Context-Aware Text Document Analysis via Pre-Stored Index
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Solution Overview
Problem
Existing text document analysis methods are inefficient when analyzing large quantities of documents for the frequency and context of target words, leading to extended analysis time and high computation costs, especially when multiple words need to be investigated.
Innovation Solution
An analysis device and method that stores context and index information for text documents, allowing for the detection of target word frequencies within specific contexts, reducing computation time and cost by pre-storing context and index information for quick analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If text document analysis is performed by extracting sentences containing target words and analyzing context for each sentence, then the analysis accuracy is improved, but the analysis time is extended when the quantity of target documents is large
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing context information for sentences before actual target word analysis. The system divides documents into sentences in advance, analyzes the context of each sentence beforehand, and stores this pre-analyzed context information in a database. When target word analysis is needed, the system directly retrieves the pre-stored context information instead of re-analyzing, thereby maintaining high analysis accuracy while significantly reducing analysis time for large document quantities.
2Loss of information
If identical processing is repeated for multiple target words to investigate their reputations, then the analysis completeness is improved, but the computation cost becomes large
Solution Approach 1:
The patent applies universality by creating a context information database that serves multiple target words simultaneously. The pre-analyzed context information is stored in a universal database structure that can be queried for any target word. When analyzing multiple target words, the system retrieves relevant context information from this shared database rather than performing separate complete analyses for each word, thereby maintaining analysis completeness while significantly reducing repeated computation costs.
3Productivity
If context information is stored for each sentence containing target words, then the analysis speed is improved, but the storage requirement increases
Solution Approach 1:
The patent applies extraction by selectively storing only the essential context information needed for analysis rather than storing complete sentence data or redundant information. The system extracts and stores key contextual features and pre-analyzed results in a structured database format. This approach retrieves only necessary information during analysis, achieving high analysis speed while minimizing storage requirements by eliminating redundant data.
Data Source
AI summary
An analysis device for analyzing a text document is provided. The analysis device includes a context storage unit configured to store context information that shows a position of a character set of a predetermined context in the text document. The analysis device also includes an index storage unit configured to store index information that shows a position of a word in the text document, for each word of a plurality of words contained in the text document. An input unit is configured to input a target word. A position detection unit is configured to detect from the index information a position of the target word contained in the text document. A frequency detection unit is configured to detect an appearance frequency of the target word per each type of context in the text document based on the position of the target word and on the context information.