Abstract: An example operation may include one or more of storing a hierarchical data set, receiving a plurality of predicted outputs from a plurality of nodes in a distributed computing environment, respectively, wherein each predicted output is generated by a different node via execution of a time-series forecasting model on a different subset of lowest level data in the hierarchical data set, combining the plurality of predicted outputs via bottom-up aggregation to generate one or more additional predicted outputs for the time-series forecasting model based on one or more levels above the lowest level in the hierarchical time-series data set, determining error values for the time-series forecasting model at each level of the hierarchical data set based on the received and the one or more additional generated predicted outputs, and modifying a parameter of the time-series forecasting model based on the determined error values.

Abstract: Deriving insights from time series data can include receiving subject matter expert (SME) input characterizing one or more aspects of a time series. A model template that specifies one or more components of the time series can be generated by translating the SME input using a rule-based translator. A machine learning model based on the model template can be a multilayer neural network having one or more component definition layers, each configured to extract one of the one or more components from time series data input corresponding to an instantiation of the time series. With respect to a decision generated by the machine learning model based on the time series data input, a component-wise contribution of each of the one or more components to the decision can be determined. An output can be generated, the output including the component-wise contribution of at least one of the one or more components.

Abstract: An example operation may include one or more of storing a hierarchical time-series data set in memory, initially training a first time-series forecasting model based on a lower level of time-series data in the hierarchical data set, training a second time-series teaching forecasting model based on an upper level of time-series data from the hierarchical data set which includes an additional level of aggregation with respect to the lower level of time-series data, optimizing one or more parameters of the initially trained first time-series forecasting model based on predicted outputs from the trained second time-series forecasting model in comparison to predicted outputs from the initially trained first time-series forecasting model, and storing the modified first time-series forecasting model in the memory.

Abstract: A method, system, and computer program product for an interpretable, feature-based post-hoc black box explainer for univariate time series forecasters are provided. The method receives a set of time series forecasting predictions. The set of time series forecasting predictions are generated from a set of black-box models trained with an initial data set. The method generates a set of features based on at least a portion of the initial data set. A set of surrogate models are trained based on the set of time series forecasting predictions and at least a portion of the set of features. A subset of surrogate models is selected. Based on the subset of surrogate models, the method generates one or more explanation outputs for time series forecasting predictions of the set of black-box models.

Abstract: One embodiment provides a method, including: accessing, at an information handling device, a dynamic visual media corpus, wherein the dynamic visual media corpus comprises a plurality of dynamic visual media scripts; segmenting each of the plurality of dynamic visual media scripts into scenes; generating, for each of the plurality of dynamic visual media scripts, a character fingerprint identifying topics corresponding to each character within a corresponding dynamic visual media script, wherein the generating comprises (i) extracting both characters and topics from the dynamic visual media script and (ii) associating each of the topics with a corresponding character, wherein the character fingerprint identifies costumes of a given character and a topic corresponding to each costume; and producing, for each scene within each dynamic visual media script, a scene vector identifying (iii) the topics included within a corresponding scene and (iv) a character fingerprint for each character occurring within the sce

Abstract: A method for managing the composition and presentation sequencing of compound visual elements, the method including generating a graph of all possible compound visual element combinations, generating a set of possible visual element presentation sequences according to a depth-first search (DFS) of the graph, generating a score for each member of the set of possible visual element presentation sequences according to visual element attributes, and enumerating a visual element presentation sequence according to a visual element presentation sequence score.

Abstract: Methods, systems, and computer program products for data filtering with fuzzy attribute association are provided herein. A computer-implemented method includes obtaining one or more rules, specified by an expert, that define a partial ranking of a plurality of fuzzy pairings between (i) a plurality of item attributes for items in a data catalog and (ii) a plurality of user attributes related to said items; generating an interactive session with the expert to resolve one or more ambiguities in the one or more rules; and deriving a scoring function based at least in part on (i) the one or more rules and (ii) the resolved one or more ambiguities, wherein the scoring function generates a comparative score between any two items of said data catalog for a given one of the users associated with the plurality of attributes.

