Search Query Expansion for Exploratory Auto-Suggestions
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Solution Overview
Problem
Traditional search engines fail to provide comprehensive search results for exploratory queries, requiring users to perform multiple searches to cover various aspects of a topic, and autosuggestions are limited to single queries, failing to capture user intent fully.
Innovation Solution
An enhanced search system that identifies user intent through deep learning models, generates associated queries and headings related to a topic, and categorizes them for a unified search experience, using pre-trained generative language models to suggest multiple relevant queries and headings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional keyword-based search engines are used, then search results are returned based on keyword matching, but comprehensive coverage of exploratory queries is not achieved and users must perform multiple searches
Solution Approach 1:
The system performs preliminary analysis of the user's query intent before executing the search. By using deep learning models to predict user intent and generate associated queries in advance, the system prepares a comprehensive set of search queries that cover multiple aspects of the topic simultaneously, eliminating the need for users to perform multiple separate searches.
Solution Approach 2:
The system introduces an intermediary layer between the user's simple prefix input and the search engine. This intermediary uses pre-trained generative language models to expand the prefix into multiple comprehensive search queries, automatically covering various aspects of the topic without requiring the user to manually formulate multiple search terms.
2Ease of operation
If autosuggestions are provided for single queries, then user input is improved, but full user intent for exploratory queries is not captured
Solution Approach 1:
The system transitions from single-dimension autosuggestion (one query suggestion) to multi-dimensional query expansion (multiple associated queries covering different aspects). By generating queries that explore various dimensions of the topic simultaneously, the system captures the full scope of exploratory user intent while maintaining ease of operation through automated suggestions.
3Adaptability or versatility
If multiple searches are performed to cover various aspects of a topic, then comprehensive results are obtained, but user experience becomes less immersive and more complex
Solution Approach 1:
The system merges multiple separate search operations into a single unified search process. By automatically generating and executing multiple associated queries that cover various aspects of the topic, then consolidating and presenting the results in an organized manner with headings and categorization, the system provides comprehensive topic coverage while maintaining a simple, immersive user experience.
Data Source
AI summary
A system for providing enhanced search functionality is provided. A system may receive a prefix from a user device and identify that a user's intent is to do an exploratory query. The system may further identify a topic based on the prefix and generate one or more associated queries relating to the topic. The system may further generate one or more headings relating to the topic. The system may then provide one or more of the one or more headings and the one or more associated queries relating to the topic to a user device.