This document describes, among other things, systems, methods, devices, and other techniques for using information about how long various videos were presented at client devices to determine subsequent video recommendations and search results. In some implementations, a computing can include a modeling apparatus, a front-end server, a request manager, one or more video file storage devices, a video selector, or a combination of some or all of these. The video selector can select video content for a particular digitized video among a plurality of digitized videos to serve to a computing device responsive to a request. The selection can be based at least in part on how long the particular digitized video has been presented at client devices associated with users having characteristics that match one or more characteristics of the user that submitted the request for video content, as indicated by the modeling apparatus.

According to some aspects, methods and systems may include determining that events associated with requests or accessing content items have occurred. The methods and systems may also include authorizing transmission of the content items to the requesting devices based on credential information associated with the requests, and determining a viewership quantity metric associated with the requests.

Methods and apparatus for pre-scaling media content to facilitate audience measurement are disclosed. An example method includes encoding a media content sample in accordance with a first encoding configuration and playing the encoded sample. The example method also includes attempting to detect the codes in the sample, and computing a ratio between the codes encoded in the sample and the codes detected when the sample is played.

Methods and apparatus to detect spillover are disclosed. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to: identify a quantity of first durations of loudness in an audio signal of media; calculate a ratio of the quantity of the first durations of loudness to a quantity of second durations of loudness in the audio signal of the media, the quantity of the second durations of loudness including the quantity of the first durations of loudness; and in response to a detection of the audio signal being spillover, store data denoting the media as un-usable to credit a media exposure when the ratio does not satisfy a loudness ratio threshold, the storing of the data to improve an accuracy of media exposure credits by not crediting spillover media.

A request from a user to view a video content item may be received, the requesting user being associated with a set of preferences and a context. A group of similar users may be identified based the set of preferences or the context. A number of promotional video items corresponding to the video content item may be identified. A first subset of the number of promotional video items may be determined based on the set of preferences or the context of the user. A watch time difference may be determined for each promotional video item in the first subset. A second subset may be determined based on the watch time difference associated with each promotional video items. An activity rate associated with the promotional video items in the second subset is determined. A promotional video item of the second subset that satisfies a criterion is provided to the user.

A method includes receiving, by a content server including one or more processors and from a client device, one or more characteristics of a particular content delivery opportunity, obtaining, by the content server, a watermarked digital component that is stenographed with a watermark representing (i) a payload that triggers an action by a client device that detects the watermark and (ii) a reporting location that is contacted by a client device in response to detecting the watermark, generating, by the content server, combined content by combining the watermarked digital component with content from a source that differs from a source of the digital component, and providing, by the content server and to the client device, the combined content.

A programming access device such as, for example, a cable or satellite set top box (STB), a digital video recorder (DVR), a personal computer, and/or a digital media receiver automatically optimizes an order of content choices presented in a content listing, such as a program guide display, favorite channel display, and/or a recording listing display based on the past viewing and/or recording history of a current user.

Apparatus, systems, articles of manufacture, and methods to identify and credit media using ratios of media characteristics are disclosed herein. Example apparatus to identify media include at least one memory, instructions, and at least one processor to execute the instructions to: determine a first ratio based on a first time interval and a second time interval of a monitored media signal; determine a second ratio based on the second time interval and a third time interval of the monitored media signal; generate a first ratio signature based on the first and second ratios; and initiate transmission of the first ratio signature to a recipient that is to compare the first signature with a second ratio signature to identify the media.

Methods, apparatus, systems, and articles of manufacture are disclosed for editing tuning data collected via automated content recognition. Examples include determining whether a time conflict exists between first tuning data corresponding to a first tuning event and second tuning data corresponding to a second tuning event. Examples also include that, in response to determining that the time conflict exists, creating a third tuning event based on the first tuning data, the second tuning data, and one or more criteria. Examples also include that modifying at least one of the first tuning event or the second tuning event based on the third tuning event. Examples also include that crediting a media presentation by the presentation device based on edited tuning data, the edited tuning data including the first modified tuning event, the second modified tuning event, and the third tuning event.

Methods, apparatus, systems, and articles of manufacture are disclosed for adjusting a tuning event. Examples disclosed herein include determining an initial adjustment factor for a group of stations and a combination of metadata categories associated with panel data and census data. Examples disclosed herein further include determining a final adjustment factor for the group of stations based on the initial adjustment factor and a bias correction factor. Example disclosed herein further include adjusting weighted minutes of the tuning event based on the final adjustment factor, the tuning event corresponding to the group of stations and the combination of metadata categories, the adjusted tuning event to be credited to media.