Abstract: A method includes: detecting, by a computing device, a new entry in one of plural databases; comparing, by the computing device, the new entry to watch entries defined in a watch database; determining, by the computing device, whether the new entry matches a watch entry in the watch database; creating, by the computing device, a new watch in the watch database when the new entry does not match any watch in the watch database; and updating, by the computing device, a watch in the watch database when the new entry matches the watch in the watch database.

Abstract: A computer-implemented method includes: receiving, by a computing device, a plurality of journal entries from a plurality of transactional systems; determining, by the computing device, association scores for a plurality of pairs of journal entries selected from the plurality of journal entries; generating, by the computing device, a reconciliation graph including a plurality of nodes representing the plurality of journal entries and a plurality of edges based on the determined association scores; recommending, by the computing device, actions to apply to at least one journal entry of the plurality of journal entries to minimize a number of nodes not connected by the plurality of edges in the reconciliation graph; receiving, by the computing device, feedback regarding the recommended actions to apply to the at least one journal entry; and updating, by the computing device, the reconciliation graph based on the feedback.

Abstract: A collision avoidance and road safety system is applied to a road network comprised of a plurality of road segments for a location to produce real time or dynamic forecasting of collision risk and root causes of the potential collision.

Abstract: A collision avoidance and road safety system is applied to a road network comprised of a plurality of road segments for a location to produce real time or dynamic forecasting of collision risk and root causes of the potential collision.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a product video representing a product and review feeds authored by a user. Product features are extracted from the product video and user specific features are extracted from the review feeds. User specific add-on content is generated based on the user specific features and user data. The user specific add-on contents are overlaid onto the product video when the product feature corresponding to a user specific feature of the user specific add-on content.

Abstract: A method includes: detecting, by a computing device, a new entry in one of plural databases; comparing, by the computing device, the new entry to watch entries defined in a watch database; determining, by the computing device, whether the new entry matches a watch entry in the watch database; creating, by the computing device, a new watch in the watch database when the new entry does not match any watch in the watch database; and updating, by the computing device, a watch in the watch database when the new entry matches the watch in the watch database.

Abstract: A computer-implemented method includes: receiving, by a computing device, a plurality of journal entries from a plurality of transactional systems; determining, by the computing device, association scores for a plurality of pairs of journal entries selected from the plurality of journal entries; generating, by the computing device, a reconciliation graph including a plurality of nodes representing the plurality of journal entries and a plurality of edges based on the determined association scores; recommending, by the computing device, actions to apply to at least one journal entry of the plurality of journal entries to minimize a number of nodes not connected by the plurality of edges in the reconciliation graph; receiving, by the computing device, feedback regarding the recommended actions to apply to the at least one journal entry; and updating, by the computing device, the reconciliation graph based on the feedback.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: identifying a target customer population of a series product and dividing into segments by customer behaviors relevant to adoption of and compliance to a series of purchases of the series product. A marketing campaign strategy for each segment is devised and executed, and adoption rate and compliance rate is predicted by analytical modeling and later evaluated by actual sales data. Parameters used in predicting the adoption rate and the compliance rate are adjusted for accuracy.

Abstract: A subsequence of machines used and a cost of providing a subservice in response to a service request with a key is determined. A second cost of using the subsequence of machines to provide the subservice in response to a different service request with a different key is determined. A distance between the cost and the second cost is computed. A value pair is formed using the distance and a number of logged occurrences of the subsequence with the key. The processing of the service request for the key is identified as a suspect for costing an improper computing cost of the service, when an aggregate distance in the value pair fails to exceed a threshold distance.

Abstract: The methods include, for instance: building model connections between models in a knowledgebase, which stores case data as model networks. An exploration probability stored in the knowledgebase indicates a likelihood of new connections based on a case data input to be employed for an analytical model of the case data input, which includes numerous stages and multiple model choices in each stage. Based on the new connections and model networks of the knowledgebase, paths are created and performance of respective paths/connections are evaluated. A predefined number of top performing paths are selected and the models and attributes that do not appear in the top performing paths are eliminated from the knowledgebase. Probabilities of model networks and a future case data input are updated accordingly and a best-fit model for the case data input is presented to a user.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a product video representing a product and review feeds authored by a user. Product features are extracted from the product video and user specific features are extracted from the review feeds. User specific add-on content is generated based on the user specific features and user data. The user specific add-on contents are overlaid onto the product video when the product feature corresponding to a user specific feature of the user specific add-on content.

