Abstract: One embodiment of the invention provides a method for terminology ranking for use in natural language processing. The method comprises receiving a list of terms extracted from a corpus, where the list comprises a ranking of the terms based on frequencies of the terms across the corpus. The method further comprises accessing a domain ontology associated with the corpus, and re-ranking the list based on the domain ontology. The resulting re-ranked list comprises a different ranking of the terms based on relevance of the terms using knowledge from the domain ontology. The method further comprises generating clusters of terms via a trained model adapted to the corpus, and boosting a rank of at least one term of the re-ranked list based on the clusters to increase a relevance of the at least one term using knowledge from the trained model.

Abstract: Various embodiments provide a data analysis apparatus, system, and method. The data analysis apparatus may collect data of a network node in a mobile access network, and then perform data analysis and adjust a configuration parameter of the network node, to implement targeted data analysis and parameter adjustment for the network node, so that a speed of data analysis and configuration parameter adjustment can be improved. In addition, modules of the data analysis apparatus may run in parallel, so that the speed of data analysis and configuration parameter adjustment can be further improved.

Abstract: A method for intent mining that includes: receiving conversation data; using an intent mining algorithm to automatically mine intents from the conversation data; and uploading the mined intents into the conversational bot. The intent mining algorithm may include: analyzing utterances of the conversation data to identify intent-bearing utterances; analyzing the identified intent-bearing utterances to identify candidate intents; selecting salient intents from the candidate intents; grouping the selected salient intents into salient intent groups in accordance with a degree of semantic similarity; for each of the salient intent groups, selecting one of the salient intents as the intent label and designating the others as the intent alternatives; and associating the intent-bearing utterances with the salient intent groups via determining a degree of semantic similarity between the candidate intents present in the intent-bearing utterance and the intent alternatives within each group.

Abstract: A real-time messaging system platform receives from, a communication application installed on a first user communication device, a first user identifier, an indication that a messaging service message composed by the first user is being directed to a first destination associated with a second user, and an identification of data present in the messaging service message. The identification of the data and a message transmission history of the first user is used to enable selection of a message of a first entity. The selected message of the first entity is caused to be displayed by the communication application within a message framework that frames the first user messaging service message. The first entity message is caused to be included in the messaging service message transmitted to the second user device, wherein the first entity is not provided with access to the identity of the first user or the second user.

Abstract: The system provides a method and apparatus for generating a profile of a first user, where the profile comprises interaction parameters associated with the user. The system can generate a profile of a second user, also comprising interaction parameters of the second user. The system can then provide suggestions to either or both the first and second user for interacting with each other.

Abstract: Methods, apparatus, and processor-readable storage media for determining a set of access points in response to a geo-location request are provided herein. An example computer-implemented method includes determining, based on geo-location information comprising a set of at least two coordinates attributed to at least one device, geo-location information attributed to a set of multiple access points; identifying two or more access point subs-sets from the set of access points, wherein each of the access point sub-sets comprises one or more of the access points; comparing geo-location information attributed to additional devices to the access points within each of the sub-sets; and outputting, to the at least one device as a response to a request for geo-location information comprising a set of at least two coordinates and based on said comparing, information pertaining to at least one of the sub-sets and the geo-location information attributed to the at least one device.

Abstract: This disclosure relates generally to system and method for hierarchical category classification of products. Generally in supervised hierarchical classification, the hierarchy structure is predefined. However, majority of the current machine learning methods either expect the model to learn the hierarchy from the data or requires separate models trained at each level taking the prediction of previous level as an additional input, thereby increasing latency in achieving training accuracy and/or requiring an explicit maintenance module to orchestrate inference and retrain multiple models (corresponding to the number of levels in the hierarchy). The disclosed method and system allows the predefined knowledge about hierarchy drive the learning process of a single model, which predicts all levels of the hierarchy. The disclosed multi-layer network model arrives at a consensus based on prediction at each level, thereby increasing the accuracy of prediction and reducing the training time.

Abstract: Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Abstract: An intention identification method includes generating a heterogeneous text network based on a language material sample; using a graph embedding algorithm to perform learning with respect to the heterogeneous text network and obtain a vector representation of the language material sample and a word, and determining keywords of the language material sample based on a similarity in terms of a vector between the language material sample and the word in the language material sample; training an intention identification model until a predetermined training termination condition is satisfied, by using the keywords of the language material samples, and obtaining the trained intention identification model; and receiving a language material query, and using the trained intention identification model to identify an intention of the language material query.

