Chatroom List Sorting by Activeness and Context
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Solution Overview
Problem
Users face inconvenience in retrieving desired chatrooms due to the lack of efficient sorting methods, as existing systems rely on manual input or scroll functions, especially when the number of chatrooms increases, and do not consider user activeness or contextual information.
Innovation Solution
A computer-implemented method and system that automatically sorts chatrooms based on user activeness and contextual information by calculating activeness and similarity scores, placing actively used or likely-to-be-used chatrooms at the top of the list, using processors to recognize and store contextual information associated with conversation events, and sorting chatrooms accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple sorting conditions (recent message time, unread message count, favorite setting) are used, then the sorting method is simple and easy to implement, but the user cannot easily retrieve specific chatrooms when the number of chatrooms increases
Solution Approach 1:
The patent changes the sorting parameters from simple conditions (message time, unread count) to complex multi-dimensional parameters including user activeness scores, contextual information matching scores, and conversation frequency. This allows the system to automatically prioritize chatrooms based on user behavior patterns rather than requiring manual intervention.
Solution Approach 2:
The system performs self-service by automatically calculating activeness scores and matching contextual information without requiring user input. The chatroom list is automatically reorganized based on user behavior patterns, eliminating the need for users to manually search or set favorite chatrooms.
2Ease of operation
If users manually set favorite or pin chatrooms to the upper end of the list, then specific chatrooms can be retrieved easily, but users need to directly set specific chatrooms one by one which is time-consuming
Solution Approach 1:
The system automatically identifies and prioritizes important chatrooms by analyzing user activeness patterns and contextual information, eliminating the need for users to manually set favorite chatrooms. The system serves itself by autonomously organizing the chatroom list based on observed user behavior.
Solution Approach 2:
The system performs preliminary analysis of user conversation patterns and contextual information in advance, calculating activeness scores and preparing the sorted chatroom list before the user needs to retrieve chatrooms. This proactive organization saves user time by having chatrooms ready in optimal positions.
3Productivity
If existing sorting methods are used, then the system is simple to implement, but the system does not consider user activeness or contextual information reducing retrieval efficiency
Solution Approach 1:
The patent introduces new parameters for measuring user activeness (conversation frequency, message volume, participation ratio) and contextual information matching (location, time, situation). These parameters transform the sorting system from a simple chronological list to an intelligent, context-aware ranking system that improves retrieval efficiency.
Solution Approach 2:
The system continuously monitors user conversation behavior and uses this feedback to dynamically adjust chatroom priorities. By analyzing ongoing user activeness patterns and contextual information, the system adapts the chatroom list in real-time to reflect current user needs and improve retrieval efficiency.
Data Source
AI summary
The chatroom sorting method including recognizing contextual information associated with an event detection point in time and storing the recognized contextual information in association with a conversation related event in response to detecting the conversation related event with respect to each of chatrooms included in a chatroom list, calculating at least one of an activeness score associated with a participation of a user into a conversation for each of the plurality of chatrooms and a similarity score between a situation at a current point in time and the contextual information, and sorting at least a portion of the chatrooms included in the chatroom list based on at least one of the activeness score and the similarity score such that selected one or more chatrooms from among the chatrooms are placed on top of the chatroom list based on results of the sorting may be provided.