18515665. CAUSAL ANALYSIS simplified abstract (NEC Corporation)
Contents
CAUSAL ANALYSIS
Organization Name
Inventor(s)
CAUSAL ANALYSIS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18515665 titled 'CAUSAL ANALYSIS
Simplified Explanation
The abstract describes a method for causal analysis using observation samples of factors to determine causal relationships and execute actions based on user input.
- The method involves determining causal structures from observation samples of factors.
- The first causal structure is presented to the user for input.
- Actions are executed based on user input about the causal structure.
- The result of the actions is presented to the user.
Potential Applications
This technology could be applied in various fields such as data analysis, decision-making processes, and predictive modeling.
Problems Solved
This technology helps in identifying causal relationships among factors and allows for the execution of actions based on these relationships, leading to more informed decision-making.
Benefits
The benefits of this technology include improved understanding of causal relationships, enhanced decision-making processes, and the ability to predict outcomes based on observed factors.
Potential Commercial Applications
The potential commercial applications of this technology include data analytics software, decision support systems, and predictive modeling tools.
Unanswered Questions
== How does this technology handle complex causal relationships among multiple factors? This article does not delve into the specifics of how the method deals with intricate causal structures involving numerous factors.
== What are the limitations of this technology in real-world applications? The article does not address the potential constraints or challenges that may arise when implementing this method in practical scenarios.
Original Abstract Submitted
Embodiments of the present disclosure relate to methods, systems and computer program products for causal analysis. In some embodiments, there is provided a computer-implemented method. The method comprises determining, from observation samples of a plurality of factors, a first causal structure indicating a first causal relationship among the plurality of factors, each observation sample including a set of observation values of the plurality of factors; presenting the first causal structure to a user; in response to receiving at least one user input about the first causal structure from the user, executing actions associated with the at least one user input based on the first causal structure; and presenting a result of the execution of the actions to the user. In other embodiments, another method, systems and computer program products are provided.
