Collaborative Filtering for Label Similarity in Cloud Systems
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Solution Overview
Problem
Organizations face challenges with software installation and maintenance on in-house computer systems, including time-consuming processes, compatibility issues, and the need for frequent updates, which can lead to outdated software and increased resource demands.
Innovation Solution
Implementing an on-demand service environment using a multi-tenant database system that provides cloud-based services, allowing users to access software and resources over the internet, and utilizing collaborative filtering to identify and merge similar labels in social media messages, reducing the need for local software installation and enhancing data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If software is installed on in-house computer systems, then organization can control and customize software functionality, but installation and maintenance process becomes time-consuming and resource-intensive
Solution Approach 1:
The patent extracts the software installation and maintenance burden from the organization's in-house systems by transitioning to a SaaS model where Salesforce handles deployment and updates centrally, eliminating the need for organization personnel to manually install and maintain software on individual computer systems
Solution Approach 2:
The system enables self-service access where organization users can access and utilize software functionality through the cloud without needing technical expertise in installation or maintenance, while Salesforce's automated systems handle all infrastructure-level tasks
2Adaptability or versatility
If software is installed on multiple computer systems, then organization can deploy functionality across different devices, but compatibility problems increase and maintenance complexity increases
Solution Approach 1:
The SaaS platform provides universal access across different devices and operating systems through a single cloud-based instance, eliminating the need for separate software installations on each device while maintaining consistent functionality and compatibility across the entire organization
Solution Approach 2:
The cloud-based platform acts as an intermediary layer between the organization's diverse computer systems and the software functionality, abstracting away compatibility issues and maintenance complexity from the users while enabling universal access
3Productivity
If software is frequently upgraded, then organization can access new features and improvements, but software becomes outdated more quickly and maintenance resources increase
Solution Approach 1:
Salesforce performs all software updates, upgrades, and maintenance actions in advance on their centralized platform before the organization needs them, so the organization automatically benefits from new features and improvements without needing to schedule or manage update processes
Solution Approach 2:
The system continuously monitors usage patterns and feedback from organization users to automatically prioritize and schedule updates that provide the most value, while handling the technical complexity of deployment automatically without requiring organization involvement
4Reliability
If organization personnel monitor and maintain each software installation, then software reliability can be ensured, but resource requirements increase significantly
Solution Approach 1:
The system automatically monitors its own performance, usage patterns, and potential issues, eliminating the need for organization personnel to manually monitor each installation while maintaining high reliability through automated alerting and diagnostic capabilities
Solution Approach 2:
The cloud platform serves as an intermediary that absorbs all monitoring and maintenance responsibilities, providing centralized visibility and control while freeing organization resources from direct involvement in software reliability management
Data Source
AI summary
Disclosed are methods, apparatus, systems, and computer-readable storage media for identifying similar labels. In some implementations, one or more servers maintain a plurality of data entries in one or more database tables storing textual data, each data entry of a first portion of the data entries including: a text sequence, a label, and a text-to-label association score, and each data entry of a second portion of the data entries including: a first label, a second label, and a similarity score. The one or more servers analyze the data of the first portion of data entries to generate one or more pairs, each pair including information identifying a first label and a second label. The one or more servers calculate a similarity score for each of the one or more pairs and store the respective similarity scores in the second portion of the data entries.