Search Term Generation from Selected Text Sections
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Solution Overview
Problem
Current search systems require user interaction for selecting and deleting search terms for each search, fail to recognize relevant sections within documents, and cannot generate search terms from non-text documents or specific sections, leading to increased user effort and irrelevant results.
Innovation Solution
A system and method that automatically generate search terms by parsing selected text or non-text objects based on user-defined profiles, allowing users to drag-and-drop graphical icons into a search engine to perform searches, including text documents, images, and audio files, by identifying specific items within these objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the system scans all sections of documents for word frequencies, then it can extract common words from the entire document, but it increases user effort to sort through irrelevant search terms and fails to recognize relevant sections
Solution Approach 1:
The patent divides the document into multiple sections and allows users to select specific sections for analysis. Instead of scanning the entire document, the system processes only the selected sections, reducing the quantity of search terms generated and decreasing user effort to review and sort through them.
2Adaptability or versatility
If the system requires user interaction for selecting and deleting search terms for each search, then it allows users to customize search terms, but it increases user effort and time for each search operation
Solution Approach 1:
The patent allows users to pre-select and pre-process documents to generate search terms in advance. By performing the analysis and term generation before the actual search operation, the system reduces or eliminates the need for user interaction during each search, thereby reducing time loss while maintaining customization through pre-established profiles.
3Adaptability or versatility
If the system cannot generate search terms from non-text documents, then it simplifies the processing mechanism, but it limits the system's ability to handle diverse file types such as images, audio, and video
Solution Approach 1:
The patent implements a universal processing mechanism that can handle multiple document types including text documents, images, audio files, and video files. The system uses appropriate parsers for each file type to extract relevant information and generate search terms, thereby achieving multi-functionality without significantly increasing overall system complexity through standardized processing pipelines.
4Measurement precision
If the system scans all sections of documents, then it ensures comprehensive word frequency analysis, but it generates more search terms that may not be relevant to the user's actual needs
Solution Approach 1:
The patent applies local quality analysis by allowing users to select specific sections of documents that are most relevant to their search needs. The system then performs word frequency analysis only on these selected sections, generating search terms that are more likely to be relevant. This localized approach reduces the quantity of irrelevant search terms while maintaining sufficient measurement precision for effective searching.
Data Source
AI summary
A text object(s) such as a document containing a plurality of text items (e.g., chapters, paragraphs, etc.) is used to generate a search term. At least one, but not all, of the text items in the text object are selected based on a profile. The selected text item(s) are parsed to generate one or more search terms. This allows a user to drag-and-drop a graphical text object into a search engine icon to automatically perform a search based on the profile. Alternatively, a non-text object (e.g., an image) containing any identifiable item is used to generate the search term. Based on the profile, the item is parsed to generate a text representation of the item. The text representation of the item is used to generate one or more search terms.