Abstract: A system and method for retrieving and extracting security information is provided. The method includes (i) extracting seed Uniform Resource Locators (URLs) from social media based on keywords that are identified for each sub-domain, (ii) crawling a security related content in the extracted seed URLs to determine relevant URLs that are related to a security domain from the extracted seed URLs, (iii) classifying the security related content into sub-domains of security to obtain domain coverage, (iv) extracting text that include acronyms from the relevant URLs, (v) automatically evolving a security ontology based on extracted text using a Long Short-Term Memory (LSTM) deep Learning model, (vi) ranking search results by accessing credibility of the URLs that include the security related content based on domain relevance and (vii) providing the ranked search results that includes trends.

Abstract: In a multitenant data platform architecture, one or more supporting data tables are used to write and store tenant data responsive to data write requests. Based on the contextual data returning an indication of a data corruption in one or more supporting data structures, an action associated with the data transaction thread is performed. A log of data corruptions and corresponding call stack trace data may be generated. The data transaction thread may be allowed to continue to execute statements that modify data tables, or the data transaction thread may be terminated. Data corruptions may be compensated for by nullifying data changes caused by corruption causing call sites. Verification methods may be used to ensure correctness of data within a transaction thread.

Abstract: Methods, systems, and computer program products for generating an executable code based on a document are disclosed. Rules are identified in a document, the identified rules are translated into encoded rules, and an executable code is generated from the encoded rules. Identification of rules includes splitting a text of the document into a plurality of sentences; and for each sentence of the plurality of sentences, determining whether the sentence corresponds to a rule. Translation of an identified rule into an encoded rule includes extracting, from the identified rule, elements corresponding to predefined categories; determining one or more relationships between the extracted elements; and translating the one or more determined relationships into a structured expression. Generating the executable code from the encoded rules includes translating the structured expression associated with the identified rule into a programming language query.

Abstract: In various embodiments, a natural language (NL) application receives a first incomplete natural language (NL) request, and generates one or more request completion recommendations based on at least the first incomplete NL request and a first recommendation model, where the first recommendation model is generated via a machine learning algorithm applied to a first data dependency model and a first request completion model. The NL application receives a selection of a first request completion recommendation included in the one or more request completion recommendations, generates a complete request based on the first incomplete NL request and the first request completion recommendation, and causes the complete request to be applied to the data storage system.

Abstract: Aspects of distributed ledger technology are leveraged to verify subrogation settlements. In particular, two parties to a subrogation claim provide cryptographic hashes to a subrogation demand smart contract stored at an address on a blockchain. The subrogation demand smart contract determines that the parties have reached an agreement by determining that the cryptographic hashes match. A settlement amount from the subrogation claim may be appended to a set of settlement amounts to determine a net settlement amount to facilitate a single payment between the parties on a periodic basis, such as daily, to alleviate the need for the parties to send or receive a payment for each individual settlement amount.

Abstract: An artificial intelligence engine that has two or more modules cooperating with each other in order to create one or more machine learning models that use an adaptive semantic learning for knowledge representations and reasoning. The modules cause encoding the representations and reasoning from one or more sources in a particular field with terminology used by one or more human sources in that field into a set of rules that act as constraints and that are graphed into a neural network understandable by a first machine learning model, and then ii) adapting an interpretation of that set of encoded rules. The understanding of that set of encoded rules is adapted by i) allowing for semantically similar terms and ii) by conclusions derived from training data, to create an understanding of that set of encoded rules utilized by the machine learning model and the AI engine.

Abstract: A computer implemented method for multi-document question answering is performed on a server communicating with a client device over a network. The method includes receiving a runtime question from a client device and retrieving runtime documents concerning the runtime question using a search engine. Runtime answer samples are identified in the retrieved runtime documents. A neural network model, trained using distant supervision and distance based ranking loss, is used to compute runtime scores from runtime question data representing the runtime question and from a runtime answer sample representing a first portion of text from the corpus of documents, where each runtime score represents a probability an answer to the runtime question is present in the runtime answer samples. A runtime answer is selected from the runtime answer samples corresponding to the highest runtime score sent to the client device.

Abstract: A virtual assistant server receives a user input from a virtual assistant interface available on a client system associated with a user identified by a user identifier. Upon receiving the user input, the virtual assistant server creates a search network of repositories not associated with the user identifier by determining, for the received user input, a priority score of each repository not associated with the user identifier based on interactions of the user identifier through the virtual assistant interface. Further, the virtual assistant server searches, for the received user input, in a repository associated with the user identifier and in the repositories in the search network. Based on the searching, a group of one or more results corresponding to the received user input are identified and returned to the client system associated with the user identifier.

Abstract: A computer-implemented method for storing blocks of a file in a heterogeneous environment. The method may comprise receiving a command header for an operation associated with a file from a first data node, matching the enhanced metadata with capabilities of a second data node, and generating a block layout map for the file based at least in part on the enhanced metadata and the capabilities of the second data node. The command header may include enhanced metadata associated with a file, and the enhanced metadata may comprise a type of workload that generated the file and a data access pattern.

Abstract: A social electronic learning system, including a plurality of computing devices for communicating with a plurality of users in an educational community, and at least one server in communication with each of the plurality of computing devices, each server in communication with at least one data storage device configured to host a plurality of electronic portfolios, each electronic portfolio associated with one or more users of the plurality of users in the educational community, wherein each server is configured such that one or more users may associate one or more digital items with each electronic portfolio, and the plurality of users may take actions on the digital items in each electronic portfolio depending on authorization criteria.

