Search Query Expansion Using Contextual Synonym Ranking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data searching and language translation methods often lead to incorrect synonym expansion, resulting in irrelevant search results due to isolated contextual decisions, which hinders productivity and accuracy in finding relevant information across languages.
Innovation Solution
A system and method that expand search queries with synonyms and rank results based on contextual relevance, utilizing user-specific data, browsing history, and statistical analysis to ensure that valid synonyms are not excluded, and correct spelling errors, thereby providing a broader and more accurate set of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If synonym expansion is performed to broaden search results, then the quantity of search results increases, but the relevance and accuracy of search results deteriorates due to inclusion of contextually irrelevant synonyms
Solution Approach 1:
The system performs preliminary contextual analysis of the original search query before conducting synonym expansion. By pre-establishing the contextual framework and relevance criteria based on the original query's semantics, the system ensures that subsequent synonym expansions are filtered through this pre-defined contextual lens, preventing inclusion of irrelevant synonyms while maintaining comprehensive result sets
Solution Approach 2:
The system applies different quality standards to different parts of the search process: the original query receives strict contextual analysis, while expanded synonyms are evaluated against this established contextual framework. This localized quality control ensures that each synonym is assessed for contextual relevance rather than applying a uniform filter, maintaining both quantity and relevance of results
2Reliability
If contextual filtering is applied to remove irrelevant synonyms, then the relevance of search results improves, but the quantity of search results decreases and may exclude valid synonyms
Solution Approach 1:
The system employs dynamic contextual analysis that adapts to each specific query rather than applying static filtering rules. The contextual framework is constructed dynamically based on the semantics, syntax, and domain of the original query, allowing the system to flexibly determine relevance for each synonym in context. This dynamic approach prevents premature exclusion of valid synonyms that might appear irrelevant under rigid filtering criteria
Solution Approach 2:
The system changes the parameters of synonym evaluation from simple keyword matching to multi-dimensional contextual assessment including semantic similarity, domain relevance, and query intent alignment. By adjusting these evaluation parameters dynamically based on the original query characteristics, the system maintains sensitivity to valid synonyms while filtering out truly irrelevant ones, preserving both quantity and quality of results
3Speed
If isolated contextual decisions are made for each synonym, then the processing speed increases, but the accuracy of synonym selection deteriorates due to inability to recover from incorrect decisions
Solution Approach 1:
The system implements feedback mechanisms where the contextual framework established from the original query continuously informs synonym evaluation decisions. Each synonym is assessed against this feedback-rich contextual model, allowing the system to maintain processing speed while improving accuracy through iterative contextual validation rather than isolated binary decisions
Solution Approach 2:
By pre-establishing a comprehensive contextual framework before synonym expansion, the system creates a reference model that guides all subsequent synonym evaluations. This preliminary action enables rapid accurate decision-making during synonym processing, as each synonym can be quickly assessed against the pre-computed contextual criteria rather than requiring complex real-time analysis
4Measurement precision
If comprehensive contextual information is collected from multiple sources, then the accuracy of search result ranking improves, but the device complexity and data processing requirements increase
Solution Approach 1:
The system segments the contextual information collection into distinct modular components: query analysis module, user profile module, browsing history module, and domain knowledge module. Each module independently processes specific types of contextual data and contributes to the overall contextual framework. This segmentation reduces system complexity by creating manageable, independent processing units while maintaining comprehensive contextual coverage
Data Source
AI summary
The invention relates to data searching and translation. In particular, the invention relates to searching documents from the Internet or databases. Even further, the invention also relates to translating words in documents, WebPages, images or speech from one language to the next. A computer implemented method comprising at least one computer in accordance with the invention is characterized by the following steps: receiving a search query including at least one search term, deriving at least one synonym for at least one search term, expanding the received search query with the at least one synonym, searching at least one document using the expanded search query, retrieving the search results obtained with the expanded query, ranking the said search results based on context of occurrence of at least one search term. The best mode of the invention is considered to be an Internet search engine that delivers better search results.