Image Processing Apparatus Contextual Page Selection
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Solution Overview
Problem
Existing printing technologies cannot ensure that the output page data accurately reflects the user's intended content, as they simply print pages containing designated keywords without considering the broader context or relevance.
Innovation Solution
An image processing apparatus that receives a target file with multiple page data and classification data, extracts specific page data containing a designated character string, determines a specific group within the classification data, and outputs additional target page data from this group, ensuring that the printed pages are contextually relevant to the user's intent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system simply prints pages containing the designated keyword, then the printing process is fast and simple, but the printed pages may not conform to user intention and lack contextual relevance
Solution Approach 1:
The patent introduces classification data as an intermediary layer between the keyword search and the final page selection. The classification data organizes pages into hierarchical groups (first group, second group, etc.), allowing the system to not only find pages containing the keyword but also to understand the contextual relationship between pages. This intermediary structure enables more accurate page selection that conforms to user intention while maintaining operational simplicity.
2Measurement precision
If the system outputs only the specific page containing the designated character string, then the output is precise to the keyword, but it fails to provide contextually related pages that the user may need
Solution Approach 1:
The patent segments the page set into multiple classification groups (first group, second group, third group, etc.) based on classification data. When a keyword is found in a specific page, the system identifies which group that page belongs to and then outputs not only the specific page but also other pages within the same group. This segmentation approach preserves contextual information by grouping related pages together while maintaining precise keyword matching capability.
Solution Approach 2:
The classification data is prepared in advance, organizing all pages into hierarchical groups before the keyword search is performed. This preliminary organization allows the system to quickly determine which group contains the keyword-matched page and immediately retrieve other relevant pages from the same group, rather than having to analyze contextual relationships after the search is complete.
3Reliability
If the system analyzes all page data to determine contextual relevance, then the output accuracy improves, but the processing time and complexity increase
Solution Approach 1:
The classification data is pre-computed and stored, organizing pages into hierarchical groups before any keyword search is performed. This preliminary action eliminates the need for complex real-time analysis of all pages during the search process. When a keyword is found, the system simply queries the pre-established classification structure to identify relevant groups, dramatically reducing processing complexity while maintaining high output accuracy.
Solution Approach 2:
By segmenting pages into classification groups, the system avoids the complexity of analyzing all pages individually for contextual relevance. Instead, the pre-established groupings provide ready-made contextual relationships, allowing the system to determine relevance by simple group membership queries rather than complex pairwise comparisons between all pages.
Data Source
AI summary
An image processing apparatus configured to: receive a target file including m page data relating to m pages and classification data classifying the m page data into n groups, m being an integer of 3 or larger, and n being an integer of 2 or larger and smaller than m; receive information of a designated character string; extract specific page data relating to a page including the designated character string from the m page data by analyzing the target file; determine a specific group of the n groups by using the classification data, the specific group including the extracted specific page data; determine one or more target page data to be output of the page data included in the specific group, the one or more target page data including page data different from the specific page data; and output the one or more target page data.