Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for obtaining real-time estimates. In one embodiment, a novel customizable, transferable system architecture is presented that enables the characterization of a task, designated for time estimate, into steps or processes. The characterization may occur using the novel architecture which introduces an estimates service module that can provide an initial timing estimate by obtaining a composite time estimate of all steps. Timing of each of the steps can be predicted using a job scheduling enterprise designed to model the job or step. In another embodiment, delays are captured by time estimate monitors which can provide the alerts and delta time differences. Such alerts and time differences can be updated and presented to the user.

Abstract: Systems and methods for submitting regulatory documents, from authoring through uploading to a health authority gateway. It may continuously publish documents into a submission archive as documents become associated to the content plan and as related content or attributes are updated. It may continuously validate submission components by applying validation rules defined by a health authority to report non-conforming validation results during the publishing process. It may allow users to review and resolve validation errors and warnings by reporting information to users on an ongoing basis to help reduce end-stage reconciliation.

Abstract: A method is provided for providing mobile device support services. The method may include monitoring a mobile device status. The method may additionally include performing device diagnostics based at least in part on captured deice status data to identify potential faults that may affect mobile device functionality. A corresponding system, apparatus, and computer program product are also provided.

Abstract: Systems and methods for data management are disclosed. One method can comprise receiving first data from one or more data sources and forming a classification group from the one or more data sources based upon one or more classifiers. The method can also comprise generating an identifier for the classification group by applying a function to the first data and/or the one or more classifiers. Second data can be received from the one or more data sources of the classification group and the second data can be associated with the identifier of the classification group.

Abstract: Methods and apparatus for using features of images representing content items to improve the presentation of the content items are disclosed. In one embodiment, a plurality of digital images are obtained, where each of the images represents a corresponding one of a plurality of content items Image features of each of the digital images are determined. Additional features including at least one of user features pertaining to a user of a client device or contextual features pertaining to the client device are ascertained. At least a portion of the content items are provided via a network to the client device using features that include or are derived from both the image features of each of the plurality of digital images and the additional features.

Abstract: A method and system for conducting an online payment transaction through a point of sale device. The method includes receiving input from a user selecting an item for purchase through the point of sale device; calculating a total purchase amount for the item in response to a request from the user to purchase the item; and sending payment authorization for the total purchase amount from the point of sale device to a payment entity, in which the payment authorization is sent to the payment entity via a mobile communication device of the user. The method further includes receiving a result of the payment authorization from the payment entity through the mobile communication device; and completing the payment transaction based on the result of the payment authorization.

Abstract: A coding amount estimation device includes: a feature vector generation unit that generates a feature vector on the basis of a feature map generated by an estimation target image and at least one filter set in advance; and a coding amount evaluation unit that evaluates a coding amount of the estimation target image on the basis of the feature vector.

Abstract: An order execution server for stock trading includes a data collection unit configured to collect trading data on at least one item, a subsidiary prediction value generation unit configured to generate a subsidiary prediction value by inputting the trading data into a pre-trained first deep learning model based on supervised learning, an order execution strategy deriving unit configured to derive an order execution strategy for the at least one item during a current period of time based on the trading data and the subsidiary prediction value by using a pre-trained second deep learning model based on reinforcement learning; and an order execution instruction unit configured to instruct order execution for the at least one item during the current period of time by using order information including the order execution strategy.

Abstract: Disclosed are systems, methods, and computer-readable storage media to select content to present to a user are disclosed. In one aspect, a method includes determining a content consumption rate of the user, and selectively presenting content to the user based on the content consumption rate. The content consumption rate may be determined based on a number of media content presented to the user over a period of time. If the number is above a threshold, a first type of content may be presented, while if the number is below (or equal) to the threshold, a second type of content, or in some aspects, no content, may be presented. After the selective presentation, additional content may be presented regardless of the content consumption rate.

