Refining Structured Data Indexes via Contextual Annotation
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Solution Overview
Problem
Existing structured data search systems face challenges in effectively indexing and retrieving relevant structured data from web pages due to the diversity of content generation on the Internet, leading to less relevant search results when structured data is not appropriately indexed.
Innovation Solution
The method involves associating additional content with structured data, such as tables, to improve indexing by parsing and identifying relevant content outside the table tags, including page titles, headings, URLs, surrounding text, and click logs, and annotating tables with this additional content to generate more comprehensive and relevant search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If structured data is indexed using only table content, then indexing simplicity is maintained, but search result relevance deteriorates due to lack of contextual information
Solution Approach 1:
The indexing process is segmented into multiple components: table content extraction, surrounding text identification, page metadata collection, and contextual information association. Each component handles a specific aspect of the indexing task, making the overall complex process manageable and systematic while improving search result relevance through comprehensive data collection
Solution Approach 2:
The system performs preliminary actions by pre-identifying and storing contextual information (surrounding text, page titles, headings, URLs) alongside the structured data during the crawling phase. This preliminary preparation ensures that when search queries are executed, relevant contextual information is already available, eliminating the need for complex real-time analysis and improving both relevance and efficiency
2Reliability
If additional content is associated with structured data, then search result relevance is improved, but processing time increases due to more data to analyze
Solution Approach 1:
Contextual information such as surrounding text, page titles, headings, and URLs is identified and associated with structured data during the initial crawling and indexing phase. This preliminary action ensures that when search queries are executed, the relevant contextual information is already prepared and stored, eliminating the need for time-consuming real-time analysis and thus reducing processing time while maintaining high search result relevance
Solution Approach 2:
The patent merges multiple data sources (table content, surrounding text, page metadata) into a unified index structure. By combining these elements during indexing rather than processing them separately during search, the system reduces overall processing time while improving search result relevance through comprehensive data integration
Data Source
AI summary
The present invention extends to methods, systems, and computer program products for refining structured data indexes. Aspects of the invention include associating structured data, such as, for example, tables, with additional content. Additional content can include content outside the and tags of a web table. Indexes for structured data (e.g., table indexes) can be refined based on the additional content to improve the relevance of providing parts of the structured data (e.g., parts of the table) in search results.