Conversational Route Ranking for Complex User Preferences
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Solution Overview
Problem
Existing map search engines fail to optimize routes based on complex user preferences and limited natural language understanding, leading to inaccurate query execution and user experience, and struggle with ambiguous queries.
Innovation Solution
A routing engine that treats each route candidate as a richly annotated document, using a language model to rank routes based on user preferences and contextual data, including historical conversations, to generate optimized navigation directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If routing algorithms optimize only for fastest time or shortest distance, then routing efficiency is improved, but ability to satisfy complex user preferences deteriorates
Solution Approach 1:
The patent transforms the routing problem by changing the parameter space from simple cost functions (time, distance) to rich text descriptions of route characteristics. Each route is annotated with textual attributes describing its features, enabling the system to evaluate routes based on user preferences expressed in natural language while maintaining efficient routing calculations.
Solution Approach 2:
The patent introduces an intermediary retrieval system that acts as a bridge between user preferences and routing algorithms. This retrieval component processes user queries, matches them against annotated route characteristics, and selects appropriate routes, thereby enabling complex preference satisfaction without directly modifying the core routing efficiency mechanisms.
2Device complexity
If map search engine uses simple cost model for route ranking, then computational complexity is reduced, but query execution accuracy deteriorates
Solution Approach 1:
The patent segments the routing system into distinct functional components: a retrieval component that handles query understanding and route selection based on user preferences, and a ranking component that performs detailed evaluation. This segmentation allows each component to specialize, maintaining computational efficiency while improving overall query execution accuracy through focused processing.
3Speed
If routing system processes only explicit query parameters, then processing speed is improved, but understanding of user intent deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-annotating route candidates with rich text descriptions of their characteristics before query processing. This preparation work is done in advance, so when user queries arrive, the system can quickly retrieve and match routes based on these pre-computed annotations without performing complex real-time analysis, thus maintaining speed while improving intent understanding.
Data Source
AI summary
Various embodiments discussed herein relate to route optimization and query understanding for route and/or direction queries with complex user preferences. Each route candidate, for example, is treated as a richly annotated document. The routing engine, in addition to performing route optimization, acts as a retriever and ranker of route documents according to user intent. Various embodiments rank routes not just based on a simple cost model, but based on many more or alternative factors according to user preferences, user intent, and/or contextual data.