Abstract: A subsequence of machines used and a cost of providing a subservice in response to a service request with a key is determined. A second cost of using the subsequence of machines to provide the subservice in response to a different service request with a different key is determined. A distance between the cost and the second cost is computed. A value pair is formed using the distance and a number of logged occurrences of the subsequence with the key. The processing of the service request for the key is identified as a suspect for costing an improper computing cost of the service, when an aggregate distance in the value pair fails to exceed a threshold distance.

Abstract: Systems and methods for predicting un-capacitated freight demand on a multi-hop shipping route are disclosed. In embodiments, a computer-implemented method, comprises: receiving daily customer booking data from one or more remote servers; determining an estimated customer arrival pattern for each port on a shipping route of a shipping vessel based on the customer booking data; determining an estimated blocking probability for each of the ports on the shipping route due to shipping capacity constraints, upstream bookings and downstream bookings; determining an estimated probability of booking cancellations for each of the ports on the shipping route; determining an estimate of how much freight will be loaded onto the shipping vessel for each of the ports; calculating un-capacitated shipping demand for each of the ports; and determining un-capacitated demand per day for each of the ports of the shipping route based on the capacitated demand and the estimated customer arrival pattern.

Abstract: A graph is constructing using a user node of a user and a set of connection nodes corresponding to connections in a social network of the user. The graph is overlaid on a risk map, which is a mapping of a geo-social risk characteristic of a geographical area. A first and a second risk indices are determined for a first and a second connection in the set of connections. Using the risk map, a first and a second risk diffusion boundary of the first and the second risk index are computed. When the first risk diffusion boundary includes the user node, a first risk contribution from the first connection node to the user node is computed using the first risk index. Using the first risk contribution, a risk index of the user is determined to accounts for a risk attributable to the user due to the user's social network.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: evaluating a brand value as a function of numerous parameters as formulated by brand value dynamics, and by use of input data for accurate prediction of the brand value. A brand equity is estimated based on the brand value and brand values of all brands competing in the market.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining input data regarding to a market for a branded product subject to loss of exclusivity scheduled. A dynamic half-life of a market value for the branded product is estimated to predict a market share erosion rate of the branded product at a point of time after the loss of exclusivity.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: identifying a target customer population of a series product and dividing into segments by customer behaviors relevant to adoption of and compliance to a series of purchases of the series product. A marketing campaign strategy for each segment is devised and executed, and adoption rate and compliance rate is predicted by analytical modeling and later evaluated by actual sales data. Parameters used in predicting the adoption rate and the compliance rate are adjusted for accuracy.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: predicting a market share based on consumer preference shift based on inputs of including sales data of respective branded products in a market, product feature data, and product event data. Feature cluster switch rates are first estimated and then brand switch rate within a subject feature cluster is estimated. Future market share of a branded product having the subject feature cluster is predicted and reported.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: building model connections between models in a knowledgebase, which stores case data as model networks. An exploration probability stored in the knowledgebase indicates a likelihood of new connections based on a case data input to be employed for an analytical model of the case data input, which includes numerous stages and multiple model choices in each stage. Based on the new connections and model networks of the knowledgebase, paths are created and performance of respective paths/connections are evaluated. A predefined number of top performing paths are selected and the models and attributes that do not appear in the top performing paths are eliminated from the knowledgebase. Probabilities of model networks and a future case data input are updated accordingly and a best-fit model for the case data input is presented to a user.

Abstract: From a log of a machine, an entry is selected relating to providing a subservice in processing a service request from a requestor associated with a key. The log entry includes a subsequence of machines used and a cost of providing the subservice. A set of entries is selected from the log, an entry including the subsequence and a second cost of providing the subservice but in processing a different service request from a different requestor associated with a different key. A distance is computed between the cost and the second cost. A number of occurrences of the subsequence with the key is determined. Using the number and the distance for the subsequence, a value pair is computed. Responsive to an aggregate number in the value pair not exceeding a threshold count. The processing of the service request is output as a suspect for using an improper sequence of machines.