DESC:BACKGROUND
A. Technical Field
[001] The present invention relates to a method and system for trending shows and channels, more particularly the invention relates to trending shows and channel trending for future viewership i.e. to recommend programs to viewers.

B. Background of the Invention
[002] Television is, for the most part, a broadcast medium. That is, our television sets mostly just receive data and hardly ever send anything feedback or response communication. This communication channel is mostly one way.
[003] Today’s consumers are watching more TV than ever, which makes understanding what and how they’re watching an essential part of any marketing campaign.
[004] Audience measurement is any method of measuring how many people are in an audience, usually in relation to radio listenership and television viewership. It often also includes demographic and sometimes psychographic information, to help broadcasters determine who is listening, rather than just how many.
[005] One of the methods involves the use of viewer “diaries,” in which a target audience self-records its viewing (or listening) habits.
[006] A more technologically sophisticated system has used Meters, which are small devices connected to every television in selected homes. These devices gather the viewing habits of the home and transmit the information to the central location for further processing.
[007] These days the Set-top boxes are becoming increasingly prevalent. These devices are capable of communicating and may enable collection of more accurate usage statistics.
[008] The system consists of boxes which are installed in a few homes, which then give data on channels watched, their periodicity, etc. - all of which are key inputs for advertisers. Industry sources cite numerous instances to point out the gross misrepresentation of the system. Industry heads also say that there is no third party audit in the measurement system.
[009] Also the small sample size may mean that "manipulating only a selected number of homes" could cause significant change in data. The industry has pointed out that quality of such data is suspicious since it was well known that upmarket homes would be the toughest ones to allow an intrusive device like a people meter in their homes. Overall, it seems like a hard problem. The TV ratings, were essentially meant as an advertisers tool to plan their media spends.
[0010] Alternatively, if everyone started watching videos on iPods or streamed over the Internet - instead of on TV in their living rooms - these top-rated shows would probably go the way of ratings as the data is not collected about what people watch on handheld video-viewing gadgets or from PCs streaming network TV shows.
[0011] The increasing complexity of home electronics, and new technologies such as time-shifted viewing, demands new ways to identify what people were watching, and when.
[0012] An emerging problem, is what type of viewing is actually counted. There are now many ways to watch a TV programs...
? Broadcasts from local channels, received through an aerial.
? Broadcasts from international channels, from a satellite dish.
? Viewing a TV program on a computer.
? Programs that are recorded on videotape or DVD, and viewed later by playing back the recording.
? The same can be done with a "personal video recorder" or digital video recorded (DVR). With this, you can watch a program in "delayed time" - e.g. watching the first half while the second half is still being broadcast.
? Another emerging problem is the very small portable TV sets now becoming popular. These cannot be connected to fixed phone lines, and any peoplemeters could be larger than the TV set itself.
[0013] All these possibilities make it difficult to record viewing: difficult, both in a technical sense and in deciding exactly what should count as viewing. The convention is that recorded viewing is counted only if it is played back within one week.
[0014] From the raw data of the number of households or people viewing TV channels, these measures are calculated:
? Ratings (of households and/or people)
? Households Using Television (HUTs)
? TARPs (Target Audience Rating Points)
? Reach and frequency
? Program rankings
? Audience share
[0015] Each of these may be explained as:
Ratings: People ratings are also a percentage, but of people, not households. Unlike radio audience surveys, which don't include children under a certain age (around 10 to 15), TV surveys usually include everybody (except babies). People ratings can also be based on demographic groups: age groups, sexes, occupation types, and so on.
HUT: Households Using Television (HUT) figures are simply ratings (not people ratings, though) for all channels combined. An HUT figure of 50 means that 50% of households were watching TV in the survey area. This can be either an average across a long time period, or a figure at a particular time.
TARPs: Target Audience Rating Points (TARPs) are used mainly by advertisers. They apply more to commercials than programs.
Reach: Reach is the number or percentage of people who see that program or commercial, or watch that channel in a particular time zone. For example, a program might have an average people rating of 10%, but a reach of 20% - which means that 10% of people in the survey area were watching it on average, but across the whole time it was being broadcast, 20% saw some part of it. Divide the people rating by the reach to find out the proportion of the program that the average viewer saw: in that example, it's 10 out of 20, which is half: i.e. the average person who watched the program saw half of it.
