Salesforce, inc. (20240338378). Semantic Search Interface for Data Repositories simplified abstract
Contents
Semantic Search Interface for Data Repositories
Organization Name
Inventor(s)
Vidya Raghavan Setlur of Portola Valley CA (US)
Arjun Srinivasan of Seattle WA (US)
Andriy Kanyuka of Vancouver (CA)
Semantic Search Interface for Data Repositories - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338378 titled 'Semantic Search Interface for Data Repositories
Simplified Explanation:
The patent application describes a method for visual analysis of datasets using natural language search queries. The system parses search tokens to determine if the query contains analytic intents and matches fields in data sources for generating visualization responses.
- The method provides visual analysis of datasets
- Natural language search queries are used to direct to data repositories
- Search tokens are parsed to identify analytic intents
- Semantic search is used to match search tokens with fields in data sources
- Visualization responses are generated when search tokens match fields and analytic intents are present
Key Features and Innovation:
- Utilizes natural language search queries for visual analysis of datasets
- Semantic search for matching search tokens with data sources
- Generates visualization responses based on matched fields and analytic intents
Potential Applications:
- Data analysis in various industries such as finance, healthcare, and marketing
- Business intelligence tools for decision-making processes
- Research and development for data exploration and insights
Problems Solved:
- Simplifies the process of visual analysis of datasets
- Enhances the efficiency of data exploration and interpretation
- Improves the user experience in accessing and analyzing data
Benefits:
- Faster and more accurate data analysis
- Enhanced visualization of complex datasets
- Improved decision-making based on data insights
Commercial Applications:
The technology can be used in business intelligence software, data visualization tools, and analytics platforms to streamline data analysis processes and improve decision-making capabilities in various industries.
Questions about Visual Analysis of Datasets:
1. How does the system determine if a natural language search query contains analytic intents? 2. What are the potential challenges in implementing semantic search for matching search tokens with data sources?
Original Abstract Submitted
a method provides visual analysis of datasets. a system receives a natural language search query that is directed to data repositories including data sources and data visualizations. the system parses search tokens to determine if the natural language search query contains analytic intents. the system also determines if the search tokens match fields in one or more data sources, using a semantic search. when (i) the search tokens match fields in the one or more data sources and (ii) the natural language search query contains analytic intents, the system generates and displays visualization responses. when (i) the search tokens do not match fields in the data sources or (ii) the natural language search query does not contain the analytic intents, the system displays pre-authored content from the data visualizations.