Abstract: Methods, systems, and computer program products for customizing agricultural practices to maximize crop yield are provided herein. A computer-implemented method includes obtaining data pertaining to (i) a geographical area comprising a plurality of regions and (ii) one or more agricultural practices applied to the geographical area; assigning each of the plurality of regions to a respective cluster of a set clusters, based at least in part on comparing features identified in the data, wherein similar ones of said regions are assigned to the same cluster; generating instructions that are specific to a given cluster in the set, wherein the instructions relate to agricultural tasks to be performed on the regions assigned to the given cluster; and triggering, based on said instructions, one or more automated farming processing devices, thereby carrying out at least a portion of said agricultural tasks.

Abstract: Methods, systems, and computer program products for environmental impact aware product refurbishing are provided herein. A computer-implemented method includes obtaining information for products comprising images of the products and location-specific demand data; determining product embeddings of the products based on the images, wherein each of the product embeddings encodes attributes of the corresponding product; creating one or more refurbished designs of each given one of the products based on the initial image of the given product and one or more design constraints; calculating an environmental impact score and a demand impact score associated with each of the created refurbished designs, wherein the demand impact score is based on the location-specific demand data; generating a recommendation to refurbish at least one of the products in accordance with at least one of the refurbished designs based on the environmental impact scores and the demand impact scores.

Abstract: Methods, systems, and computer program products for contextual anomaly detection across assets are provided herein. A method includes obtaining time-series data frames corresponding to assets; clustering the assets into one or more cohorts based on the time-series data frames, each cohort comprising assets having statistically similar time-series data frames; for each given asset within each cohort: applying a time-context window to the portion of the time-series data frames corresponding to the given asset to generate at least one transformed data frame, and determining an asset distribution for the given asset based on the at least one transformed data frame; determining one or more of that at least one of the assets within at least one of the cohorts is anomalous and that at least one of the cohorts is anomalous; and causing at least one remediation action to be performed based on the determining.

Abstract: A method for managing the composition and presentation sequencing of compound visual elements, the method including generating a graph of all possible compound visual element combinations, generating a set of possible visual element presentation sequences according to a depth-first search (DFS) of the graph, generating a score for each member of the set of possible visual element presentation sequences according to visual element attributes, and enumerating a visual element presentation sequence according to a visual element presentation sequence score.

Abstract: Methods, systems, and computer program products for customizing agricultural practices to maximize crop yield are provided herein. A computer-implemented method includes obtaining data pertaining to (i) a geographical area comprising a plurality of regions and (ii) one or more agricultural practices applied to the geographical area; assigning each of the plurality of regions to a respective cluster of a set clusters, based at least in part on comparing features identified in the data, wherein similar ones of said regions are assigned to the same cluster; generating instructions that are specific to a given cluster in the set, wherein the instructions relate to agricultural tasks to be performed on the regions assigned to the given cluster; and triggering, based on said instructions, one or more automated farming processing devices, thereby carrying out at least a portion of said agricultural tasks.

Abstract: One embodiment provides a method, including: accessing, at an information handling device, a dynamic visual media corpus, wherein the dynamic visual media corpus comprises a plurality of dynamic visual media scripts; segmenting each of the plurality of dynamic visual media scripts into scenes; generating, for each of the plurality of dynamic visual media scripts, a character fingerprint identifying topics corresponding to each character within a corresponding dynamic visual media script, wherein the generating comprises (i) extracting both characters and topics from the dynamic visual media script and (ii) associating each of the topics with a corresponding character, wherein the character fingerprint identifies costumes of a given character and a topic corresponding to each costume; and producing, for each scene within each dynamic visual media script, a scene vector identifying (iii) the topics included within a corresponding scene and (iv) a character fingerprint for each character occurring within the sce

Abstract: Methods, systems, and computer program products for data filtering with fuzzy attribute association are provided herein. A computer-implemented method includes obtaining one or more rules, specified by an expert, that define a partial ranking of a plurality of fuzzy pairings between (i) a plurality of item attributes for items in a data catalog and (ii) a plurality of user attributes related to said items; generating an interactive session with the expert to resolve one or more ambiguities in the one or more rules; and deriving a scoring function based at least in part on (i) the one or more rules and (ii) the resolved one or more ambiguities, wherein the scoring function generates a comparative score between any two items of said data catalog for a given one of the users associated with the plurality of attributes.

