Document Version Identification via Candidate Identifier Matching
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Solution Overview
Problem
Information retrieval systems face challenges in identifying and managing multiple versions of documents, leading to inaccurate citation counts and overcrowded search results, which affect the quality of search engine outputs.
Innovation Solution
The system generates and matches multiple candidate identifiers based on document metadata, normalizes them using language-specific rules, and compares them for similarity to cluster and identify different versions of documents, while summing citation counts for an accurate assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple versions of documents are included in search results, then the quantity of search results increases, but the quality of search results deteriorates due to redundancy and lack of diverse content
Solution Approach 1:
The patent segments documents into version groups by identifying duplicate versions through metadata comparison. Each version group contains multiple versions of the same document, allowing the system to select one representative version for search results while maintaining awareness of all versions. This segmentation eliminates redundancy without losing information.
Solution Approach 2:
The patent creates canonical versions as standardized copies of document versions. By generating a single canonical representation for each version group and using it for search result display, the system avoids presenting multiple identical versions while still providing comprehensive coverage of the document collection.
2Quantity of substance
If multiple versions of documents are present in the repository, then each version has its own citation count, but the accuracy of citation count assessment deteriorates
Solution Approach 1:
The patent merges citation counts from all versions within a version group to produce a single aggregated citation count for the canonical version. This combining approach ensures that the citation metric reflects the total impact of the document across all its versions, providing an accurate assessment of the document's significance.
Solution Approach 2:
The patent implements a feedback mechanism where citation counts from individual versions are aggregated and fed back to update the canonical version's citation metric. This ensures that the citation count continuously reflects the cumulative impact of all document versions.
3Reliability
If document versions are identified and managed, then the reliability of search results improves, but the device complexity increases due to version matching and normalization processes
Solution Approach 1:
The patent performs preliminary actions by pre-processing document metadata to create normalized forms and candidate identifiers before the actual version matching process. This preliminary normalization of metadata (converting to lowercase, removing punctuation, standardizing formats) simplifies subsequent comparison operations and reduces the complexity of the matching algorithm.
Solution Approach 2:
The patent introduces candidate identifiers as intermediary representations that simplify the version matching process. Instead of directly comparing complex metadata structures, the system uses these intermediate identifier strings as mediators for comparison, reducing computational complexity while maintaining matching accuracy.
Data Source
AI summary
A system and method identifies different versions of the same document in a document collection. The system and method creates multiple candidate identifiers for each document based on information associated with the document, and processes the candidate identifiers according to language specific rules. The system and method compares the processed candidate identifiers for similarity, and identifies different versions of documents based on the similarity.