Contextual Content Recall via Travel Session Filtering
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Solution Overview
Problem
Users face difficulties in recalling specific digital content items accessed during travel due to fading memory and large amounts of content, especially for frequent commuters or business travelers who multitask and experience changes in routine.
Innovation Solution
A computer-implemented method and system that associates digital content with travel session data, including routes, to filter search results based on potential user sessions of interest, allowing users to recall content items by searching for contextual data such as travel routes, even if they do not remember the exact location or time of access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users search for content items in a large content repository, then the content can be found, but the search becomes increasingly difficult and time-consuming due to fading memory and large amounts of content
Solution Approach 1:
The system performs preliminary actions by automatically capturing and storing contextual data (location, time, device information) at the moment content is accessed. This preliminary recording eliminates the need for users to remember search details later, directly resolving the contradiction between fading memory and search time.
Solution Approach 2:
The system introduces contextual data as an intermediary between the user's memory and the content repository. Instead of relying directly on user memory to search vast content stores, the contextual data serves as a mediator that bridges the gap, enabling efficient retrieval without burdening user memory.
2Adaptability or versatility
If users access content during travel sessions with changing routines and multitasking, then content consumption increases, but the ability to recall specific content details deteriorates
Solution Approach 1:
The system records contextual information (route data, location, time) in advance during travel sessions before the user needs to recall content. This preliminary capture of context during flexible access periods enables accurate recall later despite changing routines and multitasking.
Solution Approach 2:
The system adds temporal and spatial dimensions to content access by recording when and where content was consumed during travel. This dimensional enrichment transforms simple content access into multi-dimensional data that can be precisely retrieved later, overcoming the limitations of multitasking and routine changes.
3Measurement precision
If the system stores detailed information about all content access events, then recall accuracy improves, but data storage requirements and system complexity increase
Solution Approach 1:
The system extracts only the most relevant contextual features (route data, location, time) from content access events rather than storing all possible details. This selective extraction maintains high recall precision while minimizing storage requirements and system complexity.
Solution Approach 2:
The system applies different levels of detail storage based on local requirements - storing comprehensive contextual data for travel sessions where recall is needed, while using simpler storage for other contexts. This localized approach optimizes the balance between precision and complexity.
Data Source
AI summary
Systems and methods for recalling digital content utilizing contextual data are disclosed. In embodiments, a method includes: determining, by a computing device, that a user has accessed a content item from a content resource; associating, by the computing device, the content item with session data, the session data including a route between a first location and a second location; receiving, by the computing device, a first search query; determining, by the computing device, one or more potential user sessions of interest based on the first search query; receiving, by the computing device, a second search query directed to the content item; and filtering, by the computing device, search results of the second search query based on the one or more potential user sessions of interest to produce filtered search results including one or more content items associated with the session data.