Form Categorization via Non-Text Field Features
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Solution Overview
Problem
Current web search engines are inefficient for finding forms due to similarities in forms across different topics, leading to time-consuming searches as they rely solely on text-based features, which are inadequate for accurately categorizing forms.
Innovation Solution
The system categorizes forms using non-text field characteristics and field-specific text characteristics, enabling more accurate classification and search by associating forms with categories based on features such as field layout, field types, and specific text properties, rather than just relying on document text.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If text-based search is used to find forms, then search functionality is provided, but search accuracy and efficiency deteriorate due to form similarities across different topics
Solution Approach 1:
The patent segments the form classification process into multiple independent feature analysis components: text field analysis, non-text field analysis, and field-specific text characteristics. Each segment analyzes specific form attributes separately, then combines results to achieve accurate categorization despite similarities in common text fields across different form types.
Solution Approach 2:
The patent transitions from traditional single-dimension text-based search to multi-dimensional form analysis by incorporating non-text field characteristics (layout, structure, field types) and field-specific text characteristics. This dimensional expansion enables accurate differentiation of forms that share common text fields but differ in structural dimensions.
2Adaptability or versatility
If traditional text classification is used, then categorization is provided, but categorization accuracy deteriorates because forms in multiple categories share common words
Solution Approach 1:
The patent applies local quality analysis by examining field-specific text characteristics rather than treating all text uniformly. Each field's text is analyzed in the context of its specific role and position within the form structure, enabling accurate categorization even when common words appear across different form categories.
Solution Approach 2:
The patent creates a composite classification approach by combining multiple feature types (text fields, non-text fields, field-specific text characteristics) into an integrated analysis system. This composite methodology leverages the strengths of each feature type to achieve accurate form categorization that overcomes the limitations of any single feature type alone.
Data Source
AI summary
Systems and methods disclosed herein associate forms with categories based on form features for non-text field characteristics or field-specific text characteristics of the forms. One embodiment provides a method for facilitating searching for a form by associating forms with categories based on form features. The method involves automatically associating, by a processor of a computing device, forms with respective categories based on form features for non-text field characteristics or field-specific text characteristics of the forms and storing the forms and the respective categories associated with the forms at an electronic form search server. Search results are provided from the electronic form search server based on input identifying a search category and a form is identified as a search result based on the form being associated with the search category.