17948652. MESSAGE QUERY SERVICE AND MESSAGE GENERATION FOR A SOCIAL NETWORK simplified abstract (SAP SE)
Contents
- 1 MESSAGE QUERY SERVICE AND MESSAGE GENERATION FOR A SOCIAL NETWORK
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MESSAGE QUERY SERVICE AND MESSAGE GENERATION FOR A SOCIAL NETWORK - 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
MESSAGE QUERY SERVICE AND MESSAGE GENERATION FOR A SOCIAL NETWORK
Organization Name
Inventor(s)
Sai Hareesh Anamandra of Bengaluru (IN)
Kavitha Krishnan of Bangalore (IN)
Rohit Jalagadugula of Visakhapatnam (IN)
Akash Srivastava of Lucknow (IN)
MESSAGE QUERY SERVICE AND MESSAGE GENERATION FOR A SOCIAL NETWORK - A simplified explanation of the abstract
This abstract first appeared for US patent application 17948652 titled 'MESSAGE QUERY SERVICE AND MESSAGE GENERATION FOR A SOCIAL NETWORK
Simplified Explanation
The method described in the abstract involves receiving a message query from an entity identifier in a social network, generating query parameters, generating queries for a semantic graph, obtaining query results, determining message context, and retrieving messages from a repository for presentation to the entity identifier.
- Receiving message query from entity identifier in social network
- Generating query parameters based on message query
- Generating queries for semantic graph of social network
- Obtaining query results from semantic graph
- Determining message context of entity identifier
- Retrieving messages from repository based on message context
Potential Applications
This technology could be applied in social media platforms, online communities, and communication networks to enhance message delivery and content personalization.
Problems Solved
This technology solves the problem of efficiently retrieving and presenting relevant messages to users in a social network based on their context and preferences.
Benefits
The benefits of this technology include improved user experience, increased engagement, and more personalized content delivery in social networks.
Potential Commercial Applications
One potential commercial application of this technology is in social media marketing tools that can analyze user interactions and preferences to deliver targeted messages effectively.
Possible Prior Art
One possible prior art for this technology could be related to data mining algorithms used in social networks to analyze user behavior and preferences.
Unanswered Questions
How does this technology handle user privacy and data security in social networks?
This technology does not address the specific methods or mechanisms used to ensure user privacy and data security in social networks.
What are the scalability limitations of this technology when applied to large social networks with millions of users?
The abstract does not provide information on the scalability limitations of this technology when dealing with a large volume of data and users in social networks.
Original Abstract Submitted
A method includes receiving a message query from an entity identifier participating in a social network. The message query specifies one or more entities, one or more requirements, and one or more constraints. A set of message query parameters is generated based on the message query. A set of queries for a semantic graph of the social network is generated based on the set of message query parameters. The set of queries is applied to the semantic graph to obtain a set of query results. A message context of the entity identifier is determined based on the set of query results and the set of message query parameters. A set of messages from a message repository is determined based on the message context. The set of messages can be presented on a client computer associated with the entity identifier.
