Context-Inferred Search Query Generation and Result Sorting
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Solution Overview
Problem
Current search utilities often return overwhelming amounts of data due to users entering single search terms, as complex queries are difficult for average users to construct, leading to inaccurate results based on single properties like dates or keywords, which may not reflect the user's actual interests.
Innovation Solution
A method that analyzes a user's contextual settings, such as events and personal information, to dynamically generate search queries, refine search results using various ranking functions, and display them in order of importance, incorporating past, present, and future events to prioritize relevant documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single search term is entered into the search utility, then the search is easy to perform, but the search results return an overwhelming amount of data
Solution Approach 1:
The system performs preliminary actions by automatically analyzing user events and context before the search is executed. It pre-generates multiple related search terms and queries based on the user's calendar events, contacts, and other contextual information, so that when the user enters a simple search term, the system has already prepared refined queries to filter and prioritize results effectively.
2Measurement precision
If complex search queries are constructed, then the search results are more accurate, but it is difficult for average users to construct them
Solution Approach 1:
The system enables self-service by automatically generating complex search queries without user intervention. It analyzes the user's contextual information (calendar events, contacts, previous searches) and autonomously constructs sophisticated search queries with multiple criteria, filters, and ranking parameters, allowing average users to benefit from complex query capabilities without needing to understand query construction.
Solution Approach 2:
The system acts as an intermediary between the user's simple search intent and the complex search engine requirements. It translates the user's basic search term into multiple refined queries by incorporating contextual information from events, contacts, and other data sources, effectively mediating between simple user input and complex search processing without requiring the user to directly construct complex queries.
3Ease of manufacture
If search results are sorted based on a single property, then the sorting is simple to implement, but it does not accurately reflect user interests
Solution Approach 1:
The system dynamically changes multiple sorting parameters based on contextual analysis. Instead of using a single static sorting property, it adjusts multiple parameters including event importance, temporal proximity, relevance to user interests, and derivative term matching. These parameter changes are automatically determined by analyzing the user's calendar events, contacts, and search history, allowing the system to adapt the sorting criteria to accurately reflect user interests for each specific search context.
Data Source
AI summary
A method of generating a context-inferenced search query and of sorting a result of the query is described. The method includes analyzing an event associated with the user to determine a contextual setting, dynamically generating a search query based on the contextual setting, and searching at least one information source using the search query to generate a search result. Additionally, the method includes calculating an importance value for each item of the search result, sorting the items of the search result according the importance value, and displaying the sorted search result to the user.