Digital Standards Similarity Search Using Attribute Scoring
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Solution Overview
Problem
Existing standards documents, despite being digitized, lack efficient search functionality, making it time-consuming to find specific information, and conventional conversions to searchable formats do not adequately address this issue.
Innovation Solution
The conversion of standards to digital standards includes a data structure and data model that allows for similarity comparisons across documents, enabling faster and accurate identification of similar objects by substituting attribute data types for comparison and generating document similarity scores based on aggregated attribute scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If standards are converted to digital format, then accessibility and searchability are improved, but efficient search functionality and accurate information retrieval are not achieved
Solution Approach 1:
The patent transforms the search process by changing parameters from simple text matching to structured attribute-based comparison. Documents are converted from unstructured or semi-structured formats to structured data models with defined attributes and data types, enabling efficient filtering and comparison operations that reduce search time while improving accuracy.
Solution Approach 2:
The patent replaces conventional text-based search mechanisms with a data-driven comparison system. Instead of relying on keyword matching algorithms, the system uses structured data attributes, data type substitution, and automated score aggregation to identify similar documents, significantly improving both speed and precision of information retrieval.
2Measurement precision
If conventional text search is used on digitized standards, then basic search capability is provided, but accurate identification of similar objects is not achieved
Solution Approach 1:
The patent segments standards documents into discrete attributes with specific data types (e.g., numerical values, text strings, ranges). This segmentation allows the system to compare specific attributes independently using appropriate comparison methods for each data type, significantly improving search accuracy while the modular structure manages complexity through organized data classification.
Solution Approach 2:
The patent introduces structured data models and attribute schemas as intermediaries between the raw document content and the search comparison process. These intermediaries standardize the representation of information, enabling accurate comparisons by translating diverse document formats into a common structured framework that facilitates precise attribute matching.
3Productivity
If simple text matching is performed, then search speed is maintained, but format inconsistencies and data type variations are not handled
Solution Approach 1:
The patent creates a universal comparison framework that handles multiple data types (numerical, text, ranges, units) through a unified attribute-based system. The data type substitution mechanism allows the same comparison infrastructure to adapt to different formats automatically, maintaining high search efficiency while providing versatile handling of diverse standard document formats and data representations.
Data Source
AI summary
One embodiment provides a method for identifying similar objects by performing document attribute comparisons, the method including: receiving a reference document, wherein the reference document corresponds to an object and comprises a plurality of attributes of the object; receiving a request for a similarity comparison, wherein the request provides an indication of similarity attributes to be used in the similarity comparison; comparing the reference document to each of a plurality of documents corresponding to other objects; generating a document similarity score for each of the plurality of documents, wherein the document similarity score is generated based upon an aggregation of similarity attribute scores calculated for each of the similarity attributes; and providing at least one of the plurality of documents with an indication of a similarity. Other aspects are described and claimed.