Automated Search Query Redirection via Embedded Relevance Links
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Solution Overview
Problem
Users face difficulties in obtaining focused search results for ambiguous queries, as they need to manually reformulate their searches after scanning through disparate results, requiring significant manual and cognitive effort.
Innovation Solution
An automated redirection architecture that uses a user-selectable interface to add or negate topical terms, allowing users to quickly reformulate queries through 'More/None' links, which embed new queries in search results to provide focused results based on positive or negative feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually reformulate queries by scanning search results and adding terms, then search results can be redirected toward topics of interest, but significant manual and cognitive effort is required
Solution Approach 1:
The system performs automatic query reformulation by analyzing search results and generating refined queries without requiring manual user input. The algorithm automatically identifies topical terms from result entries and constructs new queries, allowing the system to serve itself in the query refinement process.
Solution Approach 2:
The system pre-processes search results to identify and extract relevant topical terms before the user needs to reformulate the query. By analyzing result entries and preparing potential query modifications in advance, the system reduces the cognitive effort and time required for query redirection.
2Productivity
If automated algorithms select topical terms from result entries, then query reformulation efficiency is improved, but complexity of the search system increases
Solution Approach 1:
The patent replaces manual mechanical query reformulation with an automated algorithmic system. The algorithm analyzes result entries, extracts topical terms, and generates new queries automatically, substituting human cognitive processes with computational algorithms that operate more efficiently.
Solution Approach 2:
The system introduces an intermediary algorithmic layer between the search results and the user. This intermediary automatically processes result entries, identifies relevant terms, and formulates refined queries, simplifying the user's interaction while managing the complexity behind the scenes.
3Measurement precision
If users scan through disparate search results to identify topical terms, then they can redirect queries toward topics of interest, but cognitive effort and time are significantly increased
Solution Approach 1:
The system automatically analyzes search result entries to identify topical terms without requiring user scanning. The algorithm processes titles, snippets, and metadata to extract relevant terms and generate refined queries, allowing the system to perform the identification task itself.
Solution Approach 2:
The system pre-analyzes search results to identify and extract topical terms before the user needs to redirect the query. By performing this analysis in advance, the system eliminates the time-consuming scanning process while maintaining precise topic identification.
Data Source
AI summary
Redirection (“biasing”) architecture that automates the selection of topical terms in a search query, and provides a user-selectable (e.g., clickable) interface which enables the user to quickly and easily re-formulate and execute a new query using terms that return more focused search results. The redirection of search by biasing the terms (strings) can also be performed by indicating that certain results are not interesting to the user. For example, one way using an existing search engine, is to apply a search operator (e.g., a hyphen) to indicate that certain terms must not occur in the search results (negation). Accordingly, by automatically selecting topical terms to negate, constructing a query, and embedding the negation in a link with each results page result, considerable manual and cognitive effort is saved.