Abstract: A system and method for comparing zones for different versions of a website based on performance metrics are provided. The method includes collecting comparison versions of at least one website specified in a received comparison request; identifying at least one comparison zone in the collected comparison versions, wherein a comparison zone is a zone included in the at least one specified website; collecting at least one comparison zone metric for each of the at least one comparison zones for the collected comparison versions, wherein the at least one comparison zone metric is a numerical value related to a user interaction metric with the at least one comparison zone; analyzing the collected comparison zone metrics to determine zone performance; and returning the analysis results.

Abstract: Embodiments for using an intelligent transaction optimization assistant by a processor. One or more actions to enhance a transaction experience of one or more users may be provided according to one or more selected constraints learned via a machine learning operation from previous transaction experiences, user behavior relating to the one or more previous transaction experiences, transaction experiences shared amongst entities associated with a social network, or a combination thereof.

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. The data subscription unit is in communication with a virtual machine that includes backtesting utility configured to generate backtesting data using one or more statistical models and one or more non-statistical models. The backtesting utility may translate the backtesting results into one or more interactive visuals, and generate a graphical user interface (GUI) for displaying the backtesting results and the one or more interactive visuals on a user device. The backtesting utility may update one or more of the displayed backtesting results and the one or more interactive visuals without re-running the modeling steps.

Abstract: A recommendation method includes generating a feature sequence based on to-be-predicted data of a user for a target object and according to a preset encoding rule, obtaining probability distribution information corresponding to each feature in the feature sequence, and obtaining, through calculation, a feature vector corresponding to each feature, obtaining a predicted score of the user for the target object based on values of N features and a feature vector corresponding to each of the N features, and recommending the target object to the user when the predicted score is greater than or equal to a preset threshold.

Abstract: Systems, methods, apparatuses, and computer-readable media are provided for determining individual item-level details associated with a transaction. A plurality of purchase transactions associated with different merchants may be displayed via a user interface. Responsive to a user selection of a first transaction, of the plurality of transactions, a camera may capture an image of at least a portion of a user receipt associated with the first transaction. The image of the user receipt may be analyzed using one or more optical character recognition (OCR) algorithms to convert the image of the user receipt into textual data. One or more character strings associated with line item-level details may be extracted from the textual data associated with the first transaction. Additional information associated with the line item details may be determined and the line item details and the additional information may be displayed via a user interface.

Abstract: An information processing device according to the present application includes an acquisition unit, a selection unit, and a search unit. The acquisition unit acquires a search query input by a user. The selection unit selects a type of target information to be searched on the basis of the search query acquired by the acquisition unit. The search unit searches for information corresponding to the search query from the type of target information to be searched selected by the selection unit.

Abstract: A system for determining customer interest in goods includes one or more memory devices storing instructions and one or more processors configured to execute the instructions. The processors are configured to receive customer location data from a smart device associated with a customer indicating the customer is within a retail venue of a retailer and to monitor, based on the customer location data, a current location of the customer within the retail venue. The processors are further configured to receive goods location data indicating locations of goods for sale within the retail venue and determine that the customer is interested in a particular good for sale within the retail venue based on the current customer location remaining in proximity to the location of the particular good for a predetermined period of time. The processors also conduct a search of pricing of the particular good at one or more other retailers and send a price comparison to the customer.

Abstract: A software voting or prediction system iteratively solicits participant preferences between members of a set, with a binary tree built used to minimize the number of iterations required. As each member of the set is considered, it is pairwise-compared with select members represented by nodes already in the binary tree, with iterations beginning at a root node of the tree and continuing to a leaf node. The newly considered member is placed as a new leaf node, and the tree is height-rebalanced as appropriate. Red-black tree coloring and tree rotation rules are optionally used for this purpose. Yes/no preference tallies are kept for each member of the set throughout the tree-building process and are ultimately used for scoring. Height-rebalancing of the tree helps minimize the number of iterations needed to precisely score each member of the set relative to its alternatives.

Abstract: A technological approach can be employed to protect data. Datasets from distinct computing environments of an organization can be scanned to identify data elements subject to protection, such as sensitive data. The identified elements can be automatically protected such as by masking, encryption, or tokenization. Data lineage including relationships amongst data and linkages between computing environments can be determined along with data access patterns to facilitate understanding of data. Further, personas and exceptions can be determined and employed as bases for access recommendations.

