Abstract: The occurrence cost of unknown words that are not registered in a morphological analysis dictionary is calculated by applying an occurrence cost regression model, which is a learning model. An information processing device includes a notation feature amount extraction unit that extracts a notation feature amount of a character string, a part-of-speech feature amount extraction unit that extracts a part-of-speech feature amount of the character string, and an occurrence cost estimation unit that receives the notation feature amount and the part-of-speech feature amount and calculates an occurrence cost of the character string by applying an occurrence cost regression model. The occurrence cost regression model is a learning model that estimates the occurrence cost from the notation feature amount and the part-of-speech feature amount of a character string, generated by a learning process using registration data of an existing morphological analysis dictionary as teacher data.

Abstract: A method, computer system, and a computer program product for online posting annotation is provided. The present invention may include identifying a topic in an online posting. The present invention may include determining that a comment to the online posting relates to the online posting. The present invention may include adding at least one detail from the comment to the online posting. The present invention may include tagging the at least one added detail with at least one piece of metadata. The present invention may include validating a viewing access based on the at least one piece of metadata and displaying an amended online posting.

Abstract: A computer-implemented method includes receiving training data that includes a plurality of API requests from a plurality of client devices. The method includes generating a plurality of permissible API sessions based on the training data. Each of the permissible API sessions is associated with a corresponding client device of the plurality of client devices and includes a sequence of API requests originating from the corresponding client device. The method includes applying a sequence embedding technique to the plurality of permissible API sessions to generate a plurality of embeddings and applying a dimensionality reduction technique to the plurality of embedding to generate a plurality of compact embeddings. The method includes storing each of the compact embeddings in a space partitioning data structure at storage locations within the space partitioning data structure that are determined based on similarities between the compact embeddings.

Abstract: A method and a system for fault diagnosis with small samples of power equipment based on virtual and real twin spaces are disclosed, which belong to the field of fault diagnosis of power equipment. The method includes: test samples containing different locations, types and severity levels of fault of power equipment are acquired to form a real physical space; a virtual mirror space is acquired by simulation according to a simulation model of the equipment to be diagnosed; the training set in the real physical space is spatially integrated with the sample set in the virtual mirror space to obtain a training sample set in the twin spaces; the training sample set in the twin spaces serves as the supplement to the training set in the real physical space, and the fault type and fault location serve as diagnostic labels to be input to the deep neural network for training.

Abstract: A system and method of data record management is provided. The system comprises a processor and a memory coupled to the processor that stores processor-executable instructions that when executed configure the processor to perform the method. The method comprises receiving a plurality of unstructured natural language data records, generating a structured dataset based on the plurality of unstructured natural language data records, transforming the structured dataset to normalize the respective frequency values based on inverse proportionality of the respective frequency values, determining a redundancy prediction value associated with that unstructured natural language data record based on the transformed structured dataset, and displaying on a graphical user interface a message identifying one or more unstructured natural language data records being associated with a redundancy prediction value greater than a threshold value.

Abstract: An apparatus includes processing circuitry and a memory storing instructions that, when executed by the processing circuitry, cause the apparatus to identify a plurality of components and a data flow that interconnects the plurality of components. The instructions cause the apparatus to determine a lineage of a record generated by the plurality of components based on the data flow. The lineage indicates the data flow from a first component to a second component of the plurality of components to generate the record. The instructions cause the apparatus to present, to a user, a visual depiction of the lineage of the record. The visual depiction indicates the data flow of a query through at least the first component and the second component of the plurality of the components to generate the record.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for machine learning for home understanding and notification. In one aspect, a method includes collecting activity data from one or more devices in a home network, generating a graph-based knowledge base including two or more nodes based on the activity data, where each node is an object, person, or routine and wherein each link is a relationship between two nodes, generating, based on the graph-based knowledge base, one or more rules, determining, based in part on the activity data, an occurrence of a particular rule of the one or more rules, generating a notification responsive to the particular rule, presenting the notification to a user, receiving, user feedback responsive to the notification, where the user feedback includes a natural language label for the particular rule, and updating the particular rule based on the user feedback.

Abstract: Embodiments facilitating data exploration in a computing environment by a processor. A multidimensional dataset may be received. The multidimensional dataset may be processed according to booting operation parameters. A visualization and exploration of an interactive representation of one or more probabilistic models for each one of a set of instances using the multidimensional dataset.

