Playable Document Snippets in Chat Streams
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional document interaction systems either focus on a single document type or lack seamless integration of multiple document types during online conversations, making it difficult for users to reference specific parts of documents within the conversation flow, especially in modern workflows involving various document types.
Innovation Solution
A computer-implemented method that detects user interactions with documents, analyzes their content and layout, and generates playable document snippets, which are then inserted into conversation streams, allowing users to interact with multiple document types without opening separate viewers, and enabling replies and grouping of user actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If document-centric approaches embed conversations inside one document, then users can reference specific parts of the document easily, but the system does not support well the modern workflow where many documents and document types are used
Solution Approach 1:
The system creates a universal conversation stream that can handle multiple document types (Word documents, Excel spreadsheets, PDFs, images, code snippets) through a single interface. The snippet generation engine is designed to work with any document type by detecting user actions and generating playable snippets regardless of the underlying document format, making the system multi-functional and adaptable to modern workflows involving diverse document types.
Solution Approach 2:
The system segments documents into playable snippets based on user actions (mouse clicks, text selections, voice comments). By dividing continuous documents into discrete, actionable snippets that can be embedded in the conversation stream, the system maintains ease of referencing specific parts while enabling support for multiple document types through a unified snippet-based approach.
2Adaptability or versatility
If conversation-centric approaches allow conversations outside the document, then conversations can bring in different documents, but users have no means to bring comments they make over the document inside the conversation
Solution Approach 1:
The system merges the advantages of both document-centric and conversation-centric approaches by embedding playable document snippets directly within the conversation stream. This integration allows users to reference specific document parts while keeping the conversation flowing externally, and automatically captures document comments and actions within the conversation context, preventing information loss.
Solution Approach 2:
The snippet generation engine acts as an intermediary that captures user actions on documents (mouse clicks, text selections, voice comments) and transforms them into playable snippets that can be embedded in the conversation stream. This intermediary mechanism ensures that document-specific interactions are preserved and made accessible within the external conversation context.
3Ease of operation
If users are forced to make up references like 'I don't agree with bullet 3 on slide 4', then the communication is hard to follow, but automatically generating playable snippets requires complex document analysis
Solution Approach 1:
The system employs automatic document analysis that detects user actions (mouse clicks, text selections, voice comments) and autonomously generates playable snippets without requiring users to manually create references. The snippet generation engine automatically analyzes document content, structure, and user interactions to create contextualized snippets, eliminating the need for users to manually formulate references like 'bullet 3 on slide 4' while managing the analytical complexity behind the scenes.
4Adaptability or versatility
If the system generates playable snippets from user actions, then users can interact with multiple document types seamlessly, but the system complexity increases
Solution Approach 1:
The system extracts the essential information needed for conversation from diverse document types by detecting user actions and generating playable snippets. Instead of requiring a separate complex system for each document type, the snippet generation engine extracts relevant content, context, and user actions into a unified snippet format that can be embedded in the conversation stream, reducing overall system complexity while maintaining versatility.
Data Source
AI summary
System that automatically embeds interactive document snippets inside chat conversation stream. Specifically, described are techniques to automatically crop meaningful areas on document pages based on users' actions and underlying content to embed them inside chat window. Embedded snippets are easy to view because smart cropping provides viewers enough context. Snippets are playable inside the chat window so users can view the snippet without having to open the corresponding document. Importantly, viewers can reply inline to a document snippet, also without having to open the original document page. Like traditional text messages, snippets are appended to the conversation chat window, allowing co-workers to see what was added. When users choose to focus on document itself (as opposed to working inside the chat window only), the system automatically shows all relevant document snippets as well as chat messages, helping the person quickly see what conversations happened around this part of the document.