Custom Dictionary for E-books Using Reader Profile
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Solution Overview
Problem
E-books often lack custom dictionaries, leading to difficulties for users in understanding rare or specialized terms, as on-board general dictionaries may not include all relevant words, resulting in incomplete comprehension and the need for external searches.
Innovation Solution
A computer-implemented method and system generate a custom dictionary for an e-book by selecting candidate words based on a user's reading profile and e-book content, providing definitions and complexity scores, which can be adjusted by the user for personalized reading assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a general on-board dictionary is used, then users can look up common terms, but specialized or rare terms in the e-book may not be included, resulting in incomplete comprehension
Solution Approach 1:
The system performs preliminary analysis of the e-book text to identify candidate specialized terms before generating the custom dictionary. This advance preparation ensures that rare and specialized terms are captured in advance, improving dictionary coverage without requiring complex real-time processing during reading.
Solution Approach 2:
The dictionary system transitions from a static general dictionary to a dynamic custom dictionary that adapts to the specific e-book content. The system automatically adjusts the dictionary composition based on the analyzed text, enabling it to include specialized terms relevant to that particular e-book while maintaining manageable complexity through automated processes.
2Reliability
If a custom dictionary is generated with all candidate words, then user comprehension is improved, but the dictionary size and processing complexity increase
Solution Approach 1:
The system introduces a complexity score parameter to evaluate and rank candidate words. By setting a threshold based on this parameter, the system filters the candidate word list to include only those terms that meet the complexity criteria. This parameter-based filtering improves comprehension accuracy for relevant terms while controlling dictionary size by excluding less significant words.
3Loss of information
If the dictionary includes all rare terms, then completeness is improved, but the user interface becomes more complex with additional settings
Solution Approach 1:
The system implements self-service functionality by automatically analyzing the e-book text, identifying candidate specialized terms, calculating their complexity scores, and generating the custom dictionary without requiring manual user intervention. This automation ensures complete term definition coverage while maintaining ease of operation, as users simply need to select the dictionary feature without managing complex settings.
Data Source
AI summary
A custom dictionary is generated for an e-book. A dictionary management system receives a custom dictionary request from a user client operated by a user, the custom dictionary request identifying the e-book and including dictionary management information describing the user. The dictionary management system chooses a group reader profile that has an associated group reading score for the user based on the dictionary management information and candidate words are identified in the identified e-book for inclusion in the custom dictionary. The dictionary management system selects words for inclusion in the custom dictionary from among the candidate words responsive to the associated group reading score for the chosen group reading profile. The dictionary management system generates the custom dictionary using the selected words, and provides the generated custom dictionary to the user client.