Auto-organizing Data Objects via Topic-Based Classification
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Solution Overview
Problem
User accounts accumulate large amounts of data, making it challenging to organize and find specific objects within this vast collection.
Innovation Solution
An object analysis and classification service is provided, which is a configurable platform that identifies objects relevant to a topic and provides analysis insights. This service includes technologies for object classification, clustering, and large language model prompts, allowing users to configure topics with specific parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually organize accumulated data objects, then organization quality improves, but time consumption and operational burden increase
Solution Approach 1:
The system performs automatic organization of data objects without requiring user intervention. The object analysis service autonomously analyzes objects, determines their relevance to topics, and organizes them into topic collections, allowing the system to serve itself rather than requiring manual user organization.
Solution Approach 2:
The patent replaces manual mechanical organization operations with automated computational analysis. Instead of users physically sorting and categorizing objects, the system uses object analysis services with machine learning models to automatically analyze and organize objects based on their content and relevance to topics.
2Reliability
If users search through accumulated data to find specific objects, then completeness of search improves, but search time and computational resources increase
Solution Approach 1:
The system performs preliminary organization of objects into topic collections before search is needed. By pre-analyzing objects and organizing them according to topics, the system prepares the data structure in advance, so that when a user needs to find objects, they are already categorized and can be retrieved quickly without searching through all accumulated data.
Solution Approach 2:
The patent segments the large collection of accumulated objects into smaller topic-based collections. Instead of one monolithic data set that requires comprehensive searching, the system divides objects into multiple topic collections, allowing users to search within relevant topics rather than through all data, improving both speed and efficiency.
3Measurement precision
If the system analyzes all objects in the collection, then accuracy of topic identification improves, but computational resources and processing time increase
Solution Approach 1:
The system applies partial analysis by focusing computational resources on analyzing objects that are most relevant to specific topics rather than uniformly analyzing all objects. The object analysis service determines relevance based on topic parameters and analyzes only those objects that meet relevance thresholds, avoiding unnecessary analysis of unrelated objects and conserving computational resources.
Solution Approach 2:
The patent applies different analysis depths and methods to different objects based on their local characteristics and relevance to topics. Rather than applying a uniform analysis process to all objects, the system adapts its analysis approach to each object's properties and its potential relevance to topics, optimizing computational resource usage while maintaining accuracy for relevant objects.
Data Source
AI summary
The present technology provides a solution that can bring organization to the accumulated data and can surface insights derived from an analysis of stored objects. More specifically, the present technology is directed to an object analysis and classification service which is a configurable platform for identifying objects relevant to a topic and providing analysis of the objects relevant to that topic. The object analysis and classification service can include one or more technologies for identifying objects relevant to a topic. The topic can be configured by a user account or can be a predefined topic selected by the user account. The topic can include parameters that can be used by the one or more technologies for identifying objects relevant to a topic and to provide insights defined by the topic.