Patent classifications
G06F16/81
METADATA DRIVEN DATASET MANAGEMENT
A method for configuring the operation of the software of a data as a service (DAAS) system during run time is described. The configuring includes at least one of configuring ingestion of a vendor dataset to produce an ingested dataset and which analysis operations to perform on the vendor dataset to produce an analyzed dataset, and the configuring also includes at least one of how to search the vendor dataset based on a search query from a customer to allow the customer to locate a new record from the vendor dataset and how to match records in the vendor dataset with a match query from the customer to provide an updated record to the customer.
Probabilistic text index for semi-structured data in columnar analytics storage formats
Herein is a probabilistic indexing technique for searching semi-structured text documents in columnar storage formats such as Parquet, using columnar input/output (I/O) avoidance, and needing minimal storage overhead. In an embodiment, a computer associates columns with text strings that occur in semi-structured documents. Text words that occur in the text strings are detected. Respectively for each text word, a bitmap, of a plurality of bitmaps, that contains a respective bit for each column is generated. Based on at least one of the bitmaps, some of the columns or some of the semi-structured documents are accessed.
Probabilistic text index for semi-structured data in columnar analytics storage formats
Herein is a probabilistic indexing technique for searching semi-structured text documents in columnar storage formats such as Parquet, using columnar input/output (I/O) avoidance, and needing minimal storage overhead. In an embodiment, a computer associates columns with text strings that occur in semi-structured documents. Text words that occur in the text strings are detected. Respectively for each text word, a bitmap, of a plurality of bitmaps, that contains a respective bit for each column is generated. Based on at least one of the bitmaps, some of the columns or some of the semi-structured documents are accessed.
SYSTEMS AND METHODS FOR SEARCHING IN IDENTITY MANAGEMENT ARTIFICIAL INTELLIGENCE SYSTEMS
Systems and methods for embodiments of artificial intelligence systems for identity management are disclosed. Embodiments of the identity management systems disclosed herein may support the creation, association, searching, or visualization of any relevant context to identity management assets for a variety of purposes, including the creation of nested identity management artifacts in a search index and search syntaxes for querying such nested artifacts.
SYSTEMS AND METHODS FOR SEARCHING IN IDENTITY MANAGEMENT ARTIFICIAL INTELLIGENCE SYSTEMS
Systems and methods for embodiments of artificial intelligence systems for identity management are disclosed. Embodiments of the identity management systems disclosed herein may support the creation, association, searching, or visualization of any relevant context to identity management assets for a variety of purposes, including the creation of nested identity management artifacts in a search index and search syntaxes for querying such nested artifacts.
Context-sensitive feature score generation
Document information may define words, key groups of words, and sets of context words within a document. Word feature scores for words within the document may be generated. Key group feature scores for individual key groups of words may be generated based on aggregation of word feature scores the words within the individual key groups of words and word feature scores for words within corresponding sets of context words. A document feature score for the document may be generated based on aggregation of word feature scores for words within the document. The key group feature scores and the document feature score may enable context-sensitive searching of words/word vectors in the document.
Context-sensitive feature score generation
Document information may define words, key groups of words, and sets of context words within a document. Word feature scores for words within the document may be generated. Key group feature scores for individual key groups of words may be generated based on aggregation of word feature scores the words within the individual key groups of words and word feature scores for words within corresponding sets of context words. A document feature score for the document may be generated based on aggregation of word feature scores for words within the document. The key group feature scores and the document feature score may enable context-sensitive searching of words/word vectors in the document.
Data driven relational algorithm formation for execution against big data
Techniques are described herein for creating an algorithm for batch mode processing against big data. The techniques involve receiving one or more user commands from a set number of commands that correspond one-to-one with a set number of low-level database operations. In a preferred embodiment, the set of database operations includes only FILTERS, SORTS, AGREGGATES, and JOINS. In the algorithm formation process, database operations are performed on a sample population of records. The user drills down to a set of useful records by performing database operations against the results of the previous database operations. While the database cluster is receiving operations, the system is tracking the operations in a dependency graph. The chains selected within the dependency graph indicate which operations are used to create the algorithm. To generate the algorithm, the database cluster reverse engineers the logic for performing those operations against big data.
Graphically representing content relationships on a surface of graphical object
A collection of data stored in a computer-readable storage medium is provided, and a plurality of portions of the collection are associated with corresponding identifiers that are associated with positions of an object to be rendered. User selections of positions on the surface of the object are received. The portions associated with the user selected position are determined, and the portions are displayed at their respective position on the surface of the object. The selected portions can be displayed as being connected by graphical elements.
Graphically representing content relationships on a surface of graphical object
A collection of data stored in a computer-readable storage medium is provided, and a plurality of portions of the collection are associated with corresponding identifiers that are associated with positions of an object to be rendered. User selections of positions on the surface of the object are received. The portions associated with the user selected position are determined, and the portions are displayed at their respective position on the surface of the object. The selected portions can be displayed as being connected by graphical elements.