Abstract: Aspects of the present invention disclose a method for managing aggregated comments of a forwarded media based on the sentiments of the forwarded media and relevance to a user. The method includes one or more processors identifying a user based at least in part on information provided by the user. The method further includes accessing user activity data utilizing the information provided by the user. The method further includes generating a first profile corresponding to the user based at least in part on the user activity data. The method further includes determining one or more preferences of the user based at least in part on the generated first profile. The method further includes identifying segments of textual data of forwarded media the user receives based at least in part on the preferences of the user, wherein the textual data corresponds to a comment associated with the forwarded media.

Abstract: Methods, apparatus and computer program product for causing a rendering of a graphical icon associated with a message communication, wherein the message communication is received in a shared communication channel in a group-based communication platform. The graphical icon comprises a user avatar associated with a sender of the message communication and a group icon indicating association of the message communication with a group.

Abstract: A computerized method for training a computer executed model for recognizing numerical quantities is provided. An input, atleast one unit expression, is received by an input module. The input module may then search for numeric values and the unit expression in a text corpus, wherein, the text corpus comprises sets of words and frequency of occurrence of each of the sets. The input module may identify identified sets, wherein the identified sets may comprise a combination of a numeric value and the unit expression. A synthetic text generation module may then generate sentences from the text corpus by applying the identified sets as input. A training dataset may be generated by a labeling module by auto labelling features in the generated sentences based on the numeric value and the unit expression and further a training module may train the training model by providing input based on the training dataset.

Abstract: Machine learning, artificial intelligence, and other computer-implemented methods are used to identify various semantically important chunks in documents, automatically label them with appropriate datatypes and semantic roles, and use this enhanced information to assist authors and to support downstream processes. Chunk locations, datatypes, and semantic roles can often be automatically determined from what is here called “context”, to wit, the combination of their formatting, structure, and content; those of adjacent or nearby content; overall patterns of occurrence in a document, and similarities of all these things across documents (mainly but not exclusively among documents in the same document set).

Abstract: In predictive natural disaster response, a server determines an affected location predicted to be affected by a natural disaster and determines whether the type of natural disaster requires relocation of an animal population at the affected location. When relocation is required, using machine learning models, the server generates a rehabilitation needs prediction for the relocation, determines an optimal location for the relocation from candidate locations, and generates a relocation plan to relocate the animal population from the affected location to the optimal location. When relocation is not required, using the machine learning models, the server generates a demands prediction for products and services at the affected location, generates a supply prediction for the products and the services at the affect location, and generates a supply plan using the demands and supply predictions.

Abstract: Multiple stage filtering may be implemented for natural language query processing pipelines. Natural language queries may be received at a natural language query processing system and processed through a query language processing pipeline. The query language processing pipeline may filter candidate linkages for a natural language query before performing further filtering of the candidate linkages in the natural language query processing pipeline as part of generating an intermediate representation used to execute the natural language query.

Abstract: A search system performs a federated search across multiple databases and generates a ranked combined list of found genealogical records. The system receives a user query with one or more specified characteristics. The system may determine expanded characteristics derived from the specified characteristics. The system searches the various databases with the characteristics retrieving records according to the characteristics. The system combines the retrieved records and ranks them using a machine learning model. The machine learning model is configured to assign a weight to the records returned from each of the genealogical databases based on the characteristics specified in the user query. The machine learning model may be trained by any combination of one or more of: a Nelder-Mead method, a coordinate ascent method, and a simulated annealing method. The ranked combined results are provided in response to the user query.

Abstract: This disclosure relates generally to data integration, and more specifically to artificial intelligence based data integration of entities post market consolidation. The method includes extracting, using one or more text mining models, metadata associated with at least one category of each of the participating entities of the deal, from data sources associated with the entities. The disclosed system dynamically configures an assessment for the at least one category based on the metadata by using a set of Natural Language Processing (NLP) rules. The assessment includes parameters associated with the data integration of the entities. Response to the assessment is obtained from users belonging to the entities. An artificial intelligence (AI) based processing model assigns a similarity score to the responses, where the similarity score is indicative of extent of match between distinct responses obtained from the entities. A recommendation engine recommends a data integration model based on the similarity score.

Abstract: In general, the systems, components, methods, and techniques provide identifying and ordering results of a search query of a database of records, the records including a location. A user-submitted query including one or more search criteria is accessed. The search criteria are applied to search the records of database to identify a plurality of results for the query; each result corresponding to a record of the database satisfying the criteria. A first physical location associated with the user-submitted query and a second physical location indicated by the location data field or attribute of an original record are determined. An order for results is determined based on the location data.

