International business machines corporation (20240104307). SELF-CONTAINED CONVERSATIONAL EXPERIENCE PREVIEWING simplified abstract
Contents
- 1 SELF-CONTAINED CONVERSATIONAL EXPERIENCE PREVIEWING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SELF-CONTAINED CONVERSATIONAL EXPERIENCE PREVIEWING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SELF-CONTAINED CONVERSATIONAL EXPERIENCE PREVIEWING
Organization Name
international business machines corporation
Inventor(s)
Muhtar Burak Akbulut of Waban MA (US)
Pankaj Dhoolia of Ghaziabad (IN)
Dan O'connor of Milton MA (US)
Andy James Stoneberg of Clarksburg MA (US)
Venkat Raghavan Ganesh Sekar of Lowell MA (US)
SELF-CONTAINED CONVERSATIONAL EXPERIENCE PREVIEWING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104307 titled 'SELF-CONTAINED CONVERSATIONAL EXPERIENCE PREVIEWING
Simplified Explanation
The abstract describes a method for generating an experience preview of a conversation model by extracting constraints associated with conversational steps, constructing a directed graph, and populating edges with flow data denoting probabilities.
- Constraints extracted from conversation model
- Directed graph constructed with nodes representing conversational steps and edges representing possible execution paths
- Flow data denoting probabilities associated with edges
- Experience preview generated by traversing a portion of the graph
Potential Applications
This technology could be applied in various fields such as:
- Conversational AI systems
- Customer service chatbots
- Virtual assistants
Problems Solved
This technology helps in:
- Improving user experience in conversational systems
- Enhancing the efficiency of chatbots
- Providing a more personalized interaction for users
Benefits
The benefits of this technology include:
- Generating accurate experience previews
- Increasing user engagement
- Optimizing conversation flow in chatbots
Potential Commercial Applications
This technology could be commercially applied in:
- Customer service industry
- E-commerce platforms
- Healthcare chatbots
Possible Prior Art
One possible prior art for this technology could be:
- Similar methods used in natural language processing systems
Unanswered Questions
How does this technology handle complex conversation models with multiple branches and decision points?
The article does not provide details on how the technology manages complex conversation models with multiple branches and decision points. Further information on the scalability and adaptability of the method would be beneficial.
What are the potential limitations or challenges faced when implementing this technology in real-world conversational systems?
The article does not address the potential limitations or challenges that may arise when implementing this technology in real-world conversational systems. Understanding the practical implications and constraints of the method would be essential for successful deployment.
Original Abstract Submitted
a plurality of constraints associated with conversational steps implemented by a conversation model is extracted from the conversation model. using the conversational steps and the constraints, a directed graph is constructed, each node in the directed graph representing a conversational step, each directed edge in the directed graph representing a possible execution path from a first conversational step to a second conversational step. an edge in the graph is populated with flow data denoting a probability associated with the edge. by traversing a portion of the graph, an experience preview is generated, the experience preview demonstrating a user experience of a portion of the conversation model.