Abstract: A communication system for processing a call includes control logic and at least one machine learning model generating call classifiers from outputs of an audio signal processor and a natural language processor operated on the call. Heuristic logic transforms the call classifiers into weighted sub-metrics for the call, and aggregate normalized Gaussian logic transforms the weighted sub-metrics into a metric control that may be applied as a feedback signal to adapt the operation of the control logic. The control logic in turn may adapt the behavior of an agent, automated voice attendant, or a template utilized in a call flow.

Abstract: An alert generator in a communication system for processing a call includes at least one machine learning model generating call classifiers from outputs of an audio signal processor and a natural language processor configure to operate on the call. Heuristic logic is configured to transform the call classifiers into a plurality of weighted sub-metrics for the call, and aggregate normalized Gaussian logic is configured to transform the weighted sub-metrics into a metric control. A threshold analyzer is configured to generate an alert signal to the communication system based on the metric control meeting a condition.

Abstract: A method, apparatus, and computer-readable medium for generating an audit trail of a record including receiving a request to generate an audit trail of the record, the request comprising a record identifier of the record and a date value, identifying commit data structures corresponding to the record based on the record identifier, each commit data structure corresponding to a set of changes previously applied to fields of the record and comprising a timestamp value, a list of changes made to fields, and a prior commit pointer pointing to a prior commit data structure, identifying commit data structures that are pertinent to the request based at least in part on the timestamp value of at least one commit data structure and the date value, and generating the audit trail of the record based on the list of changes in each commit data structure in the identified commit data structures.

Abstract: A software agent, that is used to assist in providing a service, receives communications from a set of users that are attempting to use the software agent. The communications include communications that are interacting with the software agent, and communications that are not interacting with the software agent. The software agent performs natural language processing on all communications to identify such things as user sentiment, user concerns or other items in the content of the messages, and also to identify actions taken by the users in order to obtain a measure of user satisfaction with the software agent. One or more action signals are then generated based upon the identified user satisfaction with the software agent.

Abstract: In an embodiment, a process for graph decomposition includes initializing nodes and edges of a data graph for analysis using a computer, and performing message passing between at least a portion of the nodes of the data graph to determine a corresponding measure of interest for each node of at least a portion of the data graph. The process further includes receiving an identification of one or more nodes of interest in the data graph, performing message passing between at least a portion of the nodes of the data graph using at least the determined measures of interest to identify a corresponding subgraph of interest for each of the one or more nodes of interest in the data graph, and performing an analysis action using the one or more identified subgraphs of interest.

Abstract: Described herein is a computer implemented method for confirming the completion of an onboarding setup item of an IT Service Management (ITSM) system. The system comprises a first software platform, a second software platform and an intermediary onboarding platform operatively associated with a database for storing a state of the setup item, the setup item being associated with at least one of the first and second software platforms. The method comprises receiving input data associated with at least one of the first and second software platforms; querying the received input data against completion criteria that is dependent on a predetermined item type; updating a state of the setup item; and displaying a visual indication of confirmation of the completion of the setup item.

Abstract: A communication system for processing a call includes control logic and at least one machine learning model generating call classifiers from outputs of an audio signal processor and a natural language processor operated on the call. Heuristic logic transforms the call classifiers into weighted sub-metrics for the call, and aggregate normalized Gaussian logic transforms the weighted sub-metrics into a metric control that may be applied as a feedback signal to adapt the operation of the control logic. The control logic in turn may adapt the behavior of an agent, automated voice attendant, or a template utilized in a call flow. The system includes a scorecard interface operable to select a target and an indication of the metric control to apply for the target, and to apply the metric control to generate and display a historical performance visualization and a performance feed of the metric for the target.

Abstract: A search and data analysis collaboration system is described. The search and data analysis collaboration system enables users to search for and process stored data, and further includes a home page component that can help guide users embarking on data analyses; a discovery component that enables users to discover what data is available for search and analysis; a search component that enables users to efficiently search accessible data and to iterate on search queries and corresponding results; a workbooks component that enables users to create aggregated collections of data analysis artifacts; and an actions component that enables users to configure various actions to be performed in response to analyses.

