The Nielsen Comapny (us), LLC

Raghuram Ranganathan

Daniel John Nelson

David Howell Wright

James Petro

Dan Nelson

Deborah Cross

Venugopal Srinivasan

Derrick McCulley

Arun Ramaswamy

Kenneth William McArthur

Sandeep Tapse

Anand Jain

Daniel A Nelson

Shruthi Rao

Spoorthi Ramakanth Deshmukh

Kenneth William Mcarthur

Methods, apparatus, systems, and articles of manufacture are disclosed to identify candidates for media asset qualification. Example apparatus disclosed herein include a media creditor to determine whether to credit a first media asset to linear media or non-linear media, the non-linear media including subscription video on demand (SVOD). Disclosed example apparatus also include a media asset candidate controller to: classify the first media asset as a non-candidate for media asset qualification in response to the first media asset being credited to the linear media or the non-linear media. In some examples, the media asset candidate controller is to determine whether to classify the first media asset as a candidate for media asset qualification based on whether the first media asset remains uncredited by the media creditor and the first media asset overlaps a streaming period.

Methods, apparatus, and articles of manufacture to identify candidates for media asset qualification

Methods, apparatus, systems and articles of manufacture are disclosed to optimize reference signature matching using watermark matching. An example disclosed herein includes selecting first unhashed reference signatures to evaluate for a second time segment of monitoring data based on watermark coverage of a first time segment of the monitoring data, the monitoring data obtained from a meter monitoring media presented by a media device and comparing the first unhashed reference signatures with first unhashed monitored signatures from the second time segment of the monitoring data. The example further includes, when a first media event associated with the monitoring data is not identifiable based on the comparing of the first of unhashed reference signatures with the first unhashed monitored signatures hashing the first unhashed monitored signatures to form a corresponding first hashed monitored signatures and comparing the first hashed monitored signatures with a library of reference hashed signatures to determine the first media event associated with the second time segment of the monitoring data.

Methods and apparatus to optimize reference signature matching using watermark matching

Example apparatus disclosed herein to implement signature matching with meter data aggregation for use in media identification applications include a match job aggregator to aggregate batches of meter data from a meter to form aggregated meter data associated with the meter, and a hash matcher to identify a valid hash key match between meter hash keys generated from meter signatures in the aggregated meter data and reference hash keys corresponding to a collection of media assets. Disclosed example apparatus also include a signature matcher to align, based on the valid hash key match, a sequence of reference signatures corresponding to a first media asset associated with the valid hash key match and a corresponding sequence of the meter signatures, and compare the sequence of reference signatures and the corresponding sequence of meter signatures to identify media represented by at least a portion of the sequence of the meter signatures.

Signature matching with meter data aggregation for media identification

Methods, apparatus, systems and articles of manufacture to credit unidentified media are disclosed. Disclosed example apparatus include a database updater to store a first group of signatures representative of unidentified media in a database, the first group of signatures obtained from a first media meter to monitor a first media presentation device, the first group of signatures associated with a first media exposure category based on media source information reported by the first media meter. Disclosed example apparatus also include a media comparator to compare a second group of signatures with the first group of signatures, the second group of signatures obtained from a second media meter to monitor a second media presentation device. Disclosed example apparatus further include a reporter to credit media exposure represented by the second group of signatures to the first media exposure category when the second group of signatures matches the first group of signatures.

Methods and apparatus to credit unidentified media

Methods, apparatus, systems and articles of manufacture are disclosed selectively generating and storing hashed reference signatures. An example method disclosed herein determining whether watermark coverage of a first media segment satisfies a dropout constraint, the first media segment corresponding to a first monitoring time interval of a media source feed and, when the watermark coverage of the first media segment does not satisfy the dropout constraint hashing first media signatures associated with the first media segment to generate corresponding first hashed signatures and generating first reference data for the first media segment, the first reference data including the first hashed signatures and the first media signatures. The example method further includes, when the watermark coverage of the first media segment satisfies the dropout constraint, generating second reference data for the first media segment, the second reference data including the first media signatures.

