Document Link Relation Indicator Analysis for Search Relevance
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Solution Overview
Problem
Existing web search technologies fail to efficiently identify and present related documents, such as translations of each other, leading to irrelevant search results based on language or geographic region preferences.
Innovation Solution
A method that identifies relation indicators in links between documents, such as language names or geographic region images, and determines document similarity through translation and update frequency comparison, to present relevant search results based on user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If web search technologies present multiple language versions of documents, then information completeness is improved, but search result relevance deteriorates due to language preferences
Solution Approach 1:
The system applies local quality by detecting the user's language preference and selectively presenting document versions in the appropriate language. Instead of uniformly presenting all language versions to all users, the search results are customized locally based on each user's language settings, thereby maintaining both information completeness and search result relevance.
Solution Approach 2:
The system uses an intermediary mechanism (language detection and relation indicator analysis) to mediate between the user's language preference and the available document versions. This intermediary layer analyzes links between documents to identify language relationships and automatically selects the most appropriate version to present, resolving the contradiction without requiring manual user selection.
2Measurement precision
If web search technologies identify related documents through translation comparison, then search result accuracy is improved, but processing time increases
Solution Approach 1:
The system applies preliminary action by pre-identifying and storing relation indicators in document links during document crawling and indexing. Instead of performing full translation comparisons at search time, the system has already analyzed and stored language relationship information in advance, enabling rapid retrieval and comparison during actual search operations, thus reducing processing time while maintaining accuracy.
Solution Approach 2:
The system uses partial action by performing selective translation comparison only for documents that have identified relation indicators suggesting they may be translations of each other. Rather than comparing all documents, the system focuses computational resources on a subset of potentially related documents, reducing overall processing time while maintaining search result accuracy for translation-related queries.
Data Source
AI summary
A device may identify, in a first document, a reference to a second document, the second document being different than the first document; identify that the reference to the second document is associated with a relation indicator; determine, based on identifying that the reference to the second document includes a relation indicator, that content of the second document is related to content of the first document; and process the second document based on determining that content of the second document is related to content of the first document.