Abstract: A method, system, and computer program product for determining customer migration: obtain first feature data for a plurality of users associated with a first time period; segment the plurality of users into a plurality of groups based on the first feature data; identify a center point of each group based on the feature data; obtain second feature data for one or more users of the plurality of users associated with a second time period; determine a distance between the one or more users and each center point of each group based on the second feature data; and assign the one or more users to a group of the plurality of groups based on the distance between the one or more users and each center point of each group.

Abstract: A content editor for generating content including root blocks and nested blocks is disclosed. The content editor can generate a deployment that includes the content. The content editor can generate user interface code configured to edit the content. The content editor can receive updates to the content and update the root blocks and nested blocks. The updated root blocks and nested blocks can be used to generate updated content for editing and/or can be deployed to end-users.

Abstract: Systems, methods, and non-transitory computer-readable media can receive a set of candidate training items for training an early stage model in a multi-stage recall optimization model, wherein the multi-stage recall optimization model comprises the early stage model and a target model. A random subset of the candidate training items is selected from the set of candidate training items. For each training item in the subset of candidate training items, a score is determined based on the target model. Each training item in the subset of candidate training items is labeled with a label based on a probability of the training item being a top-K of the set of candidate training items had the set of candidate training items been scored based on the target model.

Abstract: Associating callers of a contact center with their social media identity may provide mutual benefits to the caller and contact center. For example, a business operating a contact center can receive information about their current and potential customers and customers can receive additional information, incentives, or other perks by allowing access to their social media profile. When a caller initially calls a contact center, they are prompted, and possibly incentivized, to check into a virtual venue. The caller may then be known, via an associated social media identity, to the contact center. The virtual venue may then receive access to comments and other posts, such as endorsements, provided by connects to the social media identity and process the call in accordance with the sentiment or utilize the social media network for post-call follow-up.

Abstract: Embodiments predict future demand for a first product by receiving historical sales data for an aggregate products/locations level, the historical sales data including a plurality of sales data points, including sales data points for the first product at each of a plurality of locations. Embodiments extract a plurality of different types of features related to sales of each of the products and generate a plurality of clusters of sales data points based on the plurality of different types of features. Embodiments train each of the clusters to generate a plurality of trained cluster models including promotion effects per cluster. For a particular time period, a particular location and the first product, embodiment identify the features for the time period and map to one of the trained cluster models to fetch the promotion effects for the time period. Embodiments then use the promotion effects to forecast demand for the first product.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying data center asset data to monitor; monitoring data center assets within a data center; selecting an asset data broker, the asset data broker performing an asset data aggregation operation, the asset data aggregation operation collecting and aggregating the data center asset data; and, providing aggregated data center asset data to a data center monitoring and management console.

Abstract: One example method includes performing a machine learning process that involves performing an assessment of a state of a computing system, and the assessment includes analyzing information generated by an IoT edge sensor in response to a sensed physical condition in the computing system, and identifying an entity in the computing system potentially impacted by an event associated with the physical condition.

Abstract: A system and method is provided for generating subscription recommendations suggesting ways that one or more creators of content may increase subscribership and/or prominence of the one or more creators. Subscription recommendations can involve changing and/or updating subscription levels offered by a content creator to potential, existing, or previous subscribers of the content creator. Current and/or historical performance data associated with the content creator, other content creators, and/or the consumers making up a community of subscribers may be analyzed in order to generate subscription recommendations.

Abstract: A method is provided for providing mobile device support services. The method may include monitoring a mobile device status. The method may additionally include performing device diagnostics based at least in part on captured deice status data to identify potential faults that may affect mobile device functionality. A corresponding system, apparatus, and computer program product are also provided.

Abstract: A method that predicts business income from user transaction data. A multinomial classifier is trained, using a vector of features from data related to a historical transaction and a label associated with the historical transaction, to generate a probability that the historical transaction belongs to a specific classification with respect to income. Data related to a new transaction is split into a set of unigrams. A new vector of features is generated from the data related to the new transaction. The new vector includes a set of values that correspond and are assigned to the set of unigrams. A classification with respect to income is determined for the new transaction by applying the multinomial classifier to the new vector. The new transaction is labeled with the classification. One or more fields of a form that is maintained by an online service is populated using the classification.

