Computing Product Identification Through Component-Based Queries
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Solution Overview
Problem
Existing information handling systems lack an efficient method to identify and analyze computing products from search queries that do not explicitly refer to specific products, hindering accurate identification and comparison of computing components and configurations.
Innovation Solution
A system and method that analyzes search queries to identify computing components from word strings, generates search terms based on combinations of these components, and uses an index to identify computing products, incorporating dynamic web crawling, computer vision, and natural language processing to gather and standardize data for comprehensive product analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If search queries are analyzed to identify computing components from word strings, then the ability to identify computing products is improved, but the complexity of the search analysis system increases
Solution Approach 1:
The search query analysis process is segmented into distinct stages: word string analysis, computing component identification, search term generation, and product identification. Each stage processes specific information independently, making the complex system more manageable and maintainable while improving overall accuracy.
Solution Approach 2:
The system performs preliminary analysis of the word string to determine whether it refers to a particular computing product before proceeding to more complex analysis. This preliminary action filters out simple queries early, reducing the complexity burden on subsequent processing stages.
2Adaptability or versatility
If multiple search terms are generated from computing components, then the coverage of computing products is improved, but the processing time increases
Solution Approach 1:
The system generates multiple search terms based on different combinations of computing components, potentially creating more search queries than strictly necessary. This excessive action ensures comprehensive product coverage and reduces the risk of missing relevant products, with the trade-off being acceptable given the structured approach to generation.
Solution Approach 2:
The search term generation process is dynamic, adapting to the identified computing components and their relationships. The system adjusts the number and type of search terms generated based on the specific components found, optimizing the balance between coverage and processing time for each query scenario.
3Reliability
If data is standardized from multiple sources, then the quality of product analysis is improved, but the data processing complexity increases
Solution Approach 1:
The system transforms data from multiple sources by changing parameters such as data formats, structures, and representations to a standardized form. This parameter transformation enables consistent analysis while maintaining the richness and reliability of the original multi-source data.
Solution Approach 2:
The data standardization process creates a universal representation that can be used across multiple analysis functions and product types. This universal data structure simplifies processing complexity by providing a common foundation for various analysis operations.
Data Source
AI summary
Method of identifying computing products from a search query, including receiving a search query including a word string; analyzing the search query to determine that the word string does not refer to a particular computing product; in response to determining that the word string of the search query does not refer to a particular computing product, identifying words of the word string; identifying, from an index, a plurality of computing components based on the words of the word string; generating a plurality of search terms, each search term based on a differing combination of one or more computing components of the plurality of computing components and a word of the words of the word string; and identifying, from the index, one or more computing products based on the plurality of search terms