Abstract: Systems and methods for automated document graphing are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for automated document graphing may include: (1) receiving, from a document repository, a plurality of source documents; (2) extracting text from each of the plurality of source documents; (3) cleaning the extracted text by removing unnecessary characters from the extracted text; (4) rewriting multi-word proper nouns in the extracted text; (5) converting a plurality of words in the extracted text to lemma form; (6) rewriting compound terms in the extracted text; (7) removing stop words from the extracted text; (8) representing each of the remaining words in the extracted text as a vector; and (9) storing the vectors in a library.

Abstract: A unified access layer (UAL) and scalable query engine receive queries from various interfaces and executes the queries with respect to non-heterogeneous data management and analytic computing platforms that are sources of record for data they store. Query performance is monitored and used to generate a query performance model. The query performance model may be used to generate alternatives for queries of users or groups of users or to generate policies for achieving a target performance. Performance may be improved by monitoring queries and retrieving catalog data for databases referenced and generating a recommendation model according to them. Duplicative or overlapping sources may be identified based on the monitoring and transformations to improve accuracy and security may be suggested. A recommendation model may be generated based on analysis of queries received through the UAL. Transformations may be performed according to the recommendation model in order to improve performance.

Abstract: In one embodiment, the disclosed technology involves: digitally generating and storing a machine learning statistical topic model in computer memory, the topic model being programmed to model call transcript data representing words spoken on a call as a function of one or more topics of a set of topics that includes pre-seeded topics and non-pre-seeded topics; programmatically pre-seeding the topic model with a set of keyword groups; programmatically training the topic model using unlabeled training data; conjoining a classifier to the topic model to create a classifier model; programmatically training the classifier model using labeled training data; receiving target call transcript data; programmatically determining at least one of one or more topics of the target call or one or more classifications of the target call; and digitally storing the target call transcript data with additional data indicating the determined topics and/or classifications of the target call.

Abstract: This application discloses a summary generation using natural language processing via method, apparatus, and a computer device. The summary generation is implemented by obtaining a document, the document including at least one sentence. The summary generation is further implemented by extracting m candidate sentences from the document by using an extractive model. The summary generation is further implemented by outputting target words according to the m candidate sentences by using an abstractive model, and generating a summary according to the target words.

Abstract: An information processing system includes: a plurality of vehicles; and a server configured to communicate with the plurality of vehicles, wherein each of the plurality of vehicles is configured to detect wind information by using a wind detection device mounted on each of the plurality of vehicles, and send probe data to the server, the probe data including the wind information and position information on each of the plurality of vehicles at a time when the wind information was detected, and the server is configured to store the probe data received from the plurality of vehicles in a database, and provide information to a client by using the probe data stored in the database.

Abstract: A set of electronic slide decks is searched using a target slide of a first electronic slide deck, each of the electronic slide decks containing a sequence of slides to be presented individually. A computer system receives from a user input individually selecting the target slide as a search input from the slides of the first electronic slide deck, compares the target slide with the slides of each electronic slide deck in the set to determine whether any of those slides matches the target slide, so as to determine, for each of the set of electronic slide decks, whether that electronic slide deck contains at least one slide that matches the target slide; and displays a set of search results in response to the user input, wherein each of the search results represents one of the electronic slide decks determined to contain at least one matching slide.

Abstract: A system for sharing a metadata store between a relational database and an unstructured data source is disclosed. The unstructured data source may comprise a Hadoop system with a Hadoop Distributed Files System.

Abstract: A system for short text identification can determine a plurality of topics and a representative noun that identifies each of the topics in a data repository. The system can determine a co-occurrence matrix for the training words stored in the corpus and determine a word vector embedding for each of the training words in the corpus to relate each of the training words in the corpus to other ones of the training words in the corpus in an n-dimensional vector space. The system can determine word tokens for words in short text in documents in the data repository that is separate and distinct from the corpus and determine sentence vectors for short text based on the word vectors in each short text and determine a plurality of topics in the documents based on clustering of sentence vectors, wherein the plurality of topics indicates topics that are predominant in the documents in the data repository.

