for generating indexed sales data by aggregating point of sale (POS) datasets are aggregated from transactions at a plurality of POS terminals. The POS datasets for each transaction include a transaction amount, a merchant classifier, and a transaction time. An industry subset of the aggregated POS datasets is obtained for a given timeframe based on the merchant classifier. This industry subset comprises transactions for a given industry. A sales value is calculated for the industry subset, and a monthly fluctuation factor is applied to the sales value. Also, a normalization factor is applied to the sales value based on a percentage of the sales value relative to an overall market size to obtain the indexed sales value.

Abstract: TPO is an industry-neutral price optimization solution that recommends optimal prices by performing a simultaneous evaluation of all network-wide demand and supply considerations. TPO produces an optimal time-phased price profile designed to achieve the greatest return on inventory. An optimizer technique takes the baseline demand forecasts, competitive intelligence, inventory data, and other related parameters and data representing real-world objects, and determines the optimal prices at which the user will achieve the greatest return on inventory. The optimizer technique can be directed to maximize revenues, profits, or market share. TPO produces a recommended price profile, that can be manipulated in an interactive graphical user interface, and illustrates what price must be charged now, and what prices must be charged later in the booking cycle. Using price sensitive forecasting to estimate how price impacts demand, TPO helps users to maximize revenues, profits, or market share.

Abstract: A use index IDX indicative of a degree of use of external charging is calculated and transmitted to a vehicle external system. The vehicle external system provides a service or imposes a penalty based on the use index IDX. In a case where the degree of use of external charging is determined to be low based on the use index IDX, if the vehicle external system provides a non-preferential service or imposes a heavy penalty as compared with a case where the degree of use of external charging is determined to be high, a driver or an owner of a vehicle takes an action by which the use index is determined to indicate a high degree of use of external charging. As a result, the use of external charging can be promoted.

Abstract: Methods and systems predict a reward resulting from serving one of a set of offers to one or more potential respondents, for example via a webpage, using one or more processors to calculate a predicted reward according to a model. The model may include one or more variables characterizing the respondent, a set of offer-specific coefficients comprising at least one coefficient for each of said one or more variables for each offer, and a set of common coefficients comprising a separate coefficient for each of said one or more variables, each coefficient of said set of common coefficients being common to all of said offers. The model may be trained in a two stage update process including a first update operation updating at least one common coefficient and a second update operation updating at least one offer-specific coefficient.

Abstract: Customer churn risk scores are based on a multi-variable churn risk model relating customer and customer account characteristics to a risk of customer churn. A computer-implemented method of generating and presenting churn risk scores of customers of a telecommunication provider involves analyzing, on an in-memory database platform, customer call data records and customer records to calculate a churn likelihood value, an influence factor value, and an average spend value for each customer. The method assigns a churn risk score to each customer according to the model using the calculated churn likelihood value, the calculated influence factor value, and the calculated average spend value as input to the model. The churn risk scores for one or more customers are displayed visually on an interactive computer-user interface (UI).

Abstract: Method(s) and System(s) for predicting Customer Lifetime Value (CLV) based on segment level churn includes segmenting the customers into multiple segments based on weighted RFM scores associated with data within a dataset. The data is representative of purchasing behavior of customers over a predefined time period. The segmenting is performed such that customers with similar and close weighted RFM scores are placed in one segment. Further, the method includes computing a churn value for each of the customer segments based on the buying behavior of the customers within each segment. The churn value is associated with transaction characteristics associated with customers corresponding to the data in each segment. Expected lifetime period in years for the customers is then predicted from the calculated segment level chum values. Thereafter, CLV, that indicates profitability associated with customers, is predicted for each customer based on their expected lifetime value in years.

Abstract: A media control player includes a central processing unit, a graphics processing unit, an audio/video input, an audio/video output, a memory device, and a media control player housing. The media control player to receives broadcast content from a broadcast source and proprietary targeted messages from a proprietary targeted message source. The proprietary targeted messages are based on one or more viewers within a viewing area of a display device, sales data associated with the one or more viewers, and inventory data selected based at least in part on the sales data. The media control player combines the proprietary targeted messages and the broadcast content into a merged output signal, and provides the merged output signal to the display device such that the proprietary targeted messages are displayed in a message region of the display device and the broadcast content is displayed in a broadcast content region of the display device.

