Chunk-Based Search Highlighting for Document Retrieval
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Solution Overview
Problem
Conventional search engines fail to efficiently locate and highlight relevant information within documents, requiring users to open documents and perform additional searches, which is time-consuming and inefficient, especially when search keywords are not in the exact order or are scattered across different chunks.
Innovation Solution
A computer system that identifies and highlights chunks within multiple documents matching search keywords, allowing users to search and display relevant chunks in a graphical user interface, with the ability to refine searches and reuse content across different document types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional search engines return document names with one or two sentences, then the search process is simple, but the user cannot understand the meaning of search keywords in context and must open documents manually
Solution Approach 1:
The patent segments documents into meaningful chunks (sentences, paragraphs, or custom-sized segments) and performs search at the chunk level rather than returning entire documents. This allows users to see multiple relevant chunks across different documents without opening each document, significantly reducing time to locate information while maintaining search simplicity.
Solution Approach 2:
The patent introduces an intermediary layer between the search engine and documents that extracts and displays relevant chunks. This intermediary processing layer analyzes document content, identifies matching chunks, and presents them to users before document opening, bridging the gap between simple search queries and contextual understanding.
2Loss of information
If users open documents using native applications to understand context, then they can read the full content, but the process is time-consuming and the native application does not highlight search keywords
Solution Approach 1:
The patent performs preliminary search and chunk identification before the user opens documents. By pre-processing document content, extracting meaningful chunks, and highlighting matching search keywords in advance, the system eliminates the need for users to open documents and perform additional searches, saving significant time while preserving contextual understanding.
Solution Approach 2:
The patent uses visual highlighting (color changes) to emphasize search keywords within chunks and across multiple documents. This visual differentiation allows users to quickly identify and understand the context of search terms without opening documents, making keyword locations immediately apparent in the search results interface.
3Measurement precision
If search tools look for multiple search keywords in exactly the same order, then the search is precise, but the user may find nothing even if the document contains the keywords in different order
Solution Approach 1:
The patent implements dynamic search matching that adapts to different keyword orders and variations within chunks. Rather than requiring exact sequential matching, the system dynamically identifies chunks containing all search keywords regardless of order, and can handle variations in keyword spacing and surrounding text, preventing loss of relevant document content.
Solution Approach 2:
The patent changes the matching parameters from strict sequential keyword order to flexible chunk-based matching. By adjusting the search parameters to identify chunks containing all keywords in any order and allowing variations in spacing and context, the system maintains precision while recovering relevant information that would be missed by rigid ordering requirements.
4Productivity
If users limit the search to a subset of search keywords, then the search speed increases, but many instances of the subset may exist and the user spends significant effort finding the content of interest
Solution Approach 1:
The patent segments search results into meaningful chunks that contain complete contextual information for each keyword match. By organizing results at the chunk level rather than presenting all individual keyword instances, the system maintains fast search speed while reducing the effort needed to find relevant content, as users can quickly scan contextualized chunks instead of searching through numerous isolated keyword occurrences.
Data Source
AI summary
After receiving a first user request including a first set of search keywords, a computer identifies a first set of chunks within multiple documents, wherein each chunk includes terms matching the first set of search keywords, and displays at least a portion of the first set of chunks, including highlighting the terms matching the first set of search keywords in the displayed portion in a first manner. After receiving a second user request to search among the documents for documents that satisfy a second set of search keywords, the computer identifies a second set of chunks within the documents, wherein each chunk includes terms matching the second set of search keywords, and displays at least a portion of the second set of chunks, including highlighting the terms matching the second set of search keywords in the displayed portion in a second manner that is different from the first manner.