Abstract: Systems and methods for implementing extensible attributes in ETL are disclosed. In some examples, attributes configured at a source file may be extracted from the source file. The extracted attributes can be mapped to a target column of a data warehouse table, and then a dynamic ETL script may be generated. The dynamic script may be executed to move data associated with the attributes to an appropriate new column of the data warehouse.

Abstract: An information processing device according to the present application includes a generation unit and a providing unit. The generation unit uses a model that is trained to learn a relationship between a criterion for classifying users of a first company and a criterion for classifying users of a second company to generate a criterion (common key) for classifying the users of the second company into a first category, from the criterion for classifying the users of the first company into the first category. The providing unit provides a criterion generated by the generation unit.

Abstract: Systems and methods are described for generating record clusters. The methods comprise receiving a plurality of records from data sources and providing at least a subset of the records to a scoring model that determines scores for various pairings of the records, a score for a given pair of the records representing a probability that the given pair of records contain data elements about the same entity. The method further comprises generating a graph data structure that includes a plurality of nodes, individual nodes representing a different record from the records. The method also comprises assigning a different unique identifier to individual clusters of the final clusters and responding to a request for data regarding a given entity by providing aggregated data elements from those records of the records associated with a cluster of the final clusters having an identifier that represents the given entity.

Abstract: Systems and methods are disclosed to implement an indexing engine that maintains an index in an index store for a storage object in a data store. In embodiments, the index store may be implemented using an in-memory storage cluster separate from the data store. The storage object may have multiple indexes, which may have different filtering or sorting criteria for the data. In embodiments, updates to the storage object are received as an update stream by the indexing engine. Based on configurable indexing rules, the indexing engine applies the updates to the appropriate indexes. To service a query to the data store, a query engine first retrieves a set of keys satisfying the query from the index store, and then data corresponding to the keys from the data store or another index. In embodiments, the index may be refreshed via touch updates of selected data in the storage object.

Abstract: A system may iteratively scan a portion of a document, extract first data from the portion of the document, and determine, using a trained model, whether the first data corresponds to one or more document types based on one or more confidence thresholds. The system may repeat this process, increasing the portion of the document scanned by a predetermined amount each iteration, until the first data corresponds to the one or more document types based on the one or more confidence thresholds. Responsive to determining the first data corresponds to the one or more document types based on the one or more confidence thresholds, the system may cause a graphical user interface (GUI) of a user device to display a notification indicating a document type match.

Abstract: A method may include determining that input text data includes a first keyword from a first set of keywords. The method also includes determining a similarity between the input text data and a first stored text string that has previously been identified as a false positive match for the first keyword, and based on the similarity, generating a first false positive score corresponding to the input text data. Further, the method includes determining a number of keywords, from a second set of keywords, that are included in the input text data, and based on the number of keywords, generating a second false positive score corresponding to the input text data. The method also includes calculating a final false positive score corresponding to the input text data based on the first false positive score and the second false positive score.

Abstract: A method for identifying subpopulations may include receiving interaction data associated with interactions from a population of individuals. The interaction data may include a plurality of features. A first subpopulation may be identified based on at least one feature of interaction data of each individual. A second subpopulation may include all individuals other than the first subpopulation. The first subpopulation may be clustered into a first plurality of clusters based on the features. A first subset of features may be determined based on the first clusters. The first subpopulation may be clustered into a second plurality of clusters based on the first subset of features. A range for each feature of a second subset of features may be determined based on the second clusters. A subset of the second subpopulation may be determined based on interaction data for each individual and the range for each feature of the second subset of features.

Abstract: A computer-implemented method may include: providing an extension for a web browser, the extension having a user interface configured to occupy a portion of a user interface associated with the web browser; intercepting content fetched by the web browser for a web page being a company page, a social media page, or a professional page; processing the fetched content for the web page to extract information including: a company name, a candidate name, a job title, and/or an industry name; querying a database for contextual information based on the extracted information, the contextual information being a summary of information obtained from one or more sources other than the web page; and presenting, via the user interface, the contextual information including: company information based on the company name, candidate information based on the candidate name, job title information based on the job title, and/or industry information based on the industry name.

Abstract: Embodiments are directed to managing data for unified graph representation of skills and acumen. Information associated with one or more subjects may be classified to provide profile information that conforms to a unified schema. Fields of the profile information may be classified as facts, fact-relationships, actions, skills, or skill-relationships based on the unified schema. A plurality of profile graphs may be generated based on map models and the facts, the fact-relationships, the actions, the skills, or the skill-relationships such that the map models include one or more directives for associating the facts, the fact-relationships, the actions, the skills, or the skill-relationships with one or more nodes or one or more edges in the plurality of profile graphs. In response to query information provided by one or more analysis applications, classifying a portion of the plurality of profile graphs based on the query information.

Abstract: An approach is provided in which the approach calculates at least one weighting factor based on a word frequency analysis of an unlabeled document against a set of word frequencies corresponding to a set of labeled documents. The approach computes an a posteriori classification probability of the unlabeled document based on the at least one weighting factor, and creates an inferred classifier based on the a posteriori classification probability. The approach classifies the unlabeled classifier using the inferred classifier.