Abstract: An illustrative embodiment includes a method for post-retrieval query performance prediction using hybrid document-passage information. The method includes: obtaining a set of documents responsive to a specific query; extracting document-level information regarding respective documents within the set; extracting passage-level information regarding respective passages of documents within the set; and estimating a likelihood that the set of documents includes relevant information to the specific query using both the document-level information and the passage-level information.

Abstract: Query execution status may be tracked to selectively route queries to resources for execution. The completion of queries executing at computing resources obtained from a pool of computing resources configured to execute queries may be detected. Instead of returning the computing resources to the pool, the computing resources may be identified as available in resource management data. When another query is received, the resource management data may be evaluated to select an available computing resource. The query may then be routed to the selected computing resource for execution.

Abstract: Systems for performing methods for searching documents are disclosed. The system may receive a first document comprising textual content, summarize the textual content using a first neural network, and translate the summarized textual content into translated content (e.g., content translated into Lojban) using a second neural network. The system may also conduct a fuzzy search of a database using the translated content for similar translated content from a plurality of documents and output results of the fuzzy search.

Abstract: A method includes receiving a natural language query requesting data from a message oriented middleware infrastructure comprising a plurality of message oriented middleware providers, and analyzing the natural language query to determine one or more types of the data being requested. In the method, one or more queries corresponding to the determined one or more types of the data are dynamically generated. The one or more queries are in native command formats corresponding to respective ones of the plurality of message oriented middleware providers. The method also includes executing the one or more queries in the native command formats to retrieve the data from the plurality of message oriented middleware providers, and providing a response to the natural language query based on the retrieved data to a user via a user interface.

Abstract: A method includes causing display to a user of at least one event of a first result set from a first pipelined search on events at an event source. Each event comprises a time stamp and a portion of machine data. A selection of a command is received from the user. The selection is to extend the first pipelined search with the selected command in a second pipelined search. The system selects between the first result set and the event source for execution of the second pipelined search based on an analysis of the selected command and at least one command of the first pipelined search. Based on the selecting being of the first result set, display to the user is caused of at least one event of a second result set from the execution of the second pipelined search on the first result set.

Abstract: A method, system and computer program product for copying data from a source database to a target database. A first database engine of the source database assigns a data-change-ID to each changed row in the source table. The data rows of the source table are stored in a plurality of source pages. Each source page comprises a source-page-ID and a highest-data-change-ID indicating its most recently changed data row. The target table comprises a source-page-ID-column. A second database engine of the target database maintains a metadata table comprising a source-page-ID column and a highest-data-change-ID column. The highest-data-change-IDs in the metadata table are compared with the highest-data-change-IDs of the source pages for selectively copying source table rows of source pages whose highest-data-change-ID is higher than their highest-data-change-ID in the metadata table to the target table.

Abstract: An information processing system includes a storage section that stores environment information related to plural customers, a verifying section that verifies a change occurring in the environment information, an extracting section that extracts attendant information which is information attendant on the change, and a search condition generating section that generates a search condition for narrowing down, from the environment information, a target for which a condition matches the attendant information.

Abstract: An efficient fact checking system analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The efficient fact checking system automatically monitors information, processes the information, fact checks the information efficiently and/or provides a status of the information.

Abstract: Various approaches discussed herein enable browsing groups of visually similar items to an item of interest, wherein the item of interest may be identified in a query image, for example. One or more visual attributes associated with the item of interest are identified, and the visually similar items matching at least one of the visual attributes are grouped together, wherein the group is ranked according to the visually similar items' overall visual similarity to the item of interest, for example by using a visual similarity score and/or metric.

Abstract: A computer-implemented method, computerized apparatus and computer program product for minimum coordination passage scoring. Given a candidate passage in a document collection potentially matching a query received, a set of overlapping terms between the candidate passage and the query is determined. For each overlapping term in the set, a first measure of a weight of the term in the query, a second measure of a weight of the term in the candidate passage, and a third measure of a specificity of the term in the document collection are calculated. a function of the first and second measure is evaluated to obtain a value reflecting a condition on the relation therebetween. A minimum coordination score representing a relative similarity between the candidate passage and the query is determined based on the value and the first, second and third measures obtained for each of the overlapping terms.

Abstract: Data recovery in a database includes performing a backward scan of a transaction log that records transactions made on the database. The backward scan includes traversing log records starting from a latest-in-time log record toward the beginning of the transaction log. Each log record can be replayed to recover data for a database row associated with the log record. An earlier-in-time log record is skipped if the associate database row has been recovered by later-in-time log record.