Web Page Information Extraction via Tag Tree Parsing
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Solution Overview
Problem
Existing search engines struggle to efficiently extract questions and answers from web page content, requiring users to sift through entire pages, which is time-consuming and inefficient due to the scarcity of resources containing questions and answers on the internet.
Innovation Solution
A method and apparatus that parse a web page file into a tag tree, perform paragraph division, classify text content based on tag attributes, and extract questions and answers using logical block division and regular expressions to identify short title structures and candidate questions and answers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional search engines return lists of ordered web pages, then users can find related information, but users must spend time searching through entire web pages to find answers
Solution Approach 1:
The patent extracts questions and answers from web page content and presents them directly to users, rather than requiring users to search through entire web pages. The system identifies and extracts QA pairs from crawled web pages, then displays them as direct search results, eliminating the time users would spend manually searching through page content.
Solution Approach 2:
The system performs preliminary extraction of questions and answers from web pages during the crawling and indexing phase. By pre-processing web page content to identify QA pairs before user queries arrive, the system prepares structured information in advance, enabling rapid retrieval and direct presentation of answers without requiring users to search through raw web page content.
2Quantity of substance
If search engines index entire web page content, then comprehensive information is available, but the quantity of content requiring processing increases significantly
Solution Approach 1:
The patent segments web page content into structured elements using HTML tag tree parsing. By dividing web pages into tags, attributes, and content blocks, the system can selectively process only relevant portions (questions and answers) rather than treating entire pages as single units. This segmentation reduces the effective quantity of content requiring detailed processing while maintaining comprehensive indexing capabilities.
Solution Approach 2:
The system applies different processing qualities to different parts of web page content. Rather than uniformly processing all content with the same depth, the patent identifies specific regions (QA pairs) and applies targeted extraction techniques to those locations while using lighter processing for other areas. This local quality approach reduces overall processing requirements while maintaining high-quality extraction where needed.
3Measurement precision
If manual extraction of questions and answers is performed, then precise information can be obtained, but the process is time-consuming and inefficient
Solution Approach 1:
The patent implements automatic extraction of questions and answers using computational algorithms that process web page content without human intervention. The system uses tag tree parsing, pattern recognition, and natural language processing to automatically identify QA pairs, eliminating the need for manual extraction while maintaining precision through structured analysis of HTML content and semantic patterns.
Solution Approach 2:
The patent replaces manual mechanical extraction processes with automated computational systems. Instead of human operators manually identifying and extracting QA pairs, the system uses algorithmic processing, regular expressions, and machine learning models to automatically detect and extract questions and answers from web page content, dramatically increasing extraction speed while maintaining or improving precision through consistent application of extraction rules.
Data Source
AI summary
The present application discloses a method and apparatus for extracting information. A specific implementation of the method comprises: parsing a pre-acquired web page file into a structure of a tag tree, and recognizing, in nodes of the tag tree, at least one body node at which a web page body in the web page file is located; performing a paragraph division on a content contained in the at least one body node to generate paragraph blocks, and setting a tag attribute for each paragraph block according to an attribute of a tag associated with the each paragraph block; classifying a text content contained in the each paragraph block based on the tag attribute of the each paragraph block; and extracting information comprising a question and an answer from the text content contained in the each paragraph block based on a classification result. This implementation implements the automatic and precise extraction of information.