Abstract: Methods, systems, and computer program products for contextual anomaly detection across assets are provided herein. A method includes obtaining time-series data frames corresponding to assets; clustering the assets into one or more cohorts based on the time-series data frames, each cohort comprising assets having statistically similar time-series data frames; for each given asset within each cohort: applying a time-context window to the portion of the time-series data frames corresponding to the given asset to generate at least one transformed data frame, and determining an asset distribution for the given asset based on the at least one transformed data frame; determining one or more of that at least one of the assets within at least one of the cohorts is anomalous and that at least one of the cohorts is anomalous; and causing at least one remediation action to be performed based on the determining.

Abstract: A neural network based search system is provided. A first digital image is analyzed by a user device. A targeted object in the first digital image is determined based, at least in part, on (i) the characteristics of the first digital image and (ii) the features of the targeted object. A vector array is generated based, at least in part, on (i) the first digital image and (ii) the targeted object. The vector array is analyzed by the user device. The targeted object is determined based, at least in part, by the vector array. A plurality of digital images is identified based, at least in part, on the similarity of the plurality of digital images and (i) the first digital image and (ii) the targeted object responsive to identifying a plurality of digital images, a query processing is generated. The query map is generated on a user device.

Abstract: Methods, systems and computer program products for resource position planning are provided herein. A computer-implemented method includes generating a multi-commodity flow network for locations of a distributed service network over a planning horizon. The method also includes obtaining a set of candidate outage scenarios for the distributed service network, each of the set of candidate outage scenarios being associated with a corresponding probability of occurrence. The method also includes generating a resource positioning configuration for resources in the multi-commodity flow network utilizing an optimization model that reduces unmet demand for each of the set of candidate outage scenarios based at least in part on the probability of occurrence of each of the set of candidate outage scenarios.

Abstract: A neural network based search system is provided. A first digital image is analyzed by a user device. A targeted object in the first digital image is determined based, at least in part, on (i) the characteristics of the first digital image and (ii) the features of the targeted object. A vector array is generated based, at least in part, on (i) the first digital image and (ii) the targeted object. The vector array is analyzed by the user device. The targeted object is determined based, at least in part, by the vector array. A plurality of digital images is identified based, at least in part, on the similarity of the plurality of digital images and (i) the first digital image and (ii) the targeted object responsive to identifying a plurality of digital images, a query processing is generated. The query map is generated on a user device.

Abstract: Methods, systems and computer program products for resource demand prediction are provided herein. A computer-implemented method includes obtaining historical data logs for activities performed in a distributed service network, the distributed service network comprising a plurality of locations. The method also includes identifying factors influencing resource demand for the distributed service network, determining one or more constraints for specifying activity sequence ordering for activities performed in the distributed service network and generating a statistical model of the distributed service network utilizing the historical data logs, the identified factors and the determined constraints.

Abstract: Methods, systems and computer program products for resource position planning are provided herein. A computer-implemented method includes generating a multi-commodity flow network for locations of a distributed service network over a planning horizon. The method also includes obtaining a set of candidate outage scenarios for the distributed service network, each of the set of candidate outage scenarios being associated with a corresponding probability of occurrence. The method also includes generating a resource positioning configuration for resources in the multi-commodity flow network utilizing an optimization model that reduces unmet demand for each of the set of candidate outage scenarios based at least in part on the probability of occurrence of each of the set of candidate outage scenarios.