Searches and recommendations using distance metric on space of media titles
AssigneeNetflix, Inc.
InventorJANIS STIPINS, III
Life of this patent
Estimating the term…
Abstract
Techniques are described for generating search results and content recommendations using a distance metric on a space of media titles. In one embodiment, each media title may be associated with metadata tags and represented by a vector which indicates those associated tags. The distance metric may measure distance as an angle between vectors representing media titles in a bent vector space that accounts for correlations between tags. Further, a non-linear scaling may be applied to the vectors representing media titles to correct for under-tagging and redundant tagging. Based on the distance metric, a search or recommendation application may generate search results and/or content recommendations and cause the same to be presented to a user.
Claims22
A computer-implemented method comprising:
- receiving, for each of a plurality of objects, metadata tags describing the object;
- determining distances between a plurality of first vectors, each representing a respective one of the plurality of objects based on the metadata tags describing the respective object, and a plurality of second vectors, each representing a respective one of the plurality of objects based on the metadata tags describing the respective object;
- and
- generating content recommendations based at least on the determined distances,
- wherein determining distances between the plurality of first vectors and the plurality of second vectors includes correcting for under-tagging and redundant tagging by non-linearly scaling the plurality of first vectors and the plurality of second vectors.
A non-transitory computer-readable storage medium storing code for execution by a processor, wherein the code, when executed, performs an operation, comprising:
- receiving, for each of a plurality of objects, metadata tags describing the object;
- determining distances between a plurality of first vectors, each representing a respective one of the plurality of objects based on the metadata tags describing the respective object, and a plurality of second vectors, each representing a respective one of the plurality of objects based on the metadata tags describing the respective object;
- and
- generating content recommendations based at least on the determined distances,
- wherein determining distances between the plurality of first vectors and the plurality of second vectors includes correcting for under-tagging and redundant tagging by non-linearly scaling the plurality of first vectors and the plurality of second vectors.
A system, comprising:
- a memory;
- and
- a processor storing one or more applications, which, when executed on the processor, perform an operation comprising:
- receiving, for each of a plurality of objects, metadata tags describing the object,
- determining distances between a plurality of first vectors, each representing a respective one of the plurality of objects based on the metadata tags describing the respective object, and a plurality of second vectors, each representing a respective one of the plurality of objects based on the metadata tags describing the respective object, and
- generating content recommendations based at least on the determined distances;
- wherein determining distances between the plurality of first vectors and the plurality of second vectors includes correcting for under-tagging and redundant tagging by non-linearly scaling the plurality of first vectors and the plurality of second vectors.
Dependencies are inferred from the claim text.