Inferred Query Generation via Template Infix Substitution
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Solution Overview
Problem
Existing search engines often provide outdated query suggestions as new information becomes available, failing to assist users seeking information outside the coverage of past queries, leading to a poor user experience.
Innovation Solution
A method that determines prefixes, infixes, and postfixes of past queries, groups them based on matching patterns, creates query templates, and infers new queries by adding similar infixes to these templates, ensuring new information requests are represented as query suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If query suggestions are taken from past user queries, then the system can provide query suggestions based on historical data, but the information coverage becomes stale and out-of-date as new documents are made available
Solution Approach 1:
The system performs preliminary action by analyzing past queries and pre-computing query templates with placeholders before users submit new queries. This allows the system to have query suggestions ready in advance that can accommodate new information while maintaining structural reliability from historical patterns.
Solution Approach 2:
The system makes query suggestions dynamic by using templates with placeholders that can be filled with new terms from current documents. Instead of static past queries, the templates adapt to new information while maintaining the reliable structure of historically validated query patterns.
2Adaptability or versatility
If the system uses past user queries for suggestions, then it can leverage historical search behavior, but it fails to assist users seeking information outside the coverage of past queries
Solution Approach 1:
The system segments queries into templates with placeholders and specific terms. This segmentation allows the system to separate the reliable structural pattern from the specific content, enabling it to maintain historical reliability while adapting to new information topics that users may search for.
Solution Approach 2:
The system adds another dimension to query suggestions by creating templates that exist in a space between specific past queries and completely new queries. The templates with placeholders create an intermediate representation that can be filled with new terms, expanding coverage while maintaining operational ease.
3Adaptability or versatility
If the system creates query templates from grouped queries, then it can generalize patterns from historical data, but it requires complex processing to identify groups and create templates
Solution Approach 1:
The system uses copying by creating template representations that replicate the structural patterns from grouped queries. Instead of storing and processing all original queries, it copies the essential pattern structure into templates with placeholders, reducing processing complexity while maintaining generalization capability.
Solution Approach 2:
The system applies parameter changes by transforming specific query terms into placeholder parameters within templates. This parameterization reduces the complexity of storing and processing individual queries while preserving the generalizable patterns across query groups.
Data Source
AI summary
Technology is described herein for creating new, inferred queries that are suitable for use as query suggestions. The technology includes mapping different past queries that represent different information requests, but that share a number of terms having the same or similar form. An inferred query is created by replacing unshared terms in one mapped query with the unshared terms in another mapped query, based on the similarity between the unshared terms in the two mapped queries. The inferred query thus represents a new information request that is derived from the information requests of the past queries used to form it. The inferred query can then be provided as a query suggestion, which increases the likelihood of providing query suggestions that will assist users in finding the information they seek. In doing so, meaningful query suggestions can be provided to users seeking information outside the coverage of the past queries.