Abstract: A method, apparatus, and computer program product are disclosed to improve generation of fine print for promotions. The method includes receiving identifying information that identifies one or more locations and either a product or service, transmitting the identifying information, and receiving, based on the identifying information, information including a set of relevant fine print clause data structures. The method further includes displaying, by a user interface, one or more fine print clauses from the relevant fine print clause data structures and generating, using a processor, a configured fine print data structure based on the displayed fine print clauses and input received via the user interface. Finally, the method includes transmitting the configured fine print data structure. A corresponding apparatus and computer program product are also provided.

Abstract: The invention discloses a system and method for estimating a three-dimensional (3D) packaging size of an object. The method has a self calibration function to correct the scale in the measurement environment so as to reduce errors caused by human operations. The system comprises an image capture unit for capturing images of the measurement environment and objects; a scale correction unit for performing the calibration using a reference object of a known size; and an object size estimation unit for detecting the position of an object to be estimated in the image data received from the image capture unit and estimating the 3D size of the object according to the calibrated scale.

Abstract: A method includes maintaining product sales information according to a data model. The data model includes a consumer-demographics naming convention, a retail-provider-type naming convention, and a product-naming convention. The maintaining includes indexing the product sales information by consumer-demographics information, by retail-provider-type information, and by product-categorization information. The method further includes receiving raw sales information and translating the raw sales information into the data model. In addition the method includes storing the translated raw sales information as part of the product sales information. Furthermore, the method includes receiving a request for aggregation of at least a portion of the product sales information. The request specifies an intersection of the product-categorization information, the consumer-demographic information, and the retail-provider-type information.

Abstract: An apparatus, system and method of implementing a computerized brand affinity engine. The apparatus, system and method include at least a plurality of computerized access points having accessible thereto a plurality of sites mentioning at least one sponsor, a categorized, hierarchical database of keywords, wherein at least the keywords falling in at least one category of the hierarchy correspond to a sponsor category of the at least one sponsor, and a tracker, wherein the tracker tracks positive ones of the mentions of the at least one sponsor on ones of the plurality of sites and negative ones of the mentions of the at least one sponsor on ones of the plurality of sites, in accordance with positive and negative keywords of the categorized, hierarchical database in the sponsor category, and wherein the tracker issues an rating with regard to the at least one sponsor in accordance with the positive ones and the negative ones of the mentions.

Abstract: Systems and methods for using disparate data sets to attribute data to an entity are disclosed. Disparate data sets can be obtained from a variety of data sources. The disclosed systems and methods can obtain a first and second data set. Trajectories can represent multiple data records in a data set associated with an entity. Trajectories from the obtained data sets can be used to associate data stored among the various data sets. The association can be based on the agreement between the trajectories. The associated data records can further be used to associate the entities related to the associated data records.

Abstract: Technology for determining the order of the search results to maximize a financial goal is described. In an example embodiment, a method, implemented using the one or more computing devices, such as client and/or server devices, may receive a product search request from a user device associated with a user and retrieve a set of products from a product database based on the product search request. Based on a purchase probability and one or more of a margin and a price for that product, the method determines an expected financial gain for each of the products of the set and sorts the set of products into an ordered set of products having an order based on the expected financial gain associated with each of the products. The method may then provide the ordered set of products for display to the user on the user device.

Abstract: The method of processing an analysis cycle to determine interest merchants may include selecting a seed merchant relevant to a topic interest, identifying consumers that have completed a transaction with the seed merchant to generate a list of identified consumers, determining merchants visited by the identified consumers, scoring all the merchants based on network connectivity, activity, and merchant over-index, updating the seed merchant in response to the list of scored merchants relative to a scoring threshold, and scoring the list of identified consumers based on the number of distinct merchants in transaction and over-indexing. Additionally, the method may further comprise producing a list of updated interest merchants and a list of updated identified consumers, where the updated interest merchants and the updated identified consumers are relevant to the topic interest.

Abstract: Data sets for a three-stage predictor can be automatically determined. For example, multiple time series can be filtered to identify a subset of time series that have time durations that exceed a preset time duration. Whether a time series of the subset of time series includes a time period with inactivity can be determined. Whether the time series exhibits a repetitive characteristic can be determined based on whether the time series has a pattern that repeats over a predetermined time period. Whether the time series includes a magnitude spike with a value above a preset magnitude can be determined. If the time series (i) lacks the time period with inactivity, (ii) exhibits the repetitive characteristic, and (iii) has the magnitude spike with the value above the preset magnitude threshold, the time series can be included in a data set for use with the three-stage predictor.

