Action Prediction System for Interactive History Context
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Solution Overview
Problem
Conventional communication systems fail to provide business users with efficient access to interactive histories and context between senders and recipients, leading to low productivity when handling incoming calls, as users must manually search across multiple web pages and applications, lacking direct action links and stable topic information.
Innovation Solution
A system that determines previous transactions between senders and recipients using enterprise information systems, generating lists of action candidates based on interactive histories, allowing users to select actions directly, with caller-oriented and user-oriented search engines providing context and recommended actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually search for customer information across multiple web pages and applications, then they can access customer data, but user productivity is very low due to the time-consuming process
Solution Approach 1:
The system pre-processes and stores customer interaction history and transaction data in a structured format before it is needed. When a user receives a call, the system has already prepared the customer context information, eliminating the need for users to manually search across multiple systems. This preliminary preparation of data resolves the contradiction by making information immediately accessible without sacrificing the thoroughness of customer data collection.
Solution Approach 2:
The patent introduces an intermediary system (call handling system with integrated search engines) that mediates between the user and the scattered customer information across multiple web pages and applications. This intermediary automatically aggregates customer data from various sources and presents it in a unified view, resolving the contradiction by eliminating manual searching while ensuring comprehensive information access.
2Productivity
If the system provides direct action links to trigger customer actions, then user productivity increases, but the system complexity increases to generate and manage these action links
Solution Approach 1:
The system employs self-service mechanisms where automated search engines and action generators independently analyze customer context and generate appropriate action links without requiring complex manual configuration. The system serves itself by automatically understanding customer needs and creating relevant action options, resolving the contradiction by reducing the operational complexity burden while maintaining high productivity benefits.
Solution Approach 2:
The patent implements a universal action generation system that handles multiple types of customer actions (payments, appointments, information requests) through a single integrated mechanism. This multi-functional approach resolves the contradiction by consolidating what would otherwise require multiple separate systems into one unified action generation engine, reducing overall system complexity while maintaining diverse productivity-enhancing capabilities.
3Measurement precision
If the system analyzes previous transactions to generate recommended actions, then the accuracy of action recommendations improves, but the processing time and computational resources increase
Solution Approach 1:
The system applies local quality by focusing computational analysis only on the specific customer interaction context at hand rather than processing all historical data uniformly. The search engines analyze previous transactions selectively based on relevance to the current call situation, resolving the contradiction by maintaining high recommendation accuracy through targeted analysis while reducing overall computational resource consumption through selective processing.
Data Source
AI summary
Techniques for action prediction based on interactive history and context between a sender and a recipient are described herein. In one embodiment, a process includes, but is not limited to, in response to a message to be received by a recipient from a sender over a network, determining one or more previous transactions associated with the sender and the recipient, the one or more previous transactions being recorded during course of operations performed within an entity associated with the recipient, and generating a list of one or more action candidates based on the determined one or more previous transactions, wherein the one or more action candidates are optional actions recommended to the recipient, in addition to one or more actions required to be taken in response to the message. Key word identification out of voice applications as well as guided actions has also been applied to generate action prediction candidates interactive history links Other methods and apparatuses are also described.