Web Document Auto-Annotation with Sentence Embeddings and Text Generation
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Solution Overview
Problem
Existing methods for interacting with and annotating web content are inefficient, leading to time waste and the persistence of inaccurate information, as users resort to repetitive searches, bookmarking, and manual text copying to share and discuss web document snippets, lacking tools for efficient annotation and information dissemination.
Innovation Solution
An annotation-enabled web browser that allows users to create and organize annotations on web pages, pictures, videos, and sound recordings, with a separate context area for viewing and managing these annotations, enabling efficient sharing and organization while maintaining minimal document distraction and providing non-intrusive advertisements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually copy and paste text to share web document snippets, then information can be shared, but time is wasted and efficiency is reduced
Solution Approach 1:
The patent segments web documents into annotatable snippets that can be independently selected, annotated, and shared. Users can highlight specific portions of text rather than copying entire documents, enabling efficient information sharing of only the relevant parts.
Solution Approach 2:
The patent implements a copying mechanism where annotated snippets are automatically copied to a clipboard or buffer with metadata, allowing users to paste and share them across applications without manual selection and copying of text.
2Productivity
If users repeat searches to find previously accessed content, then information can be retrieved, but productivity decreases
Solution Approach 1:
The patent performs preliminary actions by automatically indexing and storing metadata about web documents and their annotations as users encounter them. This pre-processing enables rapid retrieval through the annotation search interface without requiring users to re-search for previously viewed content.
Solution Approach 2:
The patent provides feedback mechanisms where the system learns from user annotation patterns and search behavior, improving the relevance of search results and suggesting previously annotated content that matches current query intent, thereby reducing repetitive searching.
3Ease of operation
If annotation interfaces are prominently displayed, then annotations are easily accessible, but document viewing context is distracted
Solution Approach 1:
The patent extracts annotations from the main document viewing area and places them in a separate annotation search interface or sidebar. This separation allows users to access annotations without them obscuring or distracting from the primary document content.
Solution Approach 2:
The patent implements dynamic annotation display where the annotation interface adapts its visibility and positioning based on user interaction. Annotations can be collapsed, expanded, or repositioned to minimize distraction while maintaining accessibility when needed.
4Reliability
If accurate information identification tools are provided, then information accuracy improves, but device complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically detects and flags potential inaccuracies in web content through analysis of user annotations and consensus patterns, without requiring complex manual verification processes.
Solution Approach 2:
The patent introduces an intermediary layer of annotation-based verification where user comments and corrections serve as a mediator between content creators and consumers, enabling community-driven accuracy improvement without adding complex verification infrastructure.
Data Source
AI summary
The present disclosure relates to methods, non-transitory computer readable mediums (CRMs), and systems for the determination of similar information and text generation for auto-annotation of web documents. This disclosure discusses the use of sentence embedding vectors for the determination of similar information. Furthermore, this disclosure discusses the use of natural language processing techniques and deep learning for the generation of text for use within web browser viewable auto-annotations of content within web documents.