File Suggestion Module for Multi-Source Querying
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Solution Overview
Problem
Users face challenges in accessing and managing files across multiple storage locations and applications, as existing methods are limited in multi-dimensional file storage environments, requiring manual searches and lacking efficient file suggestion mechanisms.
Innovation Solution
A system and method for automatically suggesting relevant files by detecting user actions and generating queries across local and remote data stores, prioritizing and grouping files based on relevance criteria, and presenting them through a user interface, utilizing a file suggestion module integrated within the operating system or applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual file search methods are used, then users can access files across multiple storage locations, but user efficiency decreases and time is lost due to manual searching
Solution Approach 1:
The system automatically performs file search and suggestion without requiring user intervention. The file suggestion module autonomously monitors user actions, generates search queries, and presents relevant files, allowing the system to serve itself rather than requiring manual user searching.
Solution Approach 2:
The system proactively suggests files before users need them by monitoring current user actions and pre-computing relevant file suggestions. This preliminary action of anticipating user needs and preparing file suggestions in advance eliminates the need for manual searching when users actually need files.
2Adaptability or versatility
If existing file suggestion approaches are used, then some file recommendations are provided, but they are limited to one-dimensional storage and lack multi-dimensional file context
Solution Approach 1:
The system transitions from one-dimensional file storage suggestions to multi-dimensional file context by incorporating file attributes, user actions, storage locations, and temporal relationships. This dimensional expansion allows the system to suggest files based on multiple criteria simultaneously, providing comprehensive multi-dimensional file context.
3Productivity
If automated file suggestion is implemented, then user efficiency improves, but processor load and network bandwidth usage increase
Solution Approach 1:
The system performs partial automated file suggestion by generating suggestions based on specific user actions and contexts rather than continuously searching all files. This partial action approach provides sufficient file suggestions to improve user efficiency while avoiding the excessive processor load and network bandwidth consumption that would result from comprehensive continuous searching.
Data Source
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AI summary
Relevant files are determined for a user upon detecting a user action such as save, load, open, view, share, or comparable ones associated with a file. The relevancy may be determined through one or more queries based on a number of criteria, where the queries are executed on local or remote data stores related to the user. For example, files on the local computing device of the user, files in an enterprise network associated with the user, files on a social network subscribed by the user may be evaluated for various relevancy criteria. Files determined to be relevant may be prioritized, ordered, and/or grouped for suggestion to the user and presented through a user interface of an application performing the detected action.