Abstract: A system and method for the matching of database records based on the similarity between fields in the database records and fields in the search queries is provided. A set of database records may be received from a search engine for further refinement of the search results. The database records may be assigned matching strength points, based on comparisons of fields in the search query and fields in the database records. The records that do not meet predetermined qualifying criteria, based on the matching strength points, may be rejected. The remaining records may be merged together, based on the similarity between fields of the remaining records.

Abstract: Various methods, apparatuses/systems, and media for generating a data structure are provided. A database stores a historic version of taxonomy data and a new version of taxonomy data. A processor, operatively connected to the database, accesses the database and analyzes the historic version of taxonomy data and the new version of taxonomy data. The processor determines what changes have been made in connection with a particular reference data based on analyzing the historic version of taxonomy data and the new version of taxonomy data; creates, based on determining, an association between the historic version of taxonomy data and the new version of taxonomy data corresponding to said particular reference data; generates consistent metadata from said association; and generates a data structure that illustrates history of evolution of taxonomy in connection with said particular reference data based on the metadata.

Abstract: Techniques are provided for key-value store and file system integration to optimize key value store operations. A key-value store is integrated within a file system of a node. A log structured merge tree of the key-value store may be populated with a key corresponding to a content hash of a value data item stored separate from the key. A random distribution search may be performed upon a sorted log of the log structured merge tree to identify the key for accessing the value data item. A starting location for the random distribution search is derived from key information, a log size of the sorted log, and/or a keyspace size of a keyspace associated with the key.

Abstract: The present invention relates to hash join acceleration. In an embodiment, a computer receives a request to join build data rows with probe data rows. Each data row is associated with a respective join key value. From multiple buckets of a hash table, a bucket is selected that contains entries of multiple respective join key values in respective locations within the bucket. Whether or not the bucket contains an entry of the join key value of a build data row is detected. While building, multiple locations within the bucket are concurrently inspected to find an empty location in which to store the entry of the join key value of the build data row. The bucket is concurrently probed to detect whether or not the entries in the bucket include an entry of a join key value of a probe data row. For the join request, a response is sent that is based on the concurrent probing of the bucket.

Abstract: A metadata-driven file system prioritizes the distribution of files across different storage devices based on arbitrary file metadata matching to different file usage scenarios defined within one or more workflows or taxonomies. The file metadata may be tagged with different key-value pairs from the defined workflows or taxonomies. Upon receiving a file or file access request, the metadata-driven file system matches the file metadata to a key-value pair combination of the taxonomy, and stores the file to a storage device that is selected using a storage rule that is defined for the matching key-value pair combination. The taxonomy may be defined with other programmatic file operations that the metadata-driven file system may perform against files with matching metadata.

Abstract: Techniques described herein are directed to determining an effective tag for data assets. For instance, each tag associated with a data asset may be associated with certain attributes. Non-limiting examples for such attributes may include a confidence level associated with a source that applied the tag, an applied date at which the tag was applied to the data asset, and/or a hierarchical depth of the data asset to which the tag was applied, as well as additional and/or alternative types of attributes. When a request to determine a tag for a data asset is received, the attributes for all the tags applied to the data asset may be retrieved and/or analyzed to determine which of such tags effectively classifies the data asset. The determined effective tag may be returned to the requesting entity.

Abstract: An enterprise resource data store may contain electronic records, each electronic record representing an enterprise resource entry, and including, for each entry, an electronic record identifier and a set of enterprise values. A series query data store may contain electronic records, each electronic record representing a series query, and including, for each series query, an electronic record identifier and a set of pre-defined single query parameters. A back-end application computer server may receive, from a remote user device, a selected series query. The server may then retrieve, from the series query data store, information about a selected set of pre-defined single query parameters including comparison period data. In addition, the server may retrieve, from the enterprise resource data store, information about enterprise resource entries associated with the selected set and comparison period data. The server may then arrange to output an indication of step analysis results and analysis notes.

Abstract: A method for document similarity analysis. The method includes generating a reference document content identifier for a reference document, including identifying frequently occurring terms in reference document content, encoding each frequently occurring term in a term identifier and combining the term identifiers to form the reference document content identifier associated with the reference document. The method also includes obtaining at least one document similarity value by comparing the reference document content identifier to a set of archived document content identifiers stored in a document repository.

Abstract: A behavior detection module receives a training database and applies a transformation to the attributes that improves the uniformity of the values associated with each attribute. The transformed training database is used to construct a random forest classifier (RFC). The RFC includes a plurality of decision trees and generates a classification label estimate for a data entry with a plurality of attributes. The classification label estimate is determined based on classification estimates from the plurality of decision trees. Each parent node of a decision tree is associated with a condition of a transformed attribute that directs the data entry to a corresponding child node depending on whether the condition is satisfied or not. The data entry is directed through the tree to one out of a set of leaf nodes, and a classification label associated with the leaf node.