Abstract: A system for monitoring one or more lab processes and predicting their outcomes is provided. The system comprises a data acquisition module configured to acquire at least one of: ambient data and experimental data in real time from one or more lab resources and instruments. The system further comprises a process setup and monitoring module configured to receive the acquired data and facilitate setting-up and monitoring of one or more processes in real time utilizing the received data. The system furthermore comprises an experiment prediction module that is configured to obtain data from the data acquisition module and process setup and monitoring module. The experiment prediction module is further configured to employ one or more machine learning techniques on the obtained data to generate one or more patterns to predict outcomes of the one or more processes conducted in the lab in real time.

Abstract: Methods and systems are disclosed for securely granting access to physical resources. An encrypted communication is received from a client hosted on a user device requesting resource availability data for a resource configured to be shared amongst a plurality of physical resource users in a time displaced manner. Resource availability data for the resource is used to populate a resource availability interface presented by the client hosted on the user device. An encrypted communication is received from the client requesting access to the resource for a specified period of time. A category for the requested access to the resource is determined. An inference or learning artificial intelligence engine is used to determine whether access for the resource is to be granted to the user for the specified period of time. In response to determining that access is to be granted to the user an encrypted code is transmitted to the user device.

Abstract: The present disclosure is directed towards benchmarking online activity via encoded links generated by an online activity benchmarking system. The method may include identifying by a server of an online activity benchmarking system, for an information resource, a plurality of encoded links encoded by the server of the online activity benchmarking system and linked to the information resource, receiving by the server, via the identified plurality of encoded links, a plurality of requests to access the information resource, identifying by the server, for each request of the plurality of requests to access the information resource, one or more attributes corresponding to the request, categorizing by the server, the plurality of requests to access the information resource based on the one or more identified attributes, and providing by the server, for presentation, an output indicating statistics corresponding to the categorized plurality of requests based on the one or more identified attributes.

Abstract: A method provides statistically reliable life experiences to guide a user to achieve personal goals related to education, career, and other life choice options. Based on the user's specific query, the method conducts searches and analyzes the search results for statistical significance. Internal anonymized databases containing life experiences and extensive external databases are used in the search and analysis. Subsequently the method sends the most relevant life experiences to the user with optional link to specific providers related with the query to the user for achieving the user's personal goals. The method may notify the user for lack of records/data and creates a survey to all users to contribute answers and/or life experiences to the specific query. Further, the method allows service providers and law enforcement personnel to conduct queries with specific purposes such as medical survey or criminal investigation with a subpoena.

Abstract: A term-weighting and document-scoring function is used to search for a command line interface (CLI) script that is likely relevant to an operation specified in a natural language query. CLI scripts are created to perform various operations of a CLI-based application. A CLI script is associated with a description document having keywords associated with the individual commands used in the CLI script. The relevance of a CLI script to an intended operation is based on the term-weighting and document-scoring function which is applied to each component of each command in a CLI script and weighted accordingly.

Abstract: A method implements a source rank metric of measuring sources of influence. The method includes processing transactions to generate a graph. The method further includes processing the graph to select nodes. A node is identified as one or more of a source node and a destination node of an edge of the graph. The method further includes processing source ranks, of the nodes, to update the source ranks. A source rank is calculated using a subset of indegree values and a subset of outdegree edges. The method further presenting identifiers, of multiple entities represented by the nodes, sorted using the source ranks.

Abstract: A first user request which specifies a target document set wherein a first subset of the documents is flagged by a user. A primary flag table is created for the target document set. A first document subset is created matching the first user request. It is determined whether a number of flagged documents exceeds a first threshold. If so, a secondary flag table is created for the first document subset and flag data corresponding to the first document subset is stored in the secondary flag table. The flag data in the secondary flag table is merged into the primary flag table.

Abstract: Techniques for generating and leveraging heterogenous edges in an online connection network are provided. In one technique, a particular user is identified. The identification may be made in response to a computing device of the particular user requesting data from a particular system. For each entity type of multiple entity types: (1) a set of entities of the entity type is identified based on one or more attributes of the particular user; (2) a ranking of the set of entities is generated based on one or more criteria; and (3) a subset of the set of entities is selected and included in a final set of entities. The final set of entities includes entities from different entity types of the multiple entity types. The final set of entities is transmitted over a computer network to be presented concurrently on a computing device of the particular user.

Abstract: A processor(s) receives a profile of a user and ranks physical activities in a relational data structure based on the user profile to create a customized relational data structure of ranked physical activities for the user. The relational data structure maps physical activities to one or more associated attributes. An activity adviser model is produced specific to the user via machine learning by obtaining data related to physical activities performed by the user from one or more sensors, and receiving user wellness-related feedback related to the user-performed physical activities. The user wellness-related feedback includes a user ranking of one or more aspects of the user-performed physical activities. The activity adviser model specific to the user is built by using the customized relational data structure, the data and the user wellness-related feedback. The processor(s) uses the activity adviser model to provide an activity-related recommendation to the user.

Abstract: A system includes reception of a definition of a first attribute to associate with a logical object of the first application, reception of a definition of a second attribute to associate with a second logical object of the first application, determination, based on the definition of the first attribute and the definition of the second attribute, that the first attribute and the second attribute are associated with a same semantic, based on the determination, generation of e a first identifier associated with the first attribute and the second attribute and storing the first identifier associated with the first attribute and the second attribute in a first data schema associated with the first application, and storage of the first identifier associated with the first attribute and the second attribute in an analytics schema associated with an analytics application.