Abstract: A method for generating visual representations of financial interests includes: receiving an input data set including one or more data structures storing data fields and data values representative of financial interests; extracting, from the input data, one or more extracted features from the funds, the extracted features collectively indicative of a distance between different funds; generating one or more clusters of funds, based on the extracted features of the funds; determining, based on identified differences between one or more funds relative to at least one other fund in a corresponding cluster of funds, one or more fund anomalies based on the one or more extracted features; generating one or more adjustment recommendations based on the one or more fund anomalies, the one or more adjustment recommendations representing control instruction sets for automatically modifying characteristics of the corresponding fund.

Abstract: There is provided a system, method and computer program product for estimating a current value of an intangible asset, by obtaining a source file representing the intangible asset; analyzing the source file to identify at least one characteristic; classifying the source file to belong to at least one class based on the identified at least one characteristic; obtaining one or more evaluation parameters associated with the creator of the intangible asset from at least one first data source; obtaining any historical values associated with the intangible asset; predicting, using a machine learning model, a future value of the intangible asset based on the selected at least one class; the one or more evaluation parameter; and any obtained historical value; and estimating, by the machine learning model, the current value of the intangible asset based on the predicted future value and a pre-set time period.

Abstract: One variation of a method for selectively serving advertising content comprises: receiving identification of an advertisement slot loaded within a webpage; receiving a set of advertisement slot characteristics corresponding to the advertisement slot; accessing a model associating advertisement slot characteristics and user interactions with advertisements; for each target outcome, in a set of target outcomes, calculating an outcome score for the advertisement slot based on the set of advertisement slot characteristics and the model, the outcome score representing a probability of the user interacting with advertising content, presented within the advertisement slot, according to the target outcome; in response to a first outcome score, corresponding to a first target outcome, in the set of target outcomes, exceeding each other outcome score, assigning the first target outcome to the advertisement slot; and selecting a first advertisement, designating the first target outcome, for presentation within the adver

Abstract: A system and method of data record management is provided. The system comprises a processor and a memory coupled to the processor that stores processor-executable instructions that when executed configure the processor to perform the method. The method comprises receiving a plurality of unstructured natural language data records, generating a structured dataset based on the plurality of unstructured natural language data records, transforming the structured dataset to normalize the respective frequency values based on inverse proportionality of the respective frequency values, determining a redundancy prediction value associated with that unstructured natural language data record based on the transformed structured dataset, and displaying on a graphical user interface a message identifying one or more unstructured natural language data records being associated with a redundancy prediction value greater than a threshold value.

Abstract: A method and system for relation discovery from operation data includes classifying categories of extracted entities from operation data into three or more classes identified in a knowledge base. A log affiliation of the extracted entities is determined, and relations of the extracted entities are identified according to a log affiliation. The identified relations information of the extracted entities is associated with operation objects of the operation data.

Abstract: Various embodiments of the present application set forth a computer-implemented method that includes receiving, from a device, a natural-language (NL) request. The method further includes selecting, using the NL request, an intent from a set of intents, wherein the intent is associated with a pre-defined intent template, the pre-defined intent template including a set of property fields that are associated with one or more portions of the NL request. The method also includes determining, based on the NL request, a set of property field values for the set of property fields. The method further includes generating a query to be executed on a field-searchable data source, wherein the query is based on one or more property field values included in the set of property field values. The method also includes receiving, in response to the query, a result that includes a set of event field values. In addition, the method includes causing the device to display at least a portion of the result.

Abstract: A system and method are disclosed to facilitate exploratory data analytics for an enterprise. A storage area network, for a column-oriented relational database management system, may contain electronic records that store enterprise information. A query engine may receive, from a user via an interactive user interface, query parameters associated with the enterprise information. The query engine may then automatically generate an approximate query for exploratory data analytics using query-time sampling, the approximate query being associated with at least one of: (1) a stratified sampler with randomized row access, and (2) a hash-based, outlier aware join sampler. The approximate query may then be executed in connection with the enterprise information in the storage area network, and results of the executed approximate query may be provided to the user via the user interface.

Abstract: A distributed cloud computing system is disclosed that includes a controller configured to deploy a first gateway in a first cloud computing network and a second gateway in a second cloud computing network and logic. The logic, upon execution by one or more processors, causes operations including receiving, from the controller, metadata pertaining to a plurality of constructs, receiving, from each of the first and second gateways, network data, deriving heat map information detailing a density of network traffic at a plurality of geographic locations, wherein the network traffic is transmitted across multiple cloud computing networks, generating a heat map visualization illustrating the density of the network traffic that includes a map of a geographic region as well as an overlay of visual indicators representing the density of the network traffic, and causing rendering of the heat map visualization on a display screen of a network device.

