Content Mapping via Fingerprinting and Boyer-Moore Search
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Solution Overview
Problem
Conventional approaches fail to efficiently transfer user-provided supplemental content, such as annotations and notes, from individual e-book instances to omnibus versions, often requiring resource-intensive full string searches that are time-consuming and impractical for large-scale implementations.
Innovation Solution
The use of efficient string search algorithms like the Boyer-Moore search algorithm and fingerprinting processes to pre-process and quickly match content, allowing for the automated mapping of positions between individual and omnibus versions, enabling the transfer of supplemental content without full string comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full string search is used to match individual e-book content to omnibus version, then matching accuracy is improved, but computational time and resource consumption increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-processing the omnibus content to create a fingerprint database before actual matching occurs. Fingerprints (hash values) of content segments are generated in advance and stored for quick comparison, eliminating the need for resource-intensive full string searches during the matching phase while maintaining accurate identification of corresponding content between individual e-books and the omnibus version
Solution Approach 2:
The patent extracts key identifying features (fingerprints) from the full content and uses only these extracted features for matching. By taking out essential content characteristics and representing them as compact fingerprint values, the system achieves accurate matching without processing the complete text, thereby dramatically reducing computational time and resources
2Loss of information
If full string search is used to transfer annotations and notes, then transfer completeness is improved, but computational resources and energy consumption increase
Solution Approach 1:
The patent uses fingerprint copying as a lightweight alternative to full content comparison. Instead of copying and comparing entire text strings, the system copies and compares compact fingerprint representations that uniquely identify content segments. This approach ensures complete transfer of annotations and notes while consuming minimal computational energy
Solution Approach 2:
The system performs preliminary fingerprint generation and storage for all omnibus content segments before the transfer operation. This pre-computation allows the transfer process to simply compare fingerprints rather than perform energy-intensive full string searches, achieving complete annotation transfer with significantly reduced energy consumption
3Device complexity
If conventional matching methods are used, then implementation simplicity is maintained, but scalability to large-scale implementations deteriorates
Solution Approach 1:
The patent implements scalability through preliminary fingerprint database construction. By pre-processing the omnibus content and storing fingerprint indexes before matching operations, the system enables rapid scaling to large collections of e-books and omnibus versions. The pre-built fingerprint database allows linear-time matching operations that scale efficiently, whereas conventional methods would require quadratic-time full string comparisons that become prohibitively slow at scale
Solution Approach 2:
The patent introduces fingerprints as an intermediary layer between the raw content and the matching process. This intermediary representation simplifies the matching operation to a straightforward fingerprint comparison rather than complex full-text analysis. The intermediary fingerprint layer maintains implementation simplicity while enabling efficient scaling to large datasets through its compact and computationally efficient nature
Data Source
AI summary
Automated mapping between instances of content, such as e-books, and omnibus versions of that content can be performed without a resource-intensive full string search. In one embodiment, an efficient string search algorithm, such as the Boyer-Moore algorithm, is used to pre-process the individual book in order to more efficiently search for a match within the omnibus version. In another embodiment, a fingerprinting process is used to quickly find the beginning and end positions of a book within the omnibus version. The fingerprinting process can also quickly verify the match between the identified portion of the omnibus and the contents of the individual book without the need for a full string comparison. A mapping is then generated that enables the supplemental content to be updated for the omnibus version.