Abstract: A data analytics application receives a workflow that includes a sequence of tools. Each tool performs a data analytics function. The data analytics application processes a data file using the sequence of tools to generate a result item representing an outcome of the processing of the data file. The data analytics application stores one or more metadata files, each of which includes data generated by an interactive tool in the sequence during the processing of the data file. The data analytics application receives a user input through an interactive element associated with an interactive tool in the sequence. The interactive element can modify an operation of the interactive tool based on the user input. The data analytics application retrieves the metadata file for the interactive tool and processes the metadata file by using a subset of the sequence of tools and the user input to generate a different result item.

Abstract: Technology is described herein for searching an index, including operations of: obtaining a source data item; generating a source context-supplemented vector based on the source data item; and searching the index to find one or more target context-supplemented vectors that are determined to match the source context-supplemented vector. Each context-supplemented vector, which is associated with a particular data item, is made up of two parts: a language-agnostic vector and a context vector. The language-agnostic vector expresses the meaning of the particular data item in a manner that is independent of a natural language that is used to express the particular data item, while the context vector expresses a context associated with the formation of the particular data item. More generally, the technology's use of context vectors allows it to perform index search operations in a more efficient manner, compared to a search engine that does not use context vectors.

Abstract: A method includes, through a server, determining a context of interaction between a user of a data processing device communicatively coupled to the server through a computer network and the server, fetching a set of queries from a database associated with the server in accordance with determining the context of interaction, and loading the set of queries one by one on a first media device configured to render the set of queries in an audio, a video and/or a gesture format. The method also includes, through the server, receiving a response to a query of the set of queries from the user via the first media device and/or the data processing device, and refining the set of queries based on the response received to the query from the user in accordance with an Artificial Intelligence (AI) and/or a Machine Learning (ML) engine executing on the server.

Abstract: Methods, systems, and computer-readable media are disclosed herein to provide rule-based reconciliation of records. Specifically, rules are utilized to reconcile one or more records and identify duplicates therein. Once duplicate records are identified, one or more ranking sets can be utilized to identify which of the duplicate records to write to the system.

Abstract: A method for ranking relevance of documents includes using a set of queries, searching a corpus of documents for a set of candidate documents with information relevant to the set of queries. The method further includes ranking the set of candidate documents by a deep learning processing system according to relevance to respective ones of the set of queries. The method additionally includes responsive to user input, revising the ranked set of candidate documents to produce a revised ranked set of candidate documents. The method further includes using the revised ranked set of candidate documents to retrain the deep learning processing system. The method still further includes performing a categorization of the set of candidate documents by the retrained deep learning processing system.

Abstract: Certain aspects of the present disclosure relate to methods and systems for evaluating a first command line interface (CLI) input of a process. The method comprises examining the first CLI input and selecting a first clustering model corresponding to the process, wherein the first clustering model is created based on a first clustering configuration and a first feature type combination. The method further comprises creating a first feature combination for the first CLI input based on the first feature type combination, evaluating the first CLI input using the first clustering model and the first feature combination, wherein the evaluating further comprises determining a similarity score corresponding to a similarity between the first feature combination and the one or more clusters, and determining whether or not the first CLI input corresponds to normal behavior based on the similarity score.

Abstract: A method/system for managing experimental data, a computer readable storage medium, and a device are provided. The method includes: recording the managing experimental data, and preprocessing the experimental data, to obtain at least two preprocessed experimental arrays; selecting one element from each of two selected preprocessed experimental arrays according to an analysis requirement, and combining the elements to form a cyclic experimental database, the cyclic experimental database including several combination data; performing cyclic statistical analysis on the combination data in the cyclic experimental database, to obtain a cyclic statistical result corresponding to retrieved combination data.

Abstract: A method includes determining that a parser fails to parse an invalid structured query language (SQL) statement. In response to determining that the parser fails to parse the invalid SQL statement, the method generates, by an error parser, an output corresponding to the invalid SQL statement. The output includes a plurality of data structures arranged in a tree structure. Each of the plurality of data structures corresponds to a portion of the invalid SQL statement.

Abstract: A deduplication index is generated having multiple entries, each entry storing a digest of a data block that was previously stored in non-volatile data storage together with a pointer to the location in non-volatile storage at which the data block was previously stored. The entries of the disclosed deduplication index are divided into multiple deduplication index segments. A resident subset of the deduplication index segments is stored in memory of the data storage system. A non-resident subset of the deduplication index segments is stored in non-volatile data storage of the data storage system. Data deduplication is performed for each subsequently received data block for which a digest is generated that matches any one of the digests in the entries of the deduplication index segments that are contained in the resident subset of the deduplication index segments.

Abstract: Systems and methods are provided herein for flexibly using trending topics as parameters for recommending media assets that are related to a viewed media asset. A media guidance application may determine that a user has viewed a media asset. The media guidance may identify a plurality of attributes corresponding to the viewed media asset and determine that a respective attribute of the plurality of attributes matches a trending topic. The media guidance application may update a set of weightings corresponding to the plurality of attributes by increasing a weighting corresponding to the respective attribute and adjust a recommendation for a media asset different from the viewed media asset based on the updated set of weightings. The media guidance application may generate for display the recommendation of the media asset different from the viewed media asset.