Abstract: A method for teleconferencing between a monitoring device and a user device includes establishing an audio channel connection between the user device and the monitoring device of a remote user; displaying an entry code on a display of the monitoring device; obtaining from a user of the monitoring device a verbal confirmation of the entry code; and, in response to receiving the entry code from the remote user, enabling a camera of the monitoring device. In response to the verbal confirmation, the entry code is sent to the remote user. Enabling the camera of the monitoring device establishes an audio-visual connection between the user device and the monitoring device.

Abstract: A network-based enterprise or other system that makes items available for selection to users may implement selecting user interface elements for inclusion with a search result according to item category features of prior item selections. A search request for an item may be received. An item category for the item may be identified and a user interface element type selection model for the item category may be accessed to select of user interface element types for inclusion in a display of a search result in response to the search request. The user interface element type selection model for the item category may be generated based on features of previous item selections in the identified item category. Content for the selected user interface elements may be determined and a display of the search result may be provided that includes user interface elements generated according to the selected type and identified content may be included.

Abstract: A digital magazine server generates a model to associate topics with content items. To generate the model, the digital magazine server selects a set of content items that have been included in one or more digital magazines. For each content item of the set, the digital magazine server determines a distribution of concepts associated with a content item of the set based on characteristics of digital magazines including the content item of the set and a distribution of topics associated with the content item of the set based on words included in the content item. Additionally, the digital magazine server determines a parameter defining a relationship between the distributions of concepts and the distributions of topics associated with content items of the set. A model based on the distributions of concepts and of topics as well as the parameter is generated and stored for application to content items.

Abstract: Provided is a method, computer program product, and system for improving online behavior in social networking environments using predictive analytics. A processor may monitor communications and user action data of a plurality of users participating in a social networking environment. The processor may analyze the communications and the user action data to determine a user score related to a set of behavioral characteristics for each of the plurality of users. The processor may compare the user score for each of the plurality of users to a set of corrective action thresholds. In response to a first user score associated with a first user meeting one of the set of corrective action thresholds, the processor may implement a first corrective action related to improving behavior of the first user.

Abstract: Systems, devices, media, and methods are presented for generating a language detection model of a language analysis system. The systems and methods access a set of messages including text elements and convert the set of messages into a set of training messages. The set of training messages are configured for training a language detection model. The systems and methods train a classifier based on the set of training messages. The classifier has a set of features representing word frequency, character frequency, and a character ratio. The systems and methods generate a language detection model based on the classifier and the set of features.

Abstract: Techniques for generating a multi-layer network topology on a managed network are described herein. An example method includes receiving, from an internetworking device in a network, one or more encrypted packets in a flow; generating a classification decision corresponding to the flow by traversing one or more decision trees; and providing the classification decision to a controller of the network.

Abstract: Methods and systems for classifying social media users. The system computes a plurality of subgraphs from a user's social graph network and considers which types of subgraphs are overly represented in the user's social network to determine whether a user belongs to a certain class. The system may also consider features based on metadata of the user's network and social interactions occurring in the user's network.

Abstract: Various embodiments describe user segmentation. In an example, potential rules are generated by applying a frequency-based analysis to user interaction data points. Each of the potential rules includes a set of attributes of the user interaction data points and indicates that these data points belong to a segment of interest. An objective function is used to select an optimal set of rules from the potential rules for the segment of interest. The potential rules are used as variable inputs to the objective function and this function is optimized based on interpretability and accuracy parameters. Each rule from the optimal set is associated with a group of the segment of interest. The user interaction data points are segments into the groups by matching attributes of these data points with the rules.

Abstract: A image processing device which can reduce information such as a pattern, a scar and the like on a surface of a drug which are other than an engraved mark, to accurately extract the engraved mark. The image processing device includes: an obtaining unit configured to obtain a plurality of images of a drug having an engraved mark on a surface of the drug, with emitting directions of light to the surface different from each other; an edge image generating unit configured to apply respectively to the plurality of images, edge extracting filters in directions in conformity with the emitting directions, the edge extracting filters having a size in conformity with a width of a groove of the engraved mark, and generate a plurality of edge images; and an image composing unit configured to compose the plurality of edge images and generate a composite image.

