Letter-Based Text Fingerprinting for Plagiarism Detection
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Solution Overview
Problem
Current methods for detecting content piracy in natural language text documents, such as eBooks and news articles, are inadequate, as existing technologies fail to effectively identify plagiarism and protect intellectual property.
Innovation Solution
A computer-implemented method and apparatus that generates a letter-based fingerprint of natural language text by detecting letter-based patterns and computing signal strength magnitudes, allowing for the detection of plagiarism by comparing these fingerprints across different texts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing plagiarism detection methods are used, then detection capability is limited, but system complexity and resource consumption increase
Solution Approach 1:
The patent segments text into fixed-size windows (e.g., 50-200 characters) and generates fingerprints for each window independently. This segmentation allows the system to detect plagiarism in large documents efficiently by processing manageable chunks, improving both detection reliability and computational efficiency while reducing overall system complexity
Solution Approach 2:
The patent creates simplified representations (fingerprints) of text segments that capture essential features without storing complete text. These fingerprints serve as compact copies that enable comparison and plagiarism detection with minimal computational resources, resolving the contradiction between detection capability and system complexity
2Productivity
If text is segmented into windows for fingerprint generation, then processing efficiency improves, but detection precision may be affected by window boundaries
Solution Approach 1:
The patent designs the fingerprint generation process to be boundary-agnostic by using fixed-size windows and consistent feature extraction methods that work regardless of where window boundaries fall. The same fingerprinting algorithm is applied universally to all windows, ensuring detection precision is maintained while enabling efficient batch processing of segmented text
Solution Approach 2:
The patent uses overlapping windows or multiple fingerprint comparisons per segment to compensate for potential boundary effects. By performing slightly more comparisons than the minimum required (excessive action), the system ensures that no plagiarism instances are missed due to arbitrary window boundaries, thus maintaining high detection precision while preserving processing efficiency
Data Source
AI summary
A computer-implemented letter-based method of encoding a length-significant portion of natural language text to generate a letter-based fingerprint of the text portion, the method including detecting letter-based locations of occurrences of pre-determined single-letter and/or multi-letter pattern(s) within the length-significant portion, the detecting being carried out such that at least some occurrences are detected in a word-boundary independent manner that does not depend on locations of word-word boundaries, for a pattern occurrence letter-position signal which describes letter positions of the occurrences of the patterns within the text portion, computing frequency-dependent absolute or relative magnitudes of signal strength for a plurality of frequencies, the computed magnitudes representing letter-based frequencies of the pattern occurrences within the natural language text portion, and storing the computed signal strength magnitudes at the plurality of frequencies, the generated fingerprint comprising the stored signal strength magnitudes. Related apparatus and methods are also described.