Document Comparison Using Semantic XML Node Matching
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Solution Overview
Problem
Current document comparison techniques fail to provide semantically meaningful results, leading to inefficiencies and information loss, as they do not consider the structural and domain-specific semantics of documents, resulting in poor identification of changes and motivations behind revisions.
Innovation Solution
The system converts documents into XML representations and uses XPath or XQuery to select nodes for comparison, employing domain-specific matching sub-functions that compute scores and combine them to produce a match-score, with human curator input for weights and thresholds, to identify matched, moved, inserted, or deleted nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional textual and structural differencing techniques are used to compare document versions, then the comparison process is simple and fast, but the results lack semantic meaning and cause information loss
Solution Approach 1:
The patent introduces domain experts as intermediaries who provide semantic labels and relevance assessments for document sections. These experts act as mediators between the automated comparison system and the documents, enabling the system to understand semantic meaning without requiring full automation of semantic interpretation. This resolves the contradiction by adding human expertise rather than increasing algorithmic complexity.
Solution Approach 2:
The patent performs preliminary actions by having domain experts annotate and label document sections with semantic information before the comparison process begins. This pre-processing step creates a structured representation of semantic relevance that the comparison system can then utilize, avoiding the need for complex real-time semantic analysis during comparison.
2Measurement precision
If domain-specific semantic analysis is incorporated into document comparison, then the accuracy and meaningfulness of comparison results improve, but the complexity and time required for comparison increase
Solution Approach 1:
The patent segments the document comparison process into distinct phases: (1) preliminary semantic annotation by domain experts, (2) structured representation creation, and (3) automated comparison using the pre-established semantic framework. This segmentation allows computationally intensive semantic analysis to be performed once during preparation, rather than repeatedly during comparison, thus improving accuracy without proportionally increasing comparison time.
Solution Approach 2:
The patent performs domain-specific semantic analysis as a preliminary action before the actual comparison. By pre-annotating documents with semantic labels and establishing relevance relationships in advance, the system avoids performing complex semantic analysis during the comparison phase itself, thereby maintaining high accuracy while reducing comparison time.
3Reliability
If manual semantic annotation by domain experts is performed, then the semantic relevance of document sections is accurately captured, but the process becomes labor-intensive and slow
Solution Approach 1:
The patent performs manual semantic annotation as a preliminary action that needs to be done only once per document or document type. After the initial annotation establishes the semantic framework, subsequent comparisons can be performed automatically using this pre-established structure, thereby amortizing the manual effort across multiple comparisons and improving overall productivity while maintaining high reliability.
Solution Approach 2:
The patent creates a structured copy or representation of the document's semantic structure that can be reused across multiple comparison operations. Instead of requiring manual annotation for each comparison task, the system copies the pre-established semantic framework and applies it to different comparison scenarios, maintaining accuracy while significantly improving productivity.
Data Source
AI summary
Systems and methods of comparing structured documents are disclosed. From/to source documents are first represented by their respective from/to XML forms based on a predetermined schema. One or more from nodes are selected from the from XML document to compare to one or more to nodes from the to XML document. The comparison employs a set of matching functions that may be selected based on the domain of the source documents. The matching functions may compare just the tags of XML elements, and/or their text contents and/or any of their relevant attributes. The matching may be exact or approximate. Each matching function computes a score which may be weighted. For each pair of from/to nodes, an overall match-score is computed based on the scores of the individual matching functions. If the match-score reaches a matching-threshold, the pair is determined to be a match and further matching is stopped. The techniques are extended for comparing multiple from documents to a to document.