Context-Aware Document Retrieval via Preliminary Action
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Solution Overview
Problem
Users face difficulty in accessing and managing documents across multiple computing devices and cloud storage due to the vast number of documents and varying contexts in which they were accessed, making it hard to retrieve specific documents efficiently.
Innovation Solution
A system and method that identify documents accessed by a user, including context information such as date, time, applications, calendar events, and shared documents, to create a list of documents accessed in similar contexts, allowing for the presentation of a subset list matching the current context to the user, thereby simplifying document retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users store documents on cloud storage to access them across multiple devices, then document accessibility and sharing capability are improved, but the complexity of managing and retrieving specific documents increases
Solution Approach 1:
The system performs preliminary actions by automatically analyzing user access patterns, document metadata, and contextual information in advance. It pre-processes this data to build structured profiles and relationships, so when a user needs to retrieve a document, the system has already organized the information needed for rapid, context-aware retrieval, eliminating the need for users to manually manage complex storage structures.
2Quantity of substance
If the system provides a complete list of all accessed documents, then comprehensive document coverage is achieved, but the difficulty of locating specific relevant documents increases
Solution Approach 1:
The system segments the complete document list into multiple organized groups based on contextual similarities. Documents are divided into categories such as those accessed during similar time periods, with the same applications, in similar calendar events, or with shared collaborators. This segmentation transforms an overwhelming monolithic list into manageable, contextually-relevant subsets, making it easier for users to locate specific documents without sacrificing comprehensive coverage.
Solution Approach 2:
Different portions of the document list are given different organizational qualities based on their contextual characteristics. Documents are not uniformly sorted but rather organized according to their specific contextual attributes - some grouped by time, others by application, others by collaborative context. This local quality approach ensures that each document appears in the most relevant contextual group, optimizing retrieval efficiency for diverse user needs.
3Measurement precision
If the system analyzes detailed context information for each document, then document retrieval accuracy is improved, but the processing time and system complexity increase
Solution Approach 1:
The system performs preliminary analysis of context information whenever documents are accessed or metadata is generated. It pre-processes and stores contextual attributes (time, application, calendar events, collaborators) in structured formats during natural document interactions, rather than analyzing everything from scratch during retrieval. This preliminary action significantly reduces processing time during actual document search while maintaining high retrieval accuracy.
Solution Approach 2:
The system applies partial analysis by focusing on the most relevant contextual attributes for each retrieval scenario rather than analyzing all possible context dimensions equally. It selectively weighs and processes context information based on the current user needs and document types, performing excessive analysis only when necessary to achieve high precision for complex retrieval scenarios, thereby optimizing the balance between accuracy and processing time.
Data Source
AI summary
Disclosed is a document management system where accessed documents can be stored in a document list along with information regarding the context in which the documents were accessed. The context can include information regarding the time and date the document was accessed and what applications were running when the document was accessed. Other context information can include whether the document was accessed during a calendar event or if the document was included in an attachment to an e-mail. When the current context of the computing device matches a previously recorded context, documents from the document list can be entered into a subset list and presented to the user.