US 2019/0171774 A1 · DATA FILTERING BASED ON HISTORICAL DATA ANALYSIS

Abstract

A method, system, and computer program product for data filtering based on historical data analysis. A first document is identified based on keywords extracted from input. The first document is converted into a multi-dimensional vector based on analyzing a set of features of the first document. The converted multi-dimensional vector is assigned to at least one machine learning cluster in which the at least one machine learning cluster is formed based on historical data derived from previously processed documents. A set of task items linked to the at least one machine learning cluster is retrieved. The set of task items to the first document is associated.

Claims20

Dependent claims

A method of data filtering based on historical data analysis, the method comprising:

identifying, by one or more processors, a first document based on keywords extracted from input;
converting, by one or more processors, the first document into a multi-dimensional vector based on analyzing a set of features of the first document;
assigning, by one or more processors, the multi-dimensional vector to at least one machine learning cluster, wherein the at least one machine learning cluster is formed based on historical data derived from previously processed documents;
retrieving, by one or more processors, a set of task items linked to the at least one machine learning cluster;
and
associating, by one or more processors, the set of task items to the first document.

3 more elements

A computer program product for data filtering based on historical data analysis, the computer program product comprising one or more computer readable storage medium and program instructions stored on at least one of the one or more computer readable storage medium, the program instructions comprising:

program instructions to identify a first document based on keywords extracted from input;
program instructions to convert the first document into a multi-dimensional vector based on analyzing a set of features of the first document;
program instructions to assign the multi-dimensional vector to at least one machine learning cluster, wherein the at least one machine learning cluster is formed based on historical data derived from previously processed documents;
program instructions to retrieve a set of task items linked to the at least one machine learning cluster;
and
program instructions to associate the set of task items to the first document.

3 more elements

A computer system for data filtering based on historical data analysis, the computer system comprising one or more processors, one or more computer readable memories, one or more computer readable storage medium, and program instructions stored on at least one of the one or more storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, the program instructions comprising:

program instructions to identify a first document based on keywords extracted from input;
program instructions to convert the first document into a multi-dimensional vector based on analyzing a set of features of the first document;
program instructions to assign the multi-dimensional vector to at least one machine learning cluster, wherein the at least one machine learning cluster is formed based on historical data derived from previously processed documents;
program instructions to retrieve a set of task items linked to the at least one machine learning cluster;
and
program instructions to associate the set of task items to the first document.

3 more elements

Dependencies are inferred from the claim text.

Data filtering based on historical data analysis

Life of this patent

Data filtering based on historical data analysis

Life of this patent

Abstract

Claims20