Series Asset Playlists With Automatic Clustering and Clear Criteria
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Solution Overview
Problem
Existing systems require manual user intervention to create playlists for series assets, which is tedious, especially for series recorded assets or series video-on-demand (VOD) assets, and lack flexibility in selecting desired assets and identifying the basis for filtering or rearrangement.
Innovation Solution
An interactive media guidance application automatically generates playlists for series assets and groups them into clusters based on user-selected or algorithmically determined parameters, providing a user interface for selecting clustering criteria and displaying identifiers for each cluster.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual playlist creation is required, then user control over asset selection is maintained, but user convenience and time efficiency deteriorate
Solution Approach 1:
The system automatically generates playlists for series assets without requiring manual user intervention. The media guidance application autonomously identifies series assets, groups them into clusters based on predetermined criteria (such as episode order, genre, or metadata), and creates playlists automatically, allowing the system to serve itself rather than requiring continuous manual curation by the user.
Solution Approach 2:
The system performs preliminary organization of assets by pre-grouping them into clusters based on series relationships and predetermined criteria before the user needs to access them. This preliminary action eliminates the need for users to manually filter or sort through large numbers of assets when creating playlists, as the organization is already in place.
2Productivity
If filtering techniques are used to reduce playlist size, then user selection efficiency improves, but flexibility in obtaining desired assets deteriorates
Solution Approach 1:
The system segments the large collection of assets into smaller, manageable clusters based on predetermined criteria such as series relationships, episode order, or metadata attributes. This segmentation allows users to work with smaller, more relevant groups of assets rather than filtering through entire large playlists, thereby maintaining both efficiency and flexibility in asset selection.
Solution Approach 2:
The system provides dynamic playlist generation where users can adjust clustering criteria and parameters to obtain different combinations of assets based on their preferences. The playlist structure can be dynamically reconfigured by modifying cluster formation parameters, allowing flexible adaptation to different user needs while maintaining efficient asset organization.
3Ease of operation
If assets are manually filtered and rearranged, then user-specific preferences are satisfied, but time consumption increases
Solution Approach 1:
The system replaces manual mechanical operations (user manually filtering and sorting assets through interface interactions) with automated computational processes. The media guidance application uses algorithms to automatically organize assets into clusters and generate playlists, substituting human manual operations with automated processing that achieves the same organizational goals much faster.
4Device complexity
If no identifiers are provided for filter basis, then system simplicity is maintained, but user understanding of playlist composition deteriorates
Solution Approach 1:
The system uses visual identifiers and metadata tags (analogous to color changes as information carriers) to indicate the basis for asset clustering and filtering. These identifiers provide users with clear information about why assets are grouped together and what criteria were used, while the underlying system remains relatively simple by using straightforward metadata fields rather than complex processing mechanisms.
Data Source
AI summary
Systems and methods for automatically generating a playlist of series assets and systems and methods for grouping assets of a playlist in clusters are provided. In one embodiment, series assets may automatically be included into a playlist for that series. In another embodiment, an interactive media guidance application may group assets in clusters based on one or more user selected parameters or may group assets in cluster based on automatically determined parameters. In yet another embodiment, the interactive media guidance application may group assets in clusters and display at least one identifier in connection with each cluster to indicate a basis for forming the cluster. The identifier may be a key word or catch phrase that succinctly identifies a trait or characteristic of assets in a particular cluster associated with the identifier.