Intelligent system and methods of recommending media content items based on user preferences
US-9854310-B2 · Dec 26, 2017 · US
US2016269783A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016269783-A1 |
| Application number | US-201514866158-A |
| Country | US |
| Kind code | A1 |
| Filing date | Sep 25, 2015 |
| Priority date | Mar 9, 2015 |
| Publication date | Sep 15, 2016 |
| Grant date | — |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
Methods, apparatus, systems and articles of manufacture are disclosed to assign viewers to media meter data. An example method includes calculating, with a processor, first viewing probabilities for tuning panelists in a tuning household during a first set of time periods, calculating, with the processor, second viewing probabilities for viewing panelists in a plurality of candidate viewing households during a second set of time periods, identifying, with the processor, a matching one of the plurality of candidate viewing households based on an absolute difference value between an average value of the first viewing probabilities and respective ones of average values of the second viewing probabilities, and reducing an imputation error by imputing, with the processor, tuning minutes of the tuning household as viewing minutes for the respective tuning panelists when the matching one of the plurality of candidate viewing households exhibits viewing activity during one of the second set of time periods that matches one of the first set of time periods.
Opening claim text (preview).
What is claimed is: 1 . A method to impute panelist household viewing behavior, comprising: calculating, with a processor, first viewing probabilities for tuning panelists in a tuning household during a first set of time periods; calculating, with the processor, second viewing probabilities for viewing panelists in a plurality of candidate viewing households during a second set of time periods; identifying, with the processor, a matching one of the plurality of candidate viewing households based on an absolute difference value between an average value of the first viewing probabilities and respective ones of average values of the second viewing probabilities; and reducing an imputation error by imputing, with the processor, tuning minutes of the tuning household as viewing minutes for the respective tuning panelists when the matching one of the plurality of candidate viewing households exhibits viewing activity during one of the second set of time periods that matches one of the first set of time periods. 2 . A method as defined in claim 1 , wherein the first set of time periods and the second set of time periods include data points having a quarter hour resolution. 3 . A method as defined in claim 1 , further including calculating an adjusted quarter hour ratio when a number of the first set of time periods is dissimilar to a number of the second set of time periods. 4 . A method as defined in claim 3 , wherein the adjusted quarter hour ratio includes a ratio of the number of the second set of time periods divided by the number of the first set of time periods. 5 . A method as defined in claim 4 , further including generating a final quarter hour order value associated with the second set of time periods by multiplying the adjusted quarter hour ratio by a temporal placeholder associated with the first set of time periods. 6 . A method as defined in claim 5 , further including expanding the number of the second set of time periods to match the first set of time periods based on the final quarter hour order value. 7 . A method as defined in claim 1 , wherein identifying the matching one of the plurality of candidate viewing households based on an absolute difference value further includes selecting the matching one of the plurality of candidate viewing households that do not exhibit viewing behavior within a similar geographic area when the absolute difference value satisfies a threshold value from a next-lowest absolute difference value. 8 . An apparatus to impute panelist household viewing behavior, comprising: a total probability calculator to: calculate first viewing probabilities for tuning panelists in a tuning household during a first set of time periods; and calculate second viewing probabilities for viewing panelists in a plurality of candidate viewing households during a second set of time periods; and a rank engine to: identify a matching one of the plurality of candidate viewing households based on an absolute difference value between an average value of the first viewing probabilities and respective ones of average values of the second viewing probabilities; and reduce an imputation error by imputing tuning minutes of the tuning household as viewing minutes for the respective tuning panelists when the matching one of the plurality of candidate viewing households exhibits viewing activity during one of the second set of time periods that matches one of the first set of time periods. 9 . An apparatus as defined in claim 8 , wherein the first set of time periods and the second set of time periods include data points having a quarter hour resolution. 10 . An apparatus as defined in claim 8 , further including a minutes aggregator to calculate an adjusted quarter hour ratio when a number of the first set of time periods is dissimilar to a number of the second set of time periods. 11 . An apparatus as defined in claim 10 , wherein the minutes aggregator is to calculate the adjusted quarter hour ratio as a ratio of the number of the second set of time periods and the number of the first set of time periods. 12 . An apparatus as defined in claim 11 , wherein the minutes aggregator is to generate a final quarter hour order value associated with the second set of time periods by multiplying the adjusted quarter hour ratio by a temporal placeholder associated with the first set of time periods. 13 . An apparatus as defined in claim 12 , wherein the minutes aggregator is to expand the number of the second set of time periods to match the first set of time periods based on the final quarter hour order value. 14 . An apparatus as defined in claim 8 , wherein the rank engine is to select the matching one of the plurality of candidate viewing households that do not exhibit viewing behavior within a similar geographic area when the absolute difference value satisfies a threshold value from a next-lowest absolute difference value. 15 . A tangible computer readable storage medium comprising computer readable instructions that, when executed, cause a processor to at least: calculate first viewing probabilities for tuning panelists in a tuning household during a first set of time periods; calculate second viewing probabilities for viewing panelists in a plurality of candidate viewing households during a second set of time periods; identify a matching one of the plurality of candidate viewing households based on an absolute difference value between an average value of the first viewing probabilities and respective ones of average values of the second viewing probabilities; and reduce an imputation error by imputing tuning minutes of the tuning household as viewing minutes for the respective tuning panelists when the matching one of the plurality of candidate viewing households exhibits viewing activity during one of the second set of time periods that matches one of the first set of time periods. 16 . A tangible computer readable storage medium as defined in claim 15 , wherein the instructions, when executed, cause the processor to calculate an adjusted quarter hour ratio when a number of the first set of time periods is dissimilar to a number of the second set of time periods. 17 . A tangible computer readable storage medium as defined in claim 16 , wherein the instructions, when executed, cause the processor to compute a ratio of the number of the second set of time periods and the number of the first set of time periods. 18 . A tangible computer readable storage medium as defined in claim 17 , wherein the instructions, when executed, cause the processor to generate a final quarter hour order value associated with the second set of time periods by multiplying the adjusted quarter hour ratio by a temporal placeholder associated with the first set of time periods. 19 . A tangible computer readable storage medium as defined in claim 18 , wherein the instructions, when executed, cause the processor to expand the number of the second set of time periods to match the first set of time periods based on the final quarter hour order value. 20 . A tangible computer readable storage medium as defined in claim 15 , wherein the instructions, when executed, cause the processor to select the matching one of the plurality of candidate viewing households that do not exhibit viewing behavior within a similar geographic area when the absolute difference value satisfies a threshold value from a next-lowest absolute difference value.
sound input device, e.g. microphone · CPC title
involving the geographical location of the client (retrieval from the Internet by querying based on geographical locations G06F16/9537; systems specially adapted for using geographical information in broadcast systems H04H60/70; protocols in which the network application is adapted for the location of the user terminal in communication control or processing H04L67/52; services making use of the location of users or terminals in wireless networks H04W4/02; locating users or terminals in wireless networks H04W64/00) · CPC title
Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections · CPC title
involving probabilistic networks, e.g. Bayesian networks · CPC title
Analytics of user selections, e.g. selection of programmes or purchase activity (monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33) · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.