Abstract: A computer system and computer-implemented method for retail merchandise planning, including promotional product selection, price optimization and planning. According to an embodiment, the computer system for generating an electronic retail plan for a retailer comprises, a data staging module configured to input retail sensory data from one or more computer systems associated with the retailer; a data processing module configured to pre-process the inputted retail sensory data; a data warehouse module configured to store the inputted retail sensory data and the pre-processed retail sensory data; a state model module configured to generate a retailer state model for modeling operation of the retailer based on the retail sensory data; a calibration module configured to calibrate the state model module according to one or more control parameters; and an output module for generating an electronic retail plan for the retailer based on the retailer state model.

Abstract: Methods, apparatus, and processor-readable storage media for determining transaction-related user intentions using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data pertaining to digital behavior of a user during a transaction-related session on one or more electronic commerce websites; classifying the user into one of multiple categories by processing the obtained data pertaining to the digital behavior of the user using artificial intelligence techniques, wherein the multiple categories correspond to multiple predicted levels of user intention to complete a transaction; determining, based on the classification of the user and the obtained data pertaining to the digital behavior of the user, at least one reason why the user may not complete a transaction during the transaction-related session; and performing one or more automated actions based at least in part on the at least one determined reason.

Abstract: Systems and methods are disclosed to implement an item metric prediction system that predicts a metric for an item using a feature-based model built using other similar items. In embodiments, the system is used to predict item influence values (IIVs) of items indicating an expected amount of subsequent transactions that is caused by an initial transaction of the items. In embodiments, a sample of item transaction data is distributed to a plurality of task nodes, which execute in parallel to determine the items' observed IIVs from the transaction data. Subsequently, a new IIV is determined for an item whose observed IIV has a low confidence level. A set of similar items is selected, and a set of parameters of a feature-based model are tuned to fit the model to the observed IIVs of the similar items. A new IIV having a high confidence level is then obtained using the model.

Abstract: Various methods and systems are provided for conducting e-commerce. In one example, a method of conducting an e-commerce transaction includes a method of operating an online retail website. The method includes providing access to a computer interface for suppliers and presenting information to the suppliers through the computer interface regarding activity of the supplier's stock keeping unit (SKU). The suppliers are then enabled to directly modify at least one parameter associated with a presentation of the supplier's SKU on the retail website by way of the interface. The modification of the parameter may include, for example, modification of the presentation of the SKU including, for example, changing the title, adding video or photograph, or adding some other information. The modification of the parameter may also include, for example, modifying the price or entering into a bilateral agreement with the operator of the retail web site.

Abstract: Systems and methods are provided for generating engagement recommendations suggesting ways that one or more creators of content may maximize subscribership and/or subscription-based revenue, as well as support recommendations suggesting ways that the one or more creators of content may realize successful support of their content creation. Engagement recommendations can involve suggestions regarding when and/or how to engage one or more subscribers that results in a positive impact to subscribership and/or subscription-based revenue. Support recommendations can involve suggestions regarding when and/or how to elicit support in line with preferred indicia of success set forth by the one or more creators.

Abstract: The present disclosure includes systems, methods, and non-transitory computer readable media that generate and provide return of incremental digital content user interfaces that improve performance and efficiency of multi-channel, multi-region digital content campaigns. In particular, one or more embodiments generate and provide a user interface that comprises a return of incremental digital content expenditure regression curve and return of incremental digital content expenditure point representations that accurately and intuitively detail digital content campaign expenditure efficiency for combinations of channels and regions during multiple time periods in a time window. For example, the resulting return of incremental digital content expenditure user interface effectively utilizes limited computing device display space and resources to enable a publisher to quickly and accurately optimize and project high level expenditure allocation in order to improve digital content campaigns.