Abstract: A method for providing contextual analytics of target information by using similarity mapping is disclosed. The method includes retrieving, via a communication interface, raw data from several sources based on a predetermined characteristic of the raw data, the raw data including natural language data; receiving, via a graphical user interface, a target document; converting, by using a natural language processing technique, the raw data into structured data based on a predetermined parameter; refining the target document to generate a target data set; generating a structured data set from the structured data by using a dimensionality reduction technique; and displaying, via the graphical user interface, a graphical element, the graphical element including a similarity plot of the structured data set and the target data set.

Abstract: The systems and methods described herein analyze one or more selected data sources in their entirety and determine data relationships, using a single-branch approach. Indexes are created based on the determined data relationships, and data from the one or more data sets is imported into the indexes and stored in a back-end storage system. Once the data is analyzed and stored in the indexes, a user can submit a request for a data visualization. In response to the request, the system automatically generates (e.g., builds) and displays the requested data visualization to the user. In some examples, the user may request a modification of the data visualization such as changing the timeframe shown in the data visualization or adding/removing data associated with a particular parameter, and the system will automatically generate the modified data visualization for the user.

Abstract: The present invention discloses a method, a system and a computer program product for data processing and classification. The invention provides warm start and cold start classification tools for classification of data obtained from known or unknown entities. The system and method are also configured to be employed over blockchain based networks.

Abstract: According to some embodiments, a selection server is in communication with a potential communication device database and a currently participating device database, the potential communication device database storing information about communication devices associated with a transition from a first state to a second state, including at least one communication address associated with each communication device. The selection server may automatically identify a communication device as meeting a pre-determined criteria and copy information about the identified communication device from the potential communication device database to the currently participating device database.

Abstract: Approaches are described for shape-based graphics search. Each graphics object of a set of graphics objects is analyzed. The analyzing includes determining an outline of the graphics object from graphics data that forms the graphics object. The outline of the graphics object is sampled resulting in sampled points that capture the outline of the graphics object. A shape descriptor of the graphics object is determined which captures local and global geometric properties of the sampled points. Search results of a search query are determined based on a comparison between a shape descriptor of a user identified graphics object and the shape descriptor of at least one graphics object of the set of graphics objects. At least one of the search results can be presented on a user device associated with the search query.

Abstract: An embodiment of the present invention is provided with a projective transform model including a plurality of nodes and a projection table, the plurality of nodes each holding a reference vector having a dimension corresponding to the dimension of multi-dimensional data. The projection table indicates the correspondence relation between the number of each node and a coordinate in a two-dimensional space as a projection target of the reference vector held by the node. First in a learning phase, multi-dimensional input data of a positive example and a negative example is acquired, the amplitude characteristic amounts thereof are calculated, and this amplitude characteristic amount data is learned as the reference vectors of the nodes for each sample.

Abstract: Systems, methods, and computer-readable media for generating and presenting workflow graphs can include the following operations. A workflow graph including vertices is provided. An event is received to reorganize the vertices of the workflow graph. Each of the vertices is classified with a significance level, the significance level is based on at least one of a business rule and a vertex position of a vertex of the vertices. Vertices of the vertices having a low significance level are grouped together. The vertices in the group having the low significance level are combined into a new vertex, and the new vertex is expandable and collapsible to view the vertices in the group having the low significance level.

Abstract: Replication of search-related configuration customizations across multiple individual configuration files of search heads of a cluster for a consistent user experience. A search head leader of the cluster can receive a first journal entry relating to a first customization of a knowledge object from a first search head of the cluster. The search head leader may determine that the first journal entry references a parent commit journal entry matching a latest commit journal entry in a journal maintained by the search head leader. The first journal entry can be stored in the journal and sent to one or more search heads of the cluster.

Abstract: Systems and methods automatically generate a low input visualization of data updated in a workbook. One aspect describes a computer-implemented method comprising obtaining a request to update data in an application workbook for an application. The request comprises an indication of a type of update being requested and at least a subset of the data being updated. The method further comprises performing the update of the data in the application workbook and determining that the performed update of the data in the application workbook results in a change to a visualization of the data. The method also comprises generating an updated visualization based on the received request and the updated application workbook and generating a confirmation message that the updated visualization has been generated, wherein the updated visualization is generated automatically based on the update of the data.

Abstract: A document information extraction system determines a structure of an electronic document based on characteristics of the document's constituent elements. The system segments the document to generate elements with each element having similar characteristics. Elements may be clustered to assist in determining the document structure. The system determines directional relationships between elements (e.g., above, below, etc.). The system then employs a master comparator to determine familial relationships between adjacent elements. The master comparator includes a set of unit comparators and each unit comparator compares a specific characteristic between two elements. The master comparator sequentially applies the unit comparators to determine the familial relationship based on the comparisons. The system outputs a document hierarchy tree reflecting the determined familial relationships. The hierarchy tree represents the structure of the document.

Abstract: Embodiments of this application provide an information query method for a terminal and a terminal, to reduce unnecessary bandwidth traffic of a user and reduce a processing load of a service system when querying service information on a terminal app. The method in the embodiments of this application includes: receiving a first request, where the first request is used to indicate to query target service information of a first application app on the terminal; and determining, according to a query policy preset on the terminal, to process the first request on the terminal or request a service system associated with the terminal to process the first request.