Search Engine Click-Escape Model for Semantic Relevance
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Solution Overview
Problem
Existing search engines face the issue of 'escape' results, where irrelevant content is returned due to partial text matching, leading to user dissatisfaction, as they fail to accurately match user queries with the intended search results.
Innovation Solution
A search engine method that employs a click-escape model to determine semantic relatedness between user queries and search results by using an escape dictionary and a non-escape dictionary, which are constructed based on click-to-display ratios and term alignment, to sort results effectively, thereby reducing irrelevant matches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If text related matching method is used to return search results, then the search engine can process queries efficiently, but irrelevant content is returned leading to escape results that do not match user intent
Solution Approach 1:
The patent pre-processes search results by extracting entities, attributes, and values, and pre-calculates matching scores for query-template-result triplets before the actual search query is submitted. This preliminary structuring of data enables faster retrieval and more accurate matching during the search execution phase, resolving the contradiction between processing efficiency and result relevance
Solution Approach 2:
The patent transforms the search matching process from simple text comparison to a multi-parameter evaluation system that considers entity types, attribute values, and semantic relationships. By changing the matching parameters from basic text overlap to structured entity-attribute-value matching, the system achieves both efficient processing and high relevance accuracy
2Device complexity
If existing text matching schemes such as common part ratio or BM25 are used, then the matching process is simple and fast, but they cannot address the escape issue where searched results do not match user query intent
Solution Approach 1:
The patent introduces an intermediary layer of entity-attribute-value structures between the raw search results and the matching process. This intermediary representation acts as a mediator that bridges simple text matching and complex semantic understanding, enabling accurate detection of escape results while maintaining computational efficiency
Solution Approach 2:
The patent segments search results into discrete entities with specific attributes and values, rather than treating them as unstructured text. This segmentation enables the system to evaluate each component separately and combine the results, achieving high accuracy in detecting whether results match user intent without requiring overly complex matching algorithms
Data Source
AI summary
Search engine method includes: receiving a user query request input; searching candidate results matching with the query request; determining a semantic relatedness between the query request and each candidate result based on a click-escape model; sorting the candidate results according to the semantic relativity. The click-escape model has an escape dictionary, a non-escape dictionary, or a combination thereof. Sorting candidate results of a search in accordance with a semantic relatedness can enhance the sorting effect of the searched results, avoid searched results which do not match the user's query appearing in the forefront of the searched result list, and guarantee a good user experience.