Abstract: A signal relationship is defined between a granular data value and a target data value. At least a portion of the granular data value corresponds to a granular latency value that is smaller than a target data latency value corresponding to the target data value. Granular data corresponding to the granular data value is interpreted. The granular data is aggregated in response to the signal relationship. A value of the target data value for a selected time reference is estimated, and the estimated value of the target data value is provided as a nowcasting prediction of the target data value.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, and including a method for publishing content. The method comprises identifying a content item for publication. The method further comprises identifying one or more reviews associated with content included in the content item. The method further comprises evaluating a review including determining a rating for the content where determining the rating includes normalizing the rating to a first scale. The method further comprises extracting one or more relevant phrases from the review. The method further comprises publishing the content item along with a normalized rating and the one or more phrases.

Abstract: An analytical recognition system includes a video camera, an antenna, and a data analytics module. The video camera is configured to capture video data. In some embodiments, the video camera is at least one of a traffic camera or an aerial drone camera. The antenna is configured to capture mobile communication device data. The data analytics module is configured to correlate the video data and the mobile communication device data to generate a profile of a person associated with the video data and the mobile communication device data. The profile has profile data including any one or a combination of the captured video data and the captured mobile communication device data.

Abstract: Systems and methods for Artificial Intelligence (AI)-based analysis of oral reviews are provided. An example method includes prompting a user to provide an oral review concerning a subject; providing the user with an interface configured to receive the oral review; receiving, via the interface, the oral review concerning the subject in a free format; generating, based on the oral review, a text for review and presenting the text for review to the user; and providing, to the user, an option to publish the text for review via at least one social media. Generating the text for review may include removing filler words from the oral review and converting the oral review from the free format to a format according to a grammar rule of at least one human language.

Abstract: Disclosed are techniques for lane estimation. In aspects, a method includes receiving a plurality of camera frames captured by a camera sensor of a vehicle, assigning a first subset of the plurality of camera frames to a deep learning (DL) detector and a second subset of the plurality of camera frames to a computer vision (CV) detector based on availability of the DL and CV detectors, identifying a first set of lane boundary lines in a first camera frame processed by the DL detector, identifying a second set of lane boundary lines in a second camera frame processed by the CV detector, generating first and second sets of lane models based on the first and second sets of lane boundary lines, and updating a set of previously identified lane models based on the first set of lane models and/or the second set of lane models.

Abstract: An audience measurement service may monitor broadcasts in a region, ingesting closed captioning data, metadata, displayed text or logos, performing facial recognition on people, and/or generating audio/video fingerprints of broadcast content to create a database of content and associated keywords, along with times at which the content was broadcast. The audience measurement service may receive user search queries from a search provider and detect “spiking” queries. The audience measurement service may determine whether the spiking queries are related, contextually and temporally, to an item of content identified in the database, and infer that users generating the queries likely viewed the item of content. In some implementations, the audience measurement service may also infer that the users likely viewed other items of content (e.g. advertisements) displayed during the prior or subsequent few minutes on the same broadcast channel as the query-triggering item.

Abstract: A method includes receiving an identification of a feature associated with digital content of a third-party content provider, wherein the identification comprises a feature variable placeholder associated with the feature. The method further includes receiving a configuration of a feature flag associated with the feature. The method further includes determining, by a processing device of an experimentation system, a plurality of feature variable values corresponding to the feature variable placeholder. The method further includes configuring, by the processing device, one or more rules on the experimentation system to determine: when and to whom the feature is to be deployed, based on the feature flag; and which of the plurality of feature variable values is to be deployed when and to whom.

Abstract: Described are a system, method, and computer program product for applying deep learning analysis to predict and automatically respond to predicted changes in financial device primacy for a financial device holder. The method includes receiving transaction data representative of a plurality of transactions between the financial device holder and a merchant. The method also includes generating time series data based on the transaction data and generating a predictive model configured to: (i) receive an input of time-interval-based transaction data; and (ii) output a probability of primary financial device primacy change, the predictive model trained based on historic transaction data. The method further includes determining a probability of primary financial device primacy change for the financial device holder by applying the predictive model to the time series data. The method further includes, generating at least one communication to at least one issuer and/or the financial device holder.