Abstract: Disclose herein are applications and platforms for streamlined production of charts and reports from databases containing time series datasets and/or timestamped data. The applications described herein may employ dynamically retrieve data from data centers to quickly provide options to the user. The platform further allows configuration of the charts and/or reports by providing lists of metrics that may be available in the selected data, and lists of transforms that may be applied to the data. The application may employ dynamic user interfaces, which provide processing of the received time series datasets in a data agnostic manner. As a result, the systems and methods described herein may allow generating charts and reports using a streamlined workflow.

Abstract: Provided here are methods, systems, and apparatus, including computer programs encoded on computer storage media, for searching new media information using search engine. One of the methods includes: receiving search information input by a user using a search engine, and sending the search information to a server; obtaining, from a search result returned by the server, element data of new media information related to the search information; and displaying, in a current search result page of the search engine, the element data of the new media information in a new media display format, wherein the element data is data that is directly displayable without a page jump in response to an operation of the user on the element data.

Abstract: In an example embodiment, a content agnostic approach to quality of assessment of social media posts or other items or content in an online network, such as a social networking service, is utilized. Specifically, information about members contained in member profiles may be used to derive meaningful insights about posts they interact with collectively.

Abstract: The information processing device receives question information, converts words contained in the received question information into word vectors including a plurality of element values respectively associated with a plurality of elements. The information processing device refers to the memory that stores, in association with the elements, specific information specifying the strength of specific meanings contained within the element values associated with the elements and acquires, using the specific information, a plurality of semantic information items indicating the strength of the specific meanings respectively contained within the plurality of element values included in the word vectors. The information processing device performs an evaluation relating to the received question information on the basis of the acquired plurality of semantic information items.

Abstract: A method for categorizing streamed music based on a sample set of RTP scores for predetermined tracks. High-level acoustic attributes for tracks are determined by an analyzed extraction of low-level data from the tracks. The high-level acoustic attributes are used to develop computer-derived RTP scores for the tracks based on the sample set, which includes RTPs score for a plurality of possible combinations of a rhythm score (R), a texture score (T), and a pitch score (P) respectively from a R range, a T range, and a P range. At least some of the RTP scores correspond to human-determined RTP scores for predetermined tracks among a plurality of predetermined tracks. Each RTP score corresponds to a category among a plurality of categories. The computer-derived RTP scores are used to determine a category for each track among the plurality of categories. Playlists of the tracks are based on one or more of the categories.

Abstract: In one or more embodiments, a system and/or a method may implement: receiving data representing different performance behavior metrics that are associated with software instances that are respectively associated with consumer computers and that specify values of performance factors of the software instances as the consumer computers interoperate with the software instances; determining data throughput values that represent processing throughput of the software instances; determining relative capacity values of the software instances; adapting each of prediction models to the relative capacity values; determining correlation coefficients from the prediction models and the multiple data throughput values; executing a prediction model of the prediction models associated with a correlation coefficient closest to a value of “1” to result in outputting threshold values associated with the performance factors; and transmitting the threshold values to a particular consumer computer among the consumer computers as par

Abstract: The present disclosure provides various systems and methods for indexing digital (electronic) documents and providing various error reporting and identification functions. The systems and methods may utilize various software, hardware, and firmware modules to identify notations, such as sheet names, anchors, and anchor references on construction documents. Various algorithms and methods may be employed to identify errors, erroneous notations, missing sheets, missing details, and/or the like to aid in the correction of construction documents. Identified notations are indexed and used to create hyperlinked pages that are easily navigable. In some embodiments, the hyperlinked pages may include previous- and next-sheet hyperlinks that allow for direct navigation within a set of pages, according to an order provided in an index sheet (e.g., a table of contents sheet).

Abstract: A computer implemented method for searching data in a plurality of data sources is described. At a host system, a request to search a local data source is received. The request is associated with a user account of the local data source. The request is processed to determine one or more third party data sources associated with the user account. Local search parameters associated with the local data source and third party search parameters associated with the one or more third party data sources are dynamically assembled. The local search parameters and the third party search parameters are transmitted to a client device for display. A host system comprising a processor and memory storing instructions for implementing the method is also described.

Abstract: Techniques for efficient, accurate, and secure computation of a differentially private median of the union of two large confidential datasets are disclosed. In some example embodiments, a computer-implemented method comprises obtaining secret shares of a first dataset of a first entity, secret shares of a second dataset of a second entity, secret shares of gap values for the first dataset, secret shares of gap values for the second dataset, secret shares of probability mass values for the first dataset, and secret shares of probability mass values for the second dataset. The probability mass values may be computed via an exponential mechanism. In some example embodiments, the computer-implemented method further comprises determining a median of a union of the first dataset and the second dataset using an inverse transform sampling algorithm based on the obtained secret shares, and then performing a function of a networked computer system using the determined median.

