Descriptive Media Search Using Playlist Tokenization
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Solution Overview
Problem
Conventional music search algorithms based on metadata fail to provide relevant results when user queries include descriptive terms not present in the metadata database, limiting the ability to find media content that matches user descriptions of mood or activity-related characteristics.
Innovation Solution
A descriptive media content search method that utilizes playlist descriptions to identify and weight media content items based on tokenized terms, calculating relevance scores using term frequency and inverse document frequency (TFIDF), and generating an inverted index to map descriptive terms to media content, allowing for personalized and relevant search results even when specific metadata is unknown.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional metadata-based music search algorithms are used, then search speed and simplicity are maintained, but search relevance and accuracy deteriorate when user queries contain descriptive terms not present in the metadata database
Solution Approach 1:
The system pre-generates descriptive terms from playlist descriptions and stores them in an inverted index before search operations occur. This preliminary action enables the system to quickly match user queries against pre-computed descriptive terms without performing complex analysis during the actual search, thus improving search relevance while maintaining operational efficiency
Solution Approach 2:
The patent introduces an inverted index as an intermediary data structure that maps descriptive terms to media content items. This intermediary layer bridges the gap between user queries containing descriptive terms and the traditional metadata database, enabling relevant search results without requiring direct modification of the core metadata storage system
2Adaptability or versatility
If playlist descriptions are tokenized and associated with media content items to enable descriptive search, then search versatility and adaptability improve, but data processing time and computational resources increase
Solution Approach 1:
The system performs tokenization of playlist descriptions and creates the inverted index in advance, before actual search queries are submitted. This pre-processing approach converts unstructured playlist descriptions into structured, searchable data structures ahead of time, making the actual search operation fast and efficient while still providing versatile descriptive search capabilities
Solution Approach 2:
The patent segments playlist descriptions into individual tokens (descriptive terms) and creates separate index entries for each token. This segmentation allows the system to efficiently handle diverse query types by matching individual terms rather than processing entire descriptions, improving both search versatility and query response speed
Data Source
AI summary
A descriptive media content search solution is provided to allow a user to search for media content that better matches a user's descriptive search request. The descriptive media content search solution utilizes an extensive catalog of playlists each having a playlist description, such as a playlist title or other descriptive text, and identifies additional descriptive information for media content items to be searched. The descriptive media content search solution can set up a descriptive search database and utilize the descriptive search database to conduct a descriptive search responsive to the user's descriptive search request.