Abstract: A method for monitoring the operation of an IT infrastructure including a plurality of calculation nodes, includes selecting calculation nodes for performing a calculation, performing the calculation via the selected calculation nodes, attributing, via the sequencer, a score to each one of the calculation nodes having participated in the calculation performed, with each score reflecting a difference between a measured operating parameter of the calculation node for which the score is attributed and a reference operating parameter of the calculation node for which the score is attributed, verifying the operation of the calculation nodes having participated in the calculation performed, the verification being carried out using scores attributed to the calculation nodes having participated in the calculation.

Abstract: A system is provided for qualifying and analyzing data for at least one business intelligence. A platform receives source data. A data management system transforms raw data and stores it. An analytic engine is included. In operation the data management system receives first, second, and third streams of source data. The first stream is client source data, the second stream is public source data and the third stream is acquired by the data management system. The data management system organizes the first, second and third streams of data into items and their attributes. The analytic engine receives the items with their attributes from the data management system and applies logic to provide multi-dimensional analysis relative to a scale for at least one business intelligence.

Abstract: Provided herein are systems, methods and computer readable media for receiving consumer search data, aggregating by consumer and location, and utilizing the aggregated consumer search data in demand forecasting and relevance determination. An example method may include receiving consumer search data, the consumer search data indicative of search performed by a consumer, the consumer search data comprising one or more search terms and at least one of a consumer location or consumer identification information, storing the consumer search data for a predetermined time interval, and providing at least one of consumer aggregated search data to a relevance module for determining which of a plurality of promotions to present to a consumer at a second time or providing location aggregated search data to a demand forecasting module for utilization in forecasting promotion demand in a particular location.

Abstract: In some embodiments, apparatuses and methods are provided to forecast expected sales and/or demand for one or more products at one or more retail shopping facilities. Some embodiments include systems to forecast retail sales, comprising: a network transceiver; a forecast control circuit; and a memory storing computer instructions executed by the control circuit that receives, via the network transceiver from at least one third party service unassociated with retail shopping facilities and accessed over a distributed computer network, reservation data corresponding with people traveling during a future period of time to a geographic region that is within a threshold distance from a first retail shopping facility; and forecasts expected sales, during the future period of time associated with the reservation data, of at least a first set of products at the first retail shopping facility as a function of the reservation data.

Abstract: The disclosure relates to systems and methods for facilitating co-play and download of artist specific client applications via user-provided playlists that includes songs playable only through a respective artist specific client application. A playlist may include songs from a plurality of different artist specific applications. A given artist specific application may be created and branded for a particular artist, whose music may be playable only through a corresponding artist specific application. Because a given song may only be played/accessed from a corresponding artist specific application, a playlist that includes songs from different artist specific applications may cause artist specific applications to be activated (e.g., opened, placed in the foreground, etc.) when a song included therein is next in line to be played. Artist specific applications that have already played a song in the playlist may be de-activated (e.g., closed, placed in the background, etc.).

Abstract: A system and a method for account transaction balance prediction for an account held with a financial institution based on past and present account activity. An account balance prediction processor determines a recurring financial transaction based on at least one of: the internal account data, the external account data, and the transaction data. The system calculates a predicted account balance based on the total predicted financial transactions and the predicted income. A transaction monitor receives actual financial transaction data and actual income data, and compares the actual financial transaction data with the predicted financial transaction, and compares the actual income data with the predicted income data. An alert transmitter transmits in real time, an alert. A machine learning processor continuously adjusts calculations of financial transactions and income.

Abstract: In one embodiment, a system and method of predicting sale transaction conversion rate of an item operates through a search of information in response to a query over a network. The item can be included in a category of items. Information for other relevant items of the category is available through network query and historical data, among others. Respective information for the other items of the category is available to the method.

Abstract: A method for setting a filter coefficient for a communication system, which adjusts a frequency bandwidth by setting a filter coefficient of a wireless communication system over a communication network, is provided. In the method, a wireless communication system that includes a controller having a filter coefficient database and a web server, and a Digital Signal Processing device requests a filter coefficient and attribute information related to a set target frequency bandwidth from a management terminal. The wireless communication system receives the filter coefficient and the attribute information from the management terminal and stores the filter coefficient and the attribute information in the filter coefficient database. The wireless communication system sets a frequency bandwidth of the digital signal processing device as a set target frequency bandwidth based on the stored filter coefficient and the attribute information.