Abstract: A content recommendation method and system are described, according to various implementation. In an implementation, the method and system generate a record identifying a set of content items interacted with by users of a content system, where each content item is associated with one or more topics. A confidence score associated with each of a set of topics associated with the set of content items is generated, where the confidence score represents a quantity of instances a respective topic appears in a collection of content items. A portion of the set of topics having a confidence score that exceeds a threshold confidence level is determined. A search of the collection of content items is executed to identify a serendipitous candidate content item that includes multiple portions of the set of topics previously interacted with by a user. The method and system determines, based on the record, that the candidate serendipitous content item has not been interacted with by the user system.

Abstract: Various embodiments are generally directed to techniques to provide specific vehicle recommendations to generic user requests. Various techniques, methods, systems, and apparatuses include utilizing one or more tags generated by application of a machine learning model to a data source, where the data source may include generic and specific language with respect to one or more automobiles or vehicles, to provide a recommendation for a particular automobile in response to a user request for a suggestion.

Abstract: Systems and techniques are described that enable users to capture and share content through a social network application and/or service with other users. A device associated with a first account may display a camera capture interface including a control associated with a second account and may receive a selection of the control associated with the second account. The device may capture content responsive to the selection and present a preview screen of captured content. The device may receive an indication (e.g., a swipe gesture, selection of a send control, etc.) to perform an action with respect to the captured content, such as sending the captured content to the second account.

Abstract: A document recommendation method based on a semantic tag and a document recommendation device. The method includes: for each document, acquiring a first candidate tag set corresponding to the document, and processing each first candidate tag in the first candidate tag set corresponding to the document to obtain a second candidate tag set corresponding to the document; performing normalization processing on each second candidate tag in the second candidate tag set corresponding to the document to obtain a third candidate tag set corresponding to the document; performing expanding process on each third candidate tag in the third candidate tag set corresponding to the document, and acquiring a fourth candidate tag set corresponding to the document, to form a document library having semantic tags; and recommending a target document obtained from the document library having semantic tags to the user, according to historical semantic tag.

Abstract: The present invention may be a method, a computer system, and/or a computer program product. An embodiment of the present invention provides a computer-implemented method for obtaining one or more candidates for a relationship type and its label. The method comprises the following steps: analyzing a document annotated with entity types, the analysis comprising counting the number of pairs of co-occurring entity types in each sentence in the document, and judging whether there exists, in the document, a candidate for a label of a relationship type which shows relationship between or among the co-occurring entity types and, if the judgment is positive, storing a candidate for the relationship type and a candidate for its label; and outputting a result of the analysis. The method may further comprise, if the judgment is negative, storing a candidate for the relationship type without a candidate for its label.

Abstract: A system, computer program product, and method is described to propose a method to automatically suggest a visualization providing the best insight for a given dataset, by maximizing an utility function computed on properties of the input data, and previously used visualizations by the same user and for the same data. In one example method for recommending a data visualization in a computer system includes receiving at least one input dataset and at least one set of previous visualizations. A utility function is accessed. A set of potential visualizations is computed using the input dataset and the set of previous visualizations. A recommendation is selected for a proposed visualization from the set of potential visualizations by maximizing a value of the utility function, whereby the proposed visualization is a new visualization not in the set of previous visualizations.

Abstract: A computer-implemented method comprises analyzing content sections on each of a plurality of open browser pages using natural language processing to identify one or more topics on each of the plurality of open browser pages; calculating a respective relevance score for each of the content sections; grouping each of the plurality of topics into one of a plurality of topic groups; calculating a respective group ranking for each of the plurality of topic groups based on the respective relevance score for each content section. The method further comprises, for each topic group, assigning the respective group ranking to all of the content sections corresponding to the respective topic group; and, for each of the plurality of open browser pages, selecting at least one content section having a highest group ranking and modifying a display of the respective open browser page to direct attention to the selected content section.

Abstract: Briefly, embodiments disclosed herein relate to acquisition of web content publishing.

