Categorized Search Completion Ordering
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Solution Overview
Problem
Current search engines often provide confusing suggestions for partial search terms, requiring users to enter additional characters to focus results, leading to user burden and unclear search intentions.
Innovation Solution
A method that predicts categorized completions for partial search terms by using a selection ratio-based approach, grouping and ordering suggestions by category, and maintaining an alias mapping to improve search accuracy and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the search engine provides general suggestions for partial search terms, then the suggestions are easy to generate, but the suggestions become confusing and unclear in user intent
Solution Approach 1:
The patent segments search suggestions by categorizing them into different types (e.g., destinations, hotels, airports, car rentals). Each category is treated as a separate group with its own ranking and presentation, allowing users to clearly understand the type of each suggestion without confusion
Solution Approach 2:
The patent introduces category labels as intermediary elements between the partial search term and the suggestions. These category labels act as mediators that clarify the meaning and intent behind each suggestion, helping users understand whether a suggestion refers to a destination, hotel, airport, or other entity type
2Loss of information
If the search engine provides detailed categorized suggestions, then the clarity of user intent improves, but the complexity of the suggestion system increases
Solution Approach 1:
The system segments suggestions into predefined categories with fixed ranking orders. This segmentation simplifies the complexity by organizing diverse suggestions into manageable groups with established hierarchies, making the system easier to maintain and update
Solution Approach 2:
The patent implements a universal categorization framework that handles multiple types of search entities (destinations, hotels, airports, car rentals) using the same structure and processes. This multi-functionality reduces complexity by applying a single unified approach across different suggestion types
3Measurement precision
If the search engine requires users to enter extra characters to focus results, then the search precision improves, but the user burden increases
Solution Approach 1:
The patent performs preliminary categorization and ranking of suggestions before presenting them to users. By pre-organizing suggestions by category and relevance, the system provides precise results immediately after the user enters a partial search term, eliminating the need for users to type additional characters to refine results
Data Source
AI summary
In an embodiment, a method comprises receiving, from a client computer, a first request comprising a partial search term for an item, wherein the partial search term comprises one or more characters; selecting a first plurality of predicted completions of the partial search term based, at least in part, on the partial search term, wherein each predicted completion in the first plurality of predicted completions is associated with a category of a set of categories; determining an order of each category in the set of categories; ordering the first plurality of predicted completions based, at least in part, on a position, in the order, of each category that is associated with each predicted completion in the first plurality of predicted completions; sending the first plurality of predicted completions to the client computer.