17545880. PERFORMING AUTOMATED SEMANTIC FEATURE DISCOVERY simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

PERFORMING AUTOMATED SEMANTIC FEATURE DISCOVERY

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

Daniel Karl I. Weidele of Cambridge MA (US)

Lisa Amini of Weston MA (US)

Udayan Khurana of White Plains NY (US)

Kavitha Srinivas of Port Chester NY (US)

Horst Cornelius Samulowitz of Armonk NY (US)

Takaaki Tateishi of Yamato-shi (JP)

Carolina Maria Spina of Buenos Aires (AR)

Dakuo Wang of Cambridge MA (US)

Abel Valente of Buenos Aires (AR)

Arunima Chaudhary of Dehradun (IN)

Toshihiro Takahashi of Nakano-ku (JP)

PERFORMING AUTOMATED SEMANTIC FEATURE DISCOVERY - A simplified explanation of the abstract

This abstract first appeared for US patent application 17545880 titled 'PERFORMING AUTOMATED SEMANTIC FEATURE DISCOVERY

Simplified Explanation

The abstract of the patent application describes a computer-implemented method that involves identifying a data set and its associated meta information. The method then augments the data set by adding additional features based on an automatic analysis of the data set in relation to the meta information.

• The method is implemented using a computer system.
• It involves analyzing a data set and its meta information.
• Additional features are added to the data set based on the analysis.
• The analysis is performed automatically by the computer system.

Potential Applications

• Data analysis and augmentation in various industries such as finance, healthcare, and marketing.
• Improving the accuracy and effectiveness of machine learning models by incorporating additional features.
• Enhancing data sets for research purposes in fields like social sciences and environmental studies.

Problems Solved

• Manual analysis and augmentation of data sets can be time-consuming and prone to human error.
• Identifying relevant features to enhance a data set can be challenging without automated analysis.
• The method solves the problem of efficiently and accurately augmenting data sets with additional features.

Benefits

• Saves time and effort by automating the analysis and augmentation process.
• Improves the quality and richness of data sets by incorporating additional features.
• Enables more accurate and comprehensive analysis of data sets, leading to better insights and decision-making.

Original Abstract Submitted

A computer-implemented method according to one embodiment includes identifying a data set and meta information; and augmenting the data set with additional features in response to an automatic analysis of the data set in view of the meta information.