Abstract: Disclosed herein are systems and methods for classifying unstructured datasets according to a classification system and generating an enhanced, classified and structured data-set enabling efficient supplemental computer-based processing. The exemplary computer-implemented classification algorithms involve, for each entry in the input dataset, semantically interpreting a text-based occupation description, analyzing the description according to an ontology of interrelated “concepts” and identifying semantically relevant concept(s) and any associated descriptors specific to the classification system. The system is also configured to expand the list of relevant concepts to include concepts that bear a relationship thereto, scoring the various concepts and associated descriptors and identifying the concept(s) and descriptors that most accurately correspond to the input data.

Abstract: A system to extract relevant keywords or business tags that describe a company's business is provided. The keyword extraction system utilizes a smart crawler to identify and crawl product pages from a company's website. These pages serve to provide textual descriptions of product offerings, solutions, or services that make up the company's business. The keyword extraction system combines these web documents with other textual descriptions of companies, e.g. from third party data vendors or other public data sources and company databases, to form a corpus of documents that describe companies. The corpus of documents and keywords are processed to segment the plurality of companies into subsets by applying a clustering technique and to provide visualization of the clusters with business tags.

Abstract: Techniques for assessing risks of IoT devices. A system utilizing such techniques can include a packet analysis based IoT device risk assessment system and an IoT device risk assessment system. A method utilizing such techniques can include extraction of IoT device risk factors from a device profile of an IoT device and application of assessment weights to the IoT device risk factors to assess a risk level of an IoT device.

Abstract: An example method of document clustering comprises: representing each document of a plurality of documents by a vector comprising a first plurality of real values, wherein each real value of the first plurality of real values reflects a first frequency-based metric of a term comprised by the document; partitioning the plurality of documents into a first set of document clusters based on distances between vectors representing the documents; representing each document cluster of the first set of document clusters by a vector comprising a second plurality of real values, wherein each real value of the second plurality of real values reflects a second frequency-based metric of a term comprised by the document cluster; and partitioning the first set of document clusters into a second set of document clusters based on distances between vectors representing the document clusters of the first set of document clusters.

Abstract: There is a need for solutions that perform entity sensitivity classification for a database entity associated with plurality of database elements. This need can be addressed by, for example, for each database element, generating element tokens for the database element based on a textual identifier for the database element, generating token combinations for the database element based on the element tokens for the database element and a token order associated with the textual identifier, generating a token-combination document for the database element based on the token combinations for the database element, and generating element feature data for the database element based on the token-combination document for the database element, and determining the entity sensitivity classification on each element feature data associated with a database element of the plurality of database elements and using a sensitivity classification model.

Abstract: A method for displaying information and receiving inputs with a medical device includes displaying a first interface on a display of the medical device, receiving various inputs from a user, displaying a second interface on the display of the medical device, and receiving vital signs data from the patient using the second interface. The first interface includes a login area including one or more prompts for information identifying a user of the medical device and profile selection area including two or more profiles offered by the medical device. The method further involves receiving user identifying information from the user via the login area, confirming the user identifying information, activating the profile selection area in response to confirming the user identifying information, receiving a profile selection from the user via the profile selection area, and receiving patient identification information from the user with the medical device.

Abstract: Documents needing to be analyzed for various reasons, such as financial crimes, are ranked by examining the topicality and sentiment present in each document for a given subject of interest. In one approach a given document is classified to determine its category, and entity recognition is used to identify the subject of interest. Passages from the document that relate to the entity are grouped and analyzed for sentiment to generate a sentiment score. Documents are then ranked based on the sentiment scores. In another approach, a classification probability score is computed for each passage representing a likelihood that the passage relates to a category of interest, and the document is ranked based on the sentiment scores and the classification probability scores. The category classification uses an ensemble of natural language text classifiers. One of the classifiers is a naïve Bayes classifier with feature vectors generated using Word2Vec modeling.

Abstract: Systems, apparatuses, and methods for the interpretation and routing of short text messages, such as those that might be received as part of a “chat” between a customer and a customer service representative. In some embodiments, this is achieved by constructing word “vectors” based on the text in a message, with a token corresponding to each word. The word vectors are then compared to a set of mutually orthogonal unit vectors representing the “classes” or “categories” of messages that are received and are intended to be acted upon by a person or automated process. The orthogonal class unit vectors are generated by training a machine learning model using a set of previously classified text or messages.

