Netflix Inc.

Carlos A Gomez-Uribe

Vijay Bharadwaj

Angadh Singh

Janis Stipins

Christopher Alvino

Che Hammond

Antonio Molins Jiménez

Mohammad Sabah

Ehtsham Elahi

Aish Fenton

Sasi Parthasarathy

Michael Todd

Siddharth Angrish

An apparatus for minimizing installation footprints of expansion cards may include one or more expansion cards that include a short edge, a long edge that is longer than the short edge and is substantially perpendicular to the short edge, and an edge connector disposed on the short edge. The apparatus may also include an expansion-card frame dimensioned to 1) guide an expansion card toward a printed circuit board of a computing device at a substantially vertical orientation such that the short edge of the expansion card is disposed proximate the printed circuit board of the computing device and the long edge of the expansion card extends away from the printed circuit board and 2) removably couple the edge connector disposed on the short edge of the expansion card to the printed circuit board of the computing device. Various other apparatuses, systems, and methods are also disclosed.

Global recommendation systems for overlapping media catalogs

A system of assessing deployments in a network-based media system is provided herein. The system includes a data storage system storing observation vectors, each observation vector being associated with an outcome indicator, and a processing device in communication with the data storage system to receive and store observation vectors and associated outcome indicators. The processing device performs operations including communicating with an endpoint device of a user to obtain information associated with the endpoint device; and transmitting an instance of a variable user interface to the endpoint device for presentation to the user via the endpoint device based on the stored observation vectors, the stored associated outcome indicators, and the obtained information associated with the endpoint device. Related systems and methods are also disclosed.

Online techniques for parameter mean and variance estimation in dynamic regression models

Techniques for selecting and ordering groups of titles to present as recommendations. In one embodiment, for example, a method performed by one or more computing devices of an online services comprises selecting, for each of a plurality of row positions, a group of titles to fill the row position based at least in part on a relevance score computed for the group of titles. The relevance score is based at least in part on a personalized ranking for a particular user of titles in the groups in titles selected to fill the row positions. The groups of titles selected to fill to the row positions are presented as recommendations to the particular user as a sequence of rows in which each row in the sequence corresponds to one of the selected groups of titles.

Selecting and ordering groups of titles

A system of assessing deployments in a network-based media system is provided herein. The system include a data storage system storing observation vectors, each observation vector being associated with an outcome indicator, and a processing device in communication with the data storage system to receive and store observation vectors and associated outcome indicators. The processing device performs operations including communicating with an endpoint device of a user to obtain information associated with the endpoint device; and transmitting an instance of a variable user interface to the endpoint device for presentation to the user via the endpoint device based on the stored observation vectors, the stored associated outcome indicators, and the obtained information associated with the endpoint device. Related systems and methods are also disclosed.

In an approach, a method comprises using a server computer in a media content delivery system that is configured to selectively deliver a particular media title from among a library of titles, for a source title, generating title data that specifies an order of a plurality of titles that are related to the source title based on a plurality of stored probability values; wherein each probability value in the plurality of probability values represents, for each particular title of the plurality of titles, a likelihood of selecting the particular title after playing the source title; using the server computer, receiving title impression data, wherein the title impression data specifies a plurality of browsed titles that were browsed from among the plurality of titles but may have not been selected for interaction; using the server computer, receiving title interaction data, wherein the title interaction data specifies a plurality of selected titles that were selected for interaction from the plurality of browsed titles; based on the title interaction data, the title impression data and a statistical model, re-calculating the plurality of probabilities.

Recommending media items based on take rate signals

A data processing method comprises receiving title interaction data, wherein the title interaction data specifies, an order in which users interacted with a plurality of titles; generating a plurality of statistical models, each statistical model of the plurality of statistical models specifying a plurality of probabilities, wherein the plurality of probabilities represent, for each first title of the plurality of titles and each second title of the plurality of titles, a likelihood that a user will interact with the first title then next interact with the second title; refining the plurality of statistical models based on the title interaction data; determining a plurality of weight values corresponding to the plurality of statistical models for a particular user; identifying, for the particular user, one or more recommended titles of the plurality of titles based on the plurality of weight values and the plurality of statistical models.

Personalized Markov chains

Techniques are described for determining relationships between user activities and determining search results and content recommendations based on the relationships. A plays-related-to-searches application may determine a relationship score between plays of a media title and searches of a query by determining a distance between a projection of the search onto the space of the users and a projection of plays of the media title onto the space of the users. A plays-after-searches application may determine a score for plays of the streaming media title given the search by multiplying a number of times plays of the media title occur after the query is entered by the number of times any play occurs, and dividing by a product of the number of times plays of the media title occur after any query is entered and the number of times plays of any media title occur after the query is entered.

Relationship-based search and recommendations

In an approach, a method comprises receiving title interaction data, wherein the title interaction data specifies, an order in which users interacted with a plurality of titles; generating a plurality of statistical models, each statistical model of the plurality of statistical models specifying a plurality of probabilities, wherein the plurality of probabilities represent, for each first title of the plurality of titles and each second title of the plurality of titles, a likelihood that a user will interact with the first title then next interact with the second title; refining the plurality of statistical models based on the title interaction data; determining a plurality of weight values corresponding to the plurality of statistical models for a particular user; identifying, for the particular user, one or more recommended titles of the plurality of titles based on the plurality of weight values and the plurality of statistical models.

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Campbell, CA, United States of America

Carlos A Gomez-Uribe