Caller Identification System Using Relationship Context
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Solution Overview
Problem
Users often struggle to identify unknown callers, leading to potential missed important calls or uncertain responses due to lack of context, as traditional caller ID methods like phone numbers do not provide sufficient information.
Innovation Solution
An apparatus and method that detect incoming calls from unknown contacts by collecting relationship information through polling close contacts and shared databases, transcribing call portions, and providing notifications based on determined relational contexts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional caller ID methods are used to display phone numbers, then the identification process is simple, but the information provided is insufficient for users to recognize unknown callers
Solution Approach 1:
The patent combines multiple information sources including call history data, contact list information, voicemail transcripts, and social network data to create a comprehensive caller profile. This merging of diverse data sources resolves the contradiction by providing rich caller information while using a unified identification system that manages complexity through integration.
Solution Approach 2:
The identification system performs multiple functions: it analyzes call patterns, searches contact lists, processes voicemail transcripts, queries social network APIs, and generates contextual information. This multi-functionality allows a single system to provide comprehensive caller identification without requiring separate specialized systems for each data source.
2Measurement precision
If the system collects relationship information by polling close contacts and searching databases, then the accuracy of caller identification improves, but the time and computational resources required increase
Solution Approach 1:
The system pre-processed call history data, contact information, and voicemail transcripts before they are needed for identification. By having this data prepared and indexed in advance, the system can quickly retrieve relevant information during an actual identification event, improving accuracy without incurring excessive processing delays when identification is actually needed.
Solution Approach 2:
The system implements a tiered identification approach where it first performs quick checks against readily available data (call history, contact lists), then progressively searches more resource-intensive sources (social networks, detailed relationship graphs) only when necessary. This partial action strategy achieves sufficient accuracy for many cases while avoiding unnecessary time consumption for simpler identifications.
3Adaptability or versatility
If the system transcribes phone calls to identify relational cues, then the relationship detection capability improves, but the energy consumption and processing complexity increase
Solution Approach 1:
The system transcribes only portions of phone calls rather than complete transcripts, focusing on segments most likely to contain relational cues such as introductions and key discussion points. This partial transcription approach maintains relationship detection capability while significantly reducing the energy and computational resources required compared to transcribing entire calls.
Solution Approach 2:
The system extracts and analyzes only the specific relational cues from transcribed call portions rather than processing entire transcripts. By isolating and focusing on key relationship-indicating phrases and patterns, the system achieves effective relationship detection with minimal processing energy expenditure.
Data Source
AI summary
For identifying an unknown contact, a system, apparatus, method, and computer program product are disclosed. The apparatus, in one embodiment, includes a processor, a memory that stores code executable by the processor, the code identifying an incoming call from an unknown contact, collecting relationship information regarding the unknown contact, and determining a relationship to a user based on the collected relationship information. In certain embodiments, the apparatus also includes code that provides a notification based on the determined relationship. In some embodiments, the apparatus also includes code that shares the determined relationship with one or more stored contacts.