Abstract: A system is provided for decomposing events from managed infrastructures. A first engine is configured to receive message data from a managed infrastructure that includes managed infrastructure physical hardware that supports the flow and processing of information, The at least one engine is configured to determine common characteristics of events and produce clusters of events relating to the failure of errors in the managed infrastructure. Membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in a physical hardware of the managed infrastructure directed to supporting the flow and processing of information. The first engine is configured to create one or more situations that is a collection of one or more events or alerts representative of the actionable problem in the managed infrastructure. A second engine is configured to determine one or more common steps from events and produces clusters relating to events.

Abstract: Disclosed are techniques for the automated discovery and extraction of discourse phrases, or in other words terms that representative of a topic or concept communicated via a plurality of electronic documents, to facilitate the generation of a language model that is applicable to interpreting commands for invoking application-based actions via a digital assistant device. An electronic document corpus can be generated having a plurality of electronic documents that are clustered based on entropy, among other things. The clusters can be associated with a corresponding plurality of cluster attractors that are generally representative of a context of the documents included therein. The clusters can be grouped based on determined relationships, such that the groups can be further analyzed and terms or phrases representative of a discourse associated with the grouped documents can be determined.

Abstract: The material development assistance system includes a first control unit giving, based on input information inputted as the prototype plan of the material and a keyword configuring a keyword tree stored in a storage unit, a prototype ID for identifying the prototype plan, a second control unit associating the keyword corresponding to the input information given the prototype ID with the index of the input information and accumulating the associated index in the storage unit as a tree structure for each classification group, a third control unit determining whether or not the index for the classification group accumulated in the storage unit and the input information are in a predetermined relation and when determining that the index and the input information are in the predetermined relation, reading a past prototype plan using the index from the storage unit, and a fourth control unit outputting a new prototype plan.

Abstract: To provide an optimum hyper parameter for determining a learning model using a natural language as a target. An optimization apparatus including: a processor and a memory and performing learning of a document set by natural language processing has an optimization section configured to determine a hyper parameter satisfying a predetermined condition on the basis of previously set group data, generate a learning model by the determined hyper parameter, and acquire a high-dimensional vector from the learning model; and a high-dimensional visualization section configured to convert the high-dimensional vector of a word or document as an analysis target on the basis of the group data.

Abstract: Systems and methods are disclosed for news events detection and visualization. In accordance with one implementation, a method is provided for news events detection and visualization. The method includes, for example, obtaining one or more documents, the one or more documents being grouped into one or more clusters having a score, and the one or more clusters being grouped into one or more megaclusters, presenting information associated with the one or more documents on one or more timelines, wherein the one or more documents are grouped into different megaclusters being presented in a visually distinct way, and filtering the presented information based on the scores associated with the one or more clusters.

Abstract: Medical imaging study summary engine mechanisms are provided. The mechanisms receive a medical imaging study having data representing a plurality of medical images of a patient. The mechanisms generate a temporal trajectory data structure of at least a subset of the medical images in the plurality of medical images, wherein the temporal trajectory data structure specifies topological changes in temporally subsequent medical images in the plurality of medical images. The mechanisms select medical image data corresponding to selected medical images from the medical imaging study data structure based on the temporal trajectory data structure. The mechanisms output the selected medical image data via a medical imaging study user interface.

Abstract: Embodiments of the invention are directed to methods and devices for predicting interactions. One embodiment is directed to a method comprising receiving, by one or more computers, interaction data for a plurality of known interactions between resource providers and users, and creating a topological graph based on the plurality of known interactions. The method may further comprise determining, by the one or more computers, a plurality of communities to form a predictive model, and receiving a request for a prediction. In addition, the method may comprise applying the request to the predictive model, by the one or more computers, by identifying a community in the plurality of communities corresponding to the request, determining a node within the identified community, and providing information regarding the node as the requested prediction.

Abstract: A method for enabling a user to define a Life Based VR experience to align with the user's life. The user and partners provide custom information and settings about the user's life state which allows the user to integrate information to the Life Based VR experience. The partners may use the user's information to integrate its information, which is then interacted with in a Life Based VR experience by a user, according to various custom VR parameters. The partners may also use the user's interactions with the Life Based VR experience to assess behavior as compared to the user's life state, and the users may assess the partner's accuracy of information delivery when compared to the user's life state. The method also enables the user and partner to interact in a marketplace to procure the information relating to the user's life, user ratings, and partner ratings.