17944833. COMPUTING DEVICES CONFIGURED FOR LOCATION-AWARE CALLER IDENTIFICATION AND METHODS/SYSTEMS OF USE THEREOF simplified abstract (Capital One Services, LLC)

COMPUTING DEVICES CONFIGURED FOR LOCATION-AWARE CALLER IDENTIFICATION AND METHODS/SYSTEMS OF USE THEREOF

Organization Name

Capital One Services, LLC

Inventor(s)

Asher Smith-rose of Midlothian VA (US)

Lin Ni Lisa Cheng of Great Neck NY (US)

Joshua Edwards of Philadelphia PA (US)

Tyler Maiman of Melville NY (US)

Shabnam Kousha of Washington DC (US)

COMPUTING DEVICES CONFIGURED FOR LOCATION-AWARE CALLER IDENTIFICATION AND METHODS/SYSTEMS OF USE THEREOF - A simplified explanation of the abstract

This abstract first appeared for US patent application 17944833 titled 'COMPUTING DEVICES CONFIGURED FOR LOCATION-AWARE CALLER IDENTIFICATION AND METHODS/SYSTEMS OF USE THEREOF

Simplified Explanation

The abstract describes a patent application for location-aware caller identification using machine learning techniques. The method involves associating a user's location with their phone number based on transactional information and annotating phone number records with location information.

• Machine learning techniques used for location-aware caller identification
• Associating user location with phone numbers based on transactional information
• Annotating phone number records with location information
• Automated process for annotating phone number records with user-specific location information

Potential Applications

The technology could be applied in various industries such as telecommunications, customer service, and security to enhance caller identification processes.

Problems Solved

This technology solves the problem of accurately identifying the location of a caller based on transactional information and associating it with their phone number.

Benefits

The benefits of this technology include improved caller identification accuracy, enhanced user experience, and increased security measures for verifying caller locations.

Potential Commercial Applications

Potential commercial applications of this technology include call centers, emergency services, and mobile applications that require location-specific caller identification.

Possible Prior Art

One possible prior art for this technology could be existing caller identification systems that use location data but may not utilize machine learning techniques for automated annotation of phone number records.

Unanswered Questions

1. How does this technology handle privacy concerns related to tracking user locations? 2. What are the limitations of using machine learning for caller identification in terms of accuracy and reliability?

Original Abstract Submitted

Systems and methods of location-aware caller identification via machine learning techniques are disclosed. In one embodiment, an exemplary computer-implemented method may include: utilizing a trained call annotation machine learning model to determine one or both of an annotating condition and annotating location granularity, and associate one location of a user with one phone number of the user based at least on one or both of the annotating condition and the annotating location granularity; receiving second transactional information of one transaction associated with a first user; extracting second location information from the second transactional information of the one transaction; utilizing the trained call annotation machine learning model to automatically annotate one phone number record of one phone number of the first user, with the second location information at the annotating location granularity to form at least one user-specific location-specific annotated phone number record.