Methods and apparatus for optimizing station reference fingerprint loading using reference watermarks

Methods, apparatus, systems and articles of manufacture are disclosed to generate a signature based on signature candidates. An example apparatus disclosed herein includes first means for determining an alignment point of a first candidate signature segment and a second candidate signature segment, the first candidate signature segment and the second candidate signature segment include time data and signature data, the alignment point based on the time data of the first candidate signature segment and the time data of the second candidate signature segment, means for comparing a first signature to a second signature at the alignment point, the first signature representative of media included in the first candidate signature segment, the second signature included in the second candidate signature segment, and means for stitching the second signature to the first signature based on the comparison to generate a stitched signature, the stitched signature to be used for media crediting.

Methods and apparatus to generate a signature based on signature candidates

Methods and apparatus to identify alternate language versions of media based on signature matching are disclosed. Example apparatus disclosed herein include a signature matcher to compare signatures in monitored data with reference signatures to determine signature match strengths associated with portions of the monitored data, the reference signatures associated with reference media assets. Disclosed example apparatus also include a data segmenter to divide the monitored data into first and second segments, the first segments including temporally adjacent portions of the monitored data having signature match strengths that satisfy a threshold, the second segments including temporally adjacent portions of the monitored data having signature match strengths that do not satisfy the threshold. Disclosed example apparatus further includes a trend determiner to determine, based on a pattern of the first and second segments, whether the monitored data is associated with an alternative language version of one of the reference media assets.

Methods and apparatus to identify alternate language versions of media based on signature matching

In an example system, a meter device records streaming session information. Cluster creation circuitry trains a model by grouping information from multiple streaming sessions into clusters. All streaming sessions within a given cluster have matching media and streaming sources. Model executor circuitry assigns incoming streaming session information to a cluster or to noise. Cluster creation circuitry edits the model by creating new clusters out of information from multiple streaming sessions with similar attributes that were originally labeled as noise.

Methods and apparatus to accurately credit streaming sessions

Methods, apparatus, systems, and articles of manufacture are disclosed for loading and roll-off of reference media assets. Example apparatus disclosed herein are to determine whether a first condition to prune a reference media asset is satisfied, and in response to a determination that the first condition is satisfied, determine whether a second condition to prune the reference media asset is satisfied. Disclosed example apparatus are also to, in response to a determination that the second condition is satisfied: segment the reference media asset into a plurality of segments based on a length of the reference media asset, prune a first one of the segments, and retain a second one of the segments in a database to compare with meter data to credit media exposure associated with the reference media asset.

Methods and apparatus for loading and roll-off of reference media assets

Example apparatus disclosed herein are to obtain a first hash key, a second hash key and a third hash key representative of first reference media in response to a first query of a first table, the second hash key associated with a second time preceding a first time associated with the first hash key, the third hash key associated with a third time following the first time associated with the first hash key. Disclosed example apparatus are also to prequalify the first hash key as a candidate for subsequent signature processing associated with a first site signature in response to a determination that the second hash key corresponds to a second site signature preceding the first site signature in time and that the third hash key corresponds to a third site signature following the first site signature in time.

Signature retrieval and matching for media monitoring

Methods, apparatus, systems and articles of manufacture to credit media segments shared among multiple media assets are disclosed. Example methods disclosed herein include comparing a sequence of monitored media signatures with a library of reference signatures to determine a signature match, the monitored media signatures representative of a monitored media presentation. Disclosed example methods also include determining duration and offset of the signature match, the offset to represent a position of the signature match relative to a start of a reference media asset associated with the signature match. Disclosed example methods further include crediting a segment of the monitored media presentation represented by the signature match to an identifier of a class of media assets including the reference media asset in response to a determination that (i) the duration of the signature match does not exceed a first threshold and (ii) the offset does not exceed a second threshold.

Methods and apparatus to credit media segments shared among multiple media assets

Methods, apparatus, systems and articles of manufacture are disclosed for scalable architectures for reference signature matching and updating. An example method for scalable architectures for reference signature matching and updating includes accessing site signatures to be compared to reference signatures from a first group of media sources. Determining if a first reference node is an owner of a first one of the site signatures. Comparing a neighborhood of site signatures including the first site signature to reference signatures in a first subset of reference signatures when the first reference node is the owner of the first site signature, the first subset of references signatures stored in a first memory partition associated with the first reference node. Not comparing site signature to reference signatures when the first reference node is not the owner of the first one of the site signatures.

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Tampa, FL, United States of America

Raghuram Ranganathan