18531830. SYSTEMS AND METHODS FOR RECOMMENDING COLLABORATIVE CONTENT simplified abstract (ROVI GUIDES, INC.)
SYSTEMS AND METHODS FOR RECOMMENDING COLLABORATIVE CONTENT
Organization Name
Inventor(s)
Siddhartha Pande of Bengaluru (IN)
Deviprasad Punja of Bangalore (IN)
Madhusudhan Srinivasan of Bangalore (IN)
SYSTEMS AND METHODS FOR RECOMMENDING COLLABORATIVE CONTENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 18531830 titled 'SYSTEMS AND METHODS FOR RECOMMENDING COLLABORATIVE CONTENT
The system described in the patent application generates recommendations for content to be used in collaboration, based on reviews from various sources. The system filters these reviews to create a refined set of reviews, taking into account the text of the reviews, profile information, and reference information. A recommendation metric is then calculated for the content item, considering specific recommendation criteria. This metric determines whether the content item is recommended as base content for collaborative work. The system generates a recommendation indicator based on this metric, which can be displayed or stored for future use.
- The system generates content recommendations for collaboration based on reviews from multiple sources.
- Reviews are filtered to create a refined set using text, profile information, and reference data.
- A recommendation metric is calculated for each content item based on specific criteria.
- The metric determines if the content item is suitable as base content for collaboration.
- A recommendation indicator is generated and can be displayed or stored as needed.
Potential Applications: - Content creation platforms - Collaborative work environments - E-learning platforms
Problems Solved: - Identifying relevant content for collaboration - Streamlining the content selection process - Improving the quality of collaborative work
Benefits: - Enhanced collaboration efficiency - Access to high-quality content - Improved decision-making based on recommendations
Commercial Applications: Title: Enhanced Content Recommendation System for Collaboration This technology can be utilized in various industries such as content creation platforms, e-learning environments, and collaborative workspaces to streamline the process of selecting and using relevant content for collaborative projects. By providing tailored recommendations based on reviews and specific criteria, this system can significantly improve the efficiency and quality of collaborative work.
Questions about the Enhanced Content Recommendation System for Collaboration: 1. How does the system filter reviews to generate a refined set for content recommendations? 2. What are the key factors considered in calculating the recommendation metric for content items?
Original Abstract Submitted
The system generates a recommendation of content for use in collaboration, allowing relevant content to be used as base content. The system identifies a content item, and retrieves reviews for the content item from one or more sources or forums. The system filters the reviews to generate a reduced set of reviews based on text of the respective reviews, profile information associated with the reviews, and reference information. A recommendation metric is determined for the content item based on the reduced set of reviews and based on the one or more recommendation criteria. The recommendation criteria specify which aspects of the content impact recommendation, and how those aspects impact recommendation. The recommendation metric indicates whether the content item is recommended as base content, to be used for generating collaborative content. The system generates a recommendation indicator indicative of the recommendation metric, and outputs the indicator for display, storage, or both.
