Dynamic Stopword Removal in Search Query Processing
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Solution Overview
Problem
Existing search systems face challenges in accurately identifying and removing stopwords from search queries, as some words can be meaningless in one context but meaningful in another, leading to inaccurate query interpretation and search results.
Innovation Solution
A method and system that dynamically identify potential stopwords by splitting search queries into location and subject portions based on predefined query patterns, determining the association of stopwords with these portions, and modifying the query accordingly to improve search result relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stopwords are removed from search queries using a predefined list, then query interpretation accuracy is improved, but words that are meaningful in specific contexts may be incorrectly removed
Solution Approach 1:
The query is divided into location portion and subject portion based on query patterns. Stopwords are selectively removed from only the location portion while being retained in the subject portion, allowing context-dependent stopword handling that preserves meaningful words while removing irrelevant ones.
Solution Approach 2:
Different parts of the query receive different stopword treatment based on their semantic role. The location portion undergoes stopword removal while the subject portion preserves stopwords that may be contextually significant, applying local quality differentiation to resolve the contradiction.
2Loss of information
If all words in a query are retained, then contextually meaningful words are preserved, but query processing efficiency and result relevance deteriorate
Solution Approach 1:
The query is segmented into location and subject portions, enabling selective stopword removal only from the location portion. This maintains processing efficiency by removing irrelevant words while preserving contextually meaningful words in the subject portion.
Solution Approach 2:
The stopword removal parameter is dynamically adjusted based on query pattern matching. When a query matches a known pattern, stopwords are removed from the location portion; otherwise, the original query is preserved, optimizing processing efficiency based on query characteristics.
3Stability of the object's composition
If stopword removal is applied uniformly to all queries, then processing consistency is improved, but context-specific accuracy deteriorates
Solution Approach 1:
The stopword removal process is made dynamic through query pattern matching. The system adapts its stopword handling based on whether the query matches known patterns, transitioning from uniform static removal to context-aware dynamic processing that maintains both consistency and accuracy.
Solution Approach 2:
Different stopword removal strategies are applied to different query types based on pattern matching. Location-based queries receive aggressive stopword removal while other query types retain stopwords, providing locally optimized processing for each context.
Data Source
AI summary
Dynamic identification and removal of potential stopwords from a search query is provided. A search query comprising plural terms is received. A possible stopword among the terms that appears in a predefined list of possible stopwords is identified. Query splits are determined based on one or more query patterns, each query split comprising a location portion using a first subset of the plural terms and a subject portion using a second subset. Either the location portion or the subject portion of the query splits is modified, by removing the possible stopword from that portion. The search engine is queried with the location portion and the subject portion for each of the query splits, and scored search results are obtained for each of the query splits. The search results returned for at least one of the query splits is selected to return as a response to the search query.