Automated Caller ID Generation via Data Analysis
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Solution Overview
Problem
Existing caller identification systems require manual input of enhanced caller information, which is cumbersome and often results in missed opportunities for customized content presentation.
Innovation Solution
A system that automatically generates enhanced caller identification information by analyzing various data sources, including websites, previous call data, and user interactions, to provide logos, likely subjects, and other relevant information without manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual input of enhanced caller information is required, then customized content can be presented, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The system automatically generates enhanced caller identification information by analyzing call data, website information, and social media data without requiring manual input from the called party. The system serves itself by autonomously collecting and processing data to create customized caller profiles, eliminating the need for users to manually enter information while still providing personalized content.
Solution Approach 2:
The system collects and analyzes data about calling parties in advance of actual calls, building profiles and gathering information from websites, social media, and call history beforehand. This preliminary data collection enables the system to automatically generate enhanced caller identification information when needed, without requiring last-minute manual input.
2Extent of automation
If automated data collection from multiple sources is implemented, then customized caller information is generated automatically, but system complexity increases
Solution Approach 1:
The system employs a multi-functional architecture where a single server platform performs diverse functions: collecting call data, analyzing website information, gathering social media data, processing images and videos, and generating enhanced caller identification. This universal system handles multiple data types and sources through integrated tools and applications, managing complexity through consolidation rather than separate specialized systems.
Solution Approach 2:
The system uses intermediary components such as web crawlers, social media API interfaces, and data processing intermediaries to bridge between various data sources and the core analysis engine. These intermediaries standardize data collection from diverse sources (websites, social media platforms, call records) into a unified format that the system can process, reducing the complexity of direct integration with multiple external systems.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatically generating enhanced caller identification data are disclosed. In one aspect, a method includes the actions of receiving telephone call placement data that indicates the placement of a telephone call from a calling party to a called party. The actions further include receiving caller identification data. The actions further include accessing first telephone call data that reflects characteristics of telephone calls placed and received by the calling party. The actions further include based on the first telephone call data and the identity of the calling party, determining additional data to combine with the caller identification data. The actions further include generating enhanced caller identification data by combining the additional data with the caller identification data. The actions further include providing, for output, the enhanced caller identification data and data indicating the telephone call.