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can include a software development component and graphical user interface, referred to herein in some embodiments as a pipeline editor, or Lambda Studio IDE, that provides a visual environment for use with the system, including providing real-time recommendations for performing semantic actions on data accessed from an input HUB, based on an understanding of the meaning or semantics associated with the data.

Abstract: A device may receive customer data, and may identify unique communication channels associated with the customer data. The device may determine, based on the customer data, an optimal order for a Markov chain model, and may determine a model accuracy of the Markov chain model based on the optimal order. The device may transform transitions in the Markov chain model, based on the customer data, to generate transformed transitions, and may process the customer data, with a multi-level indexing model and based on the unique communication channels and the transformed transitions, to generate sparse matrices. The device may determine removal effects and steady state values for the sparse matrices, and may determine attribution weights for the unique communication channels based on the Markov chain model with the optimal order, the removal effects, and the steady state values. The device may perform actions based on the attribution weights.

Abstract: A system for processing exception event request to identify defective product includes one or more processors configured to receive, from a customer device, an exception event request associated with a product included in an order, the received exception event request comprising a product identifier. Access database to identify a number of exception event requests associated with the product identifier stored in the database. Determine when the number of exception event requests associated with the product identifier exceeds a predetermined threshold number of exception event requests for the product identifier. In response to determining that the number of exception event requests associated with the product identifier exceeds the predetermined threshold number of exception event requests, identify the product as a defective product.

Abstract: A method and system for providing a data consolidation for improved customer communication and agent performance evaluation in a multi-channel contact center are provided. The method includes receiving interaction data of an agent with customers across different communication channels within the contact center, consolidating the interaction data received across the different communication channels, aggregating the consolidated data to generate a set of metrics indicative of agent performance, inputting the set of metrics into an agent performance measurement framework, and determining a performance score for the agent based on an output of the agent performance measurement framework.

Abstract: Described are systems and methods for product recommendation refinement in a topic-based virtual storefront embedded in a topical community web page. A system and method may facilitate determining user and community member activity in the virtual storefront based on which weighted keywords are derived. A topic set containing various weighted keywords may be iteratively configured for extracting and ordering one or more products that are extracted from a plurality of heterogeneous sources. A server may be configured for refining the topic set by modifying a baseline session keyword weight or a baseline contextual keyword weight based on a total topic set weight, an elasticity parameter, core topic keyword weights associated with core topic keywords, session keyword weights, and/or contextual keyword weights; and identifying, based at least on the configured topic set, products to be presented to a user as product recommendations in the virtual storefront.

Abstract: A computer-implemented method and system for streamlining interactions between a customer and a customer service representative of a company. An interaction is commenced between the customer and the customer service representative during which historical data is accessed related to the customer stored in a company controlled computer system responsive to the interaction. The historical data preferably relates to at least one product or service provided by the company to the customer. At least a part of the historical information is displayed to the customer service representative. On the display, a first tab is generated related to the historical data as is a second tab relating to a quote for a new product or service for offering to the customer. The customer service representative is thereafter enabled to switch between displaying the historical data and the quote by selecting the first or second tab, respectively, without having to save the quote.

Abstract: A system and method for comparative performance monitoring of software release versions is disclosed. A remote network management platform may include a computational instance for managing a network. Transactions between a server of the computational instance and a client device in the managed network may be logged to a database. Transactions may be carried out by a release version of a set of program code units executing on the server. A software application executing on a computing device may retrieve and analyze a first set of transactions carried out by a first release version of the set of program code units to determine a first set of performance metrics, and do the same for a second set of transactions carried out by a second release version of the set of program code units to determine a second set of performance metrics.

Abstract: A validation system and method are provided that examine data for use in tracking and/or generating an action plan. Data is received and stored at an implementation data store from production data sources. Evaluation rules are applied to the data by a data storage system. The evaluation rules are applied by running previously created scripts of commands of the data storage system. Applying the evaluation rules to the one or more sets of the data outputs a deviation measure for at least one of the sets of the data. The deviation measure and a restricted list of defined validation decisions is presented to an analyst for the data. A selected validation decision is received, and the data is validated for use in the action plan, rejected for use in the action plan, or identified as requiring additional analysis before being validated for use in the action plan.