Abstract: Disclosed aspects relate to entity model establishment using an infinite mixture topic modeling (IMTM) technique. A set of event data which corresponds to a set of events may be detected. Using the IMTM technique, the set of event data which corresponds to the set of events may be analyzed. Based on analyzing the set of event data using the IMTM technique, a set of entity models for the set of events may be determined. Based on the set of entity models for the set of events, a subset of the set of entity models for the set of events may be established.

Abstract: A natural language (NL) application implements functionality that enables users to more effectively access various data storage systems based on NL requests. The operations of the NL application are guided by, at least in part, on one or more templates and/or machine-learning models. Advantageously, the templates and/or machine-learning models provide a flexible framework that may be readily tailored to reduce the amount of time and user effort associated with processing NL requests and to increase the overall accuracy of NL application implementations.

Abstract: Embodiments can provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement an enhanced corpus management system, the method comprising: identifying one or more functional domain categories; ingesting one or more incoming documents to form an open-domain corpus; for each functional domain category, identifying one or more representative documents to establish a seed sub-corpus; calculating a degree of fit score between each of the one or more incoming documents and the one or more established functional domain category seed sub-corpora; and assigning one or more of the incoming documents to one or more of the functional domain categories based upon the degree of fit score to create an enhanced corpus.

Abstract: Embodiments are directed towards a method for searching data. The method comprises providing an inverted index that comprises at least one record, wherein the at least one record comprises at least one field name and a corresponding at least one field value. The at least one field name and corresponding value are extracted from time-stamped searchable events that are stored in a field searchable datastore and comprise portions of raw data. The at least one record further comprises a posting value that identifies a location in the field searchable datastore where an event associated with the at least one record is stored. The method further comprises receiving an incoming search query that references a field name and evaluating the incoming search query. Furthermore, responsive to the evaluating, the method comprises determining results for the incoming search query using the field searchable datastore or the inverted index.

Abstract: Methods and systems disclosed herein may quantify the content and nature of a first stream of text to detect when the typical composition of the first stream of text changes. Quantifying the content and nature of the first stream of text may begin by generating a baseline representation of the content of the first stream of text as represented by a first matrix. Once generated, the first matrix may be used as a control against subsequently received sequences of text. In this regard, a second matrix may be generated from a second sequence of text and compared to the first matrix to determine the differences between the first sequence of text and the second sequence of text. Once a difference is determined, the difference may be compared to a threshold value and, when the difference exceeds the threshold value, an administrator may be notified and corrective action taken.

Abstract: A computer-implemented technique receives an input expression that a user submits with an intent to accomplish some objective. The technique then uses a machine-trained intent encoder component to map the input expression into an input expression intent vector (IEIV). The IEIV corresponds to a distributed representation of the intent associated with the input expression, within a vector intent vector space. The technique then leverages the intent vector to facilitate some downstream application task, such as the retrieval of information. Some application tasks also use a neighbor search component to find expressions that express an intent similar to that of the input expression. A training system trains the intent encoder component based on the nexus between queries and user clicks, as recorded in a search engine's search log.

Abstract: A first vector representation of a first word within a first narrative text and a machine-generated label corresponding to the first word are constructed. Using the first vector representation, an annotator model is trained. The annotator model is configured to produce a set of probabilities, each probability in the set of probabilities representing a probable output annotation corresponding to a word within a narrative text. The training includes minimizing a difference between a first human-generated label corresponding to the first word and a first probable output annotation corresponding to the first word. Using the trained annotator model and a second narrative text, second training data is generated. The trained annotator model is configured to produce an output annotation corresponding to a word within a narrative text. The second training data is usable to train a relation extraction model.

Abstract: A search system configured to determine, according to a facet hierarchy definition, a facet hierarchy for a set of search results, the facet hierarchy comprising a plurality of facet topics represented by a set of search results. The search is further configured to generate a search user interface comprising a facet hierarchy interface configured to display a representation of the facet hierarchy in conjunction with results from a set of results, update the search results display to display faceted search results and update the facet hierarchy interface to display, in conjunction with the faceted search results, a control to allow a user to select a search facet topic where the search facet topic is a facet topic from the facet hierarchy that is not represented in the faceted search results.

