Search Query Processing System Using Sentiment-Based Ranking
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Solution Overview
Problem
Conventional search systems fail to identify sufficiently relevant data in response to a search query and often do not accurately reflect the relevancy of search results to the query.
Innovation Solution
A navigation system that uses GPS or Wi-Fi to navigate users within structures and on roadways, capable of generating navigation routes from a user's current location to a specified item location within a structure, and transmitting these routes to user devices along with maps and turn-by-turn instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search systems are used to process search queries, then the search process is simple and fast, but the relevance and accuracy of search results are insufficient
Solution Approach 1:
The search system is segmented into multiple independent modules: query processing module, search module, ranking module, and result presentation module. Each module handles a specific aspect of search processing, allowing for specialized optimization while maintaining overall system functionality. This segmentation enables improved search result relevance through dedicated ranking algorithms without overwhelming system complexity.
Solution Approach 2:
An intermediary ranking module is introduced between the search module and result presentation module. This intermediary processes search results through multiple ranking criteria including relevance scoring, popularity metrics, and user preferences, thereby improving search result relevance without requiring complete system redesign.
2Reliability
If multiple sources of position data are utilized to enhance positioning accuracy, then positioning reliability is improved, but system complexity and data processing requirements increase
Solution Approach 1:
Multiple positioning data sources (GPS satellite signals, Wi-Fi access point triangulation, cellular tower location) are merged into a unified positioning system. The system combines these diverse data sources through sensor fusion algorithms to achieve enhanced positioning reliability and accuracy, particularly in environments where individual sources may be unreliable.
Solution Approach 2:
The positioning system implements continuous feedback mechanisms where position data from multiple sources is constantly monitored, cross-validated, and adjusted. The system provides feedback loops that compare expected position with actual position measurements, enabling real-time correction of positioning errors and improvement of overall positioning reliability.
Data Source
AI summary
Systems and methods for enhanced search query systems and methods are described. A large language model is used to extract metadata from a plurality of items of content related to respective items. Sentiment analysis is utilized to determine user sentiment regarding respective item attributes and/or items. Values are associated with a given item's attributes using the determined user sentiment. A user query is received over a network. A search is performed for items satisfying the query using the extracted metadata. Items identified in the search may be ranked using respective values, the values based at least in part on the determined user sentiment, assigned to respective attributes associated with the items. The ranked search results may be transmitted to the user device, the ranked search results corresponding at least in part to the item and/or item attribute rankings, wherein the ranked search results are displayed via the user device.