E-book Term Annotation via TF-IDF Disambiguation
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Solution Overview
Problem
Existing systems for wikification, particularly in the context of electronic books, are inefficient in detecting and disambiguating relevant terms due to their reliance on raw context analysis, which is cumbersome and not suited for large volumes of text, limiting the reader's ability to access deeper information.
Innovation Solution
A computer-implemented method employing TF-IDF based content analysis to automatically detect relevant terms in electronic books, disambiguate multi-sense terms, and establish hyperlinks to external information sources, allowing for direct and prompt presentation of related information on an electronic device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional raw context analysis is used for term disambiguation, then the system can identify relevant terms, but the process becomes cumbersome and interruptive to the reader
Solution Approach 1:
The system performs preliminary term detection and disambiguation processing during book compilation or preprocessing, so that when readers encounter terms, the relevant information is already prepared and can be displayed immediately without interrupting the reading flow
Solution Approach 2:
The system introduces an intermediary processing layer that automatically detects terms, retrieves relevant information from external sources, and presents it to readers in a streamlined manner, eliminating the need for readers to manually search while maintaining accuracy
2Loss of information
If manual search methods are used to find information about book terms, then readers can access detailed information, but the process is time-consuming and interruptive
Solution Approach 1:
The system pre-identifies and pre-processes term information during book compilation, so that when readers need information about a term, it is already prepared and can be displayed immediately without requiring manual search or interrupting the reading flow
Solution Approach 2:
The system introduces an intermediary processing layer that automatically detects terms, retrieves relevant information from external sources, and presents it to readers in a streamlined manner, eliminating the need for readers to manually search while maintaining accuracy
3Measurement precision
If existing wikification systems are applied to large volumes of text corpus, then comprehensive term coverage is achieved, but the processing efficiency decreases
Solution Approach 1:
The system segments the large text corpus into smaller manageable units such as chapters or sections, and processes each segment independently with optimized term detection algorithms, maintaining accuracy while improving overall processing efficiency through divide-and-conquer approach
Solution Approach 2:
The system focuses on detecting and processing only the most relevant terms rather than attempting to process every possible term in the text, using heuristics and context analysis to identify high-value terms that warrant detailed disambiguation, thus improving efficiency without significantly compromising coverage
Data Source
AI summary
Systems and methods for rendering automatic annotation for electronic books with external information provided by an information database. A computer implemented method is used to automatically determine key terms and match the key terms with correct information from external information sources for presentation at an e-book page. The key terms can be detected based on a TF-IDF based content analysis process. The detected key terms can be processed by a disambiguation process to select the pertinent definition for multi-sense terms according to one or more selected information sources. Hyperlinks can be embedded in the key terms for direct and convenient link to the matching external information in response to user interactions.