Abstract: A method and system for improving linguistic data and storage technology is provided. The method includes receiving data input text from a user and identifying text within the data input text. The data input text is edited and improvements in the data input text are detected via a machine learning process. In response, a modified version of the user interface is generated for allowing additional users to view and modify additional data input text. Change attributes associated with the data input text with respect to the modified version of the user interface are determined and alternative input suggestions are ranked. Editing data and code are generated in response to an editor engine interacting with a hardware controller. The editing data and code is executed thereby updating and modifying functions associated with software engines to increase an efficiency of future recommendations associated with future data input text analysis.

Abstract: Systems and methods for using an application control prioritization index are disclosed.

Abstract: Methods for providing sliding window pattern matching for large data sets are provided. In one aspect, a method includes accessing a data store comprising a plurality of records each associated with a timestamp and at least one type of measurement value. The method also includes retrieving a multidimensional search query spanning a defined length of time. The method also includes iteratively searching the plurality of records using the multidimensional search query, which is successively reduced in size. Each iteration uses an optimization function to determine similarity values. Once a match with an optimal confidence value is found, the iterative search can be halted. The method also includes outputting a prediction result selected from the plurality of records having associated timestamps after the candidate match assigned to the optimal confidence value. Systems and machine-readable media are also provided.

Abstract: Methods, systems, and computer-readable storage media for selective segmentation of Internet-of-Things (IoT) data in data analytics systems. Implementations can include receiving IoT data from an IoT device, determining that segmentation is to be applied to the IoT data, determining a segment start and a segment end for a segment based on one of a property represented in the IoT data and a property value represented in the IoT data, and providing a table that records the segment independently of the IoT data.

Abstract: In one embodiment, a network assurance system that monitors a network labels time periods with positive labels, based on the network assurance system detecting problems in the network during the time periods. The network assurance system assigns tags to discrete portions of a feature space of measurements from the monitored network, based on whether a particular range of values in the feature space has a threshold probability of occurring during a positively-labeled time period. The network assurance system determines a set of the assigned tags that frequently co-occur with the positively-labeled time periods in which problems are detected in the network. The network assurance system causes performance of a mitigation action in the network based on the set of assigned tags that frequently co-occur with the positively-labeled time periods.

Abstract: An endpoint configured for adaptively generating responses to data queries, comprising program store for storing code, and one or more processors of an endpoint coupled to the program store for executing the code which comprises: (1) Code instructions for detecting a data query from a requester with respect to one or more information resources of the endpoint. (2) Code instructions for adaptively generating a response to the data query. The adaptively generated response comprises data indicative of one or more fictive information resources which are of a similar type as the information resource(s). The response is adaptively generated according to an analysis of data extracted from the data query, the information resource(s), previous interaction of the requester with the endpoint and/or identified information resource operation(s) at the endpoint which precede the detection of the data query. (3) Code instructions for providing the adaptively generated response to the requester.

Abstract: An example operation may include one or more of monitoring, by a resolution node, transaction sequences on a blockchain network, constructing, by the resolution node, a directed acyclic graph (DAG) based on the transaction sequences, computing, by the resolution node, a total order of the transaction sequences from the DAG, maintaining, by the resolution node, local partial orders in final total orderings of blocks, and resolving, by the resolution node, transaction ordering inversions from the local partial orders.

Abstract: In implementations of determining user segmentation based on a photo library, a device maintains digital images in the photo library, as well as metadata associated with the digital images. The device includes a segmentation module implemented to determine characteristics about a user of the device by analysis of the metadata of the digital images. The segmentation module can determine a segmentation based on the characteristics determined about the user. The segmentation includes one or more segments that each represent a generalized aspect of the user, where a generalized aspect is attributable to multiple people and anonymity of the user is maintained. The segmentation module can associate an anonymous identifier with the segmentation effective to maintain the anonymity of the user and privacy of the metadata. The segmentation and the anonymous identifier can then be communicated to a marketing system that generates personalized marketing messages based on the segmentation.

Abstract: Systems, methods, and computer program products for determining an application status of an applicant for an educational program may include receiving cohort performance data comprising first data entries for participants that have respectively achieved outcomes for the educational program and applicant performance data comprising second data entries for the applicant, calculating adjusted cohort performance data based on the cohort performance data and first data characteristics, providing a predictor model based on the adjusted cohort performance data and the outcomes, sequentially changing predictive parameters of the first data characteristics to create second data characteristics and creating an adjusted predictor model based on the second data characteristics and the outcomes, calculating adjusted applicant performance data based on the applicant performance data and the second data characteristics, and calculating a probability of success for the applicant in the educational program based on the adjust