Frequency: Frequency also applies to commercials. For example, a common myth (not supported by much empirical data) is that the average frequency for a TV commercial should be 3: in other words, the average person should see the commercial 3 times before rushing off to buy the advertised product. (In fact, people just don't behave like that.)
Program rankings: Program rankings are popular with people who don't understand the ratings system (e.g. many journalists). These are often reported in the press, along the lines of "Channel 28 had 6 of the top 10 programs last week". Such figures can be quite misleading. A channel with 6 of the top 10 programs probably had an audience share of around 30%, not the 60% you might assume. That's because in one week a channel might broadcast around 150 programs, and most of the viewing was to the bottom 140, not the top 10.
Audience share: Audience share can be confusing. If a channel has 30% audience share, that doesn't mean that 30% of people watch it. A share figure is a share of person-hours, not of people. A 30% share means that, of every 100 hours that people in the survey area spent watching TV, 30% of those hours were with that channel. So if you add up all the share figures for every channel, the total is always 100%. It's also possible to calculate share figures for specific time periods, but it usually doesn't make sense to calculate shares for an individual program unless all channels in the area have programs starting and finishing at the same time.
[0016] The viewership for websites may be measured through Server-based and user-based methods. However it may encounter Problems such as:
- proxies
- ethical problems: - (block their cookies?)
- Code of Practice.
[0017] Some of the Television viewership Measurement Terms are
Universe Estimate (U.E.): Total persons or homes in a given population,
Rating %: The estimate of the size of television audience relative to the total universe, expressed as a percentage. The estimated percent of all TV households or persons tuned to a specific station.
Share (of Audience): The percent of Households Using Television (HUT) or Persons Viewing Television (PVT) which are tuned to a specific program or station at a specific time.
Average Audience (AA): The estimated average audience of a program during a time increment of its duration.
Weighted Average: Calculated by multiplying each program's rating by its duration, summing these products and dividing the total by the sum of the duration. See also Duration Averaging.
Duration Averaging: Averaging programs together by weighting according to the length of each program
Coverage: The percent of TV households that could receive a program. It’s the ability to view, not actual viewing.
Coverage Area: Rating % Average Audience in percent of homes able to receive an individual cable network or specialty channel.
[0018] Further, most of these systems involve several manual data entry points. Data gets captured manually or through an Electronic Data Collector(EDC) and has to be manually imported into a system for review. EDC only captures data elements but not overall viewership metrics including those relating to Study Performance, Site Performance, Monitor Performance, and Budgets etc. All present systems only has manually entered data and reports but no correlation to determine and offer programs of the viewer’s choice.
[0019] Further, the available systems have various drawbacks/ deficiencies such as the current viewership measurement is based on historical consumption. This means the user can only get the most popular programs for last week / last month / last year etc. Thus the TV viewership measurement data outputs are only available after at least a week or more.
[0020] Another drawback associated with the present systems is that there is no measurement for future intention to view a particular program / channel which is the most critical indicator to both trade and consumers from the standpoint of their specific planning viewership.
[0021] Also the current TV measurement ratings cannot be used to recommend programs to TV viewers as they are mainly meant for the business and trade.
[0022] Further, the present systems fails to guide towards / help the viewer in discovery of programs that the crowds have discovered which might have been unknown to a specific user.
[0023] Further, when viewers are searching for programs to watch in a current / future timeframe there is no present method to discover programs that the crowds have discovered which might have been unknown to a specific user.
[0024] Also, manual and /or editorial trending of programs and channels is impossible due to sheer volume of TV show across 600+ channels.
[0025] As per the present system the measurement data outputs are only available after a week.
[0026] Any or all of the present system does not indicates or teaches directly or indirectly trending of shows and/or channels for intention of viewership in the future.
[0027] Any or all of the present system does not take in to consideration viewer interactions and activities.
[0028] Any or all of the present systems and method thereof for TV measurement ratings cannot be used to recommend programs to TV viewers due to many and all of the above mentioned constraints.
[0029] For the reasons stated above, which will become apparent to those skilled in the art upon reading and understanding the specification, there is a need in the art for a system and method for trending shows and channels for future viewership that is universally useable, scalable and independent of new technology platforms, uses minimum resources that is easy and cost effectively maintained and is portable and can be deployed anywhere in very little time.

BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Reference will be made to embodiments of the invention, examples of which may be illustrated in the accompanying figures. These figures are intended to be illustrative, not limiting. Although the invention is generally described in the context of these embodiments, it should be understood that it is not intended to limit the scope of the invention to these particular embodiments.
Fig. 1 illustrates a system for trending shows and channels for future viewership.
Fig. 2 illustrates a flow diagram of the method for trending shows and channels for future viewership.

SUMMARY OF THE INVENTION

[0031] The present invention relates to trending shows and channels for future viewership. The system of the present invention include a plurality of input devices, at least one tracking module, at least one viewer profile database configured to store viewer profile, at least one program database configured to store current and future programs and the program popularity levels, at least one encoder module, a cloud computing platform and a system processor. The system implements a method for profiling a plurality ofprograms and channels based on a plurality of series of objective input parameters respective to the viewer; generate a plurality of program and channels popularity level ratings at every event occurring at any of the parameters by providing weightage to the parameters and prioritizing the parameters, create rankings within those specific lists of the plurality of programs and channels to come up with cohesive result relating to the preferences of each unique viewer.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE INVENTION

[0032] The embodiments herein provide a method and system for trending shows and channels for future viewership. Further the embodiments may be easily implemented in various viewership measurement structures. The method of the invention may also be implemented as application performed by a stand alone or embedded system.
[0033] The invention described herein is explained using specific exemplary details for better understanding. However, the invention disclosed can be worked on by a person skilled in the art without the use of these specific details.
[0034] References in the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, characteristic, or function described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
[0035] Hereinafter, the preferred embodiments of the present invention will be described in detail. For clear description of the present invention, known constructions and functions will be omitted.
[0036] Parts of the description may be presented in terms of operations performed by a computer system, using terms such as data, state, link, fault, packet, and the like, consistent with the manner commonly employed by those skilled in the art to convey the substance of their work to others skilled in the art. As is well understood by those skilled in the art, these quantities take the form of data stored/transferred in the form of electrical, magnetic, or optical signals capable of being stored, transferred, combined, and otherwise manipulated through mechanical and electrical components of the computer system; and the term computer system includes general purpose as well as special purpose data processing machines, switches, and the like, that are standalone, adjunct or embedded.
[0037] A user displays different behaviour pattern on different platforms. According to an embodiment of the present invention, the method and system for trending shows and channels for future viewership of the user is in accordance to the user’s choices, preference and to the benefit across multiple platforms.
[0038] According to an embodiment of the present invention, the system of the present invention and method profiles each unique user and is capable of providing preferred show trend and channels trends for future viewership for the user based on his profile.
[0039] According to an embodiment of the present invention, the present system and method works by creating clusters of viewer profiles and content preference groups. Then it maps the various profile clusters with the content groups to come up with cohesive results relating to the preferences of each unique viewer.
[0040] According to an embodiment of the present invention, a series of objective inputs constituted through various user activities across various connected platforms are provided to the system. The sources of objective inputs may include web and mobile portals, various applications and utilities, social networks, online forums , blogs, third party portals and apps etc.
[0041] According to an embodiment of the present invention, a series of objective inputs are constituted through various user activities such as search, program browsing, favoriting, setting reminders, check-ins, mentions, share, discussions, sentiments, Video views etc. across various connected platforms and are provided to the system as parameters for deriving the trending shows and channels.
[0042] According to an embodiment of the present invention, the variable may convey any desired parameter for trending of shows and/or channels in accordance to the user’s preference and / or choices for program viewing across multiple platforms.
[0043] As per one of the embodiment of the present invention, the defined system may be implemented as a combination of Hardware, Data and Software.
[0044] According to an embodiment of the present invention, the defined system and the method thereof may be implemented to trend every current and future shows and / or channels on a real time basis.
[0045] As per one of the embodiment of the present invention, the system and the method thereof provides means for adjusting these trending of shows and/ or channels based on custom domain factors on scoring methods along with adjustments for fluctuating user interest / activities / actions / social interaction around those programs.
[0046] As per one of the embodiment of the present invention, the system and the method thereof for trending of shows and/or channels wherein trends may be created by taking inputs of various user activities from various connected platforms wherein the list of sources may include but not limited to web & mobile portals, apps, social networks, online forums, blogs, etc.
[0047] As per one another embodiment of the present invention the method and system thereof may be capable of monitoring and may be tracking user activities like program browsing, favouriting, setting reminders, check-ins, mentions, share, etc. and may be being used as parameters for the trending.
[0048] Also as per one another embodiment of the present invention the method and system thereof may be capable of monitoring, tracking and may be capturing host of program related factors and may be further prioritizing and weighting to create a program potential popularity. All these parameters may be assigned weightages by the system and the final output may be derived in terms of Trends for each show. These Trends may be associated to specific genre, sub-genre, hybrid genres, languages and date combinations to create Trends within those specific lists. Further the trending of shows and/or channels can be categorized for each genres, sub-genre, language, geography, etc.
[0049] The system and method thereof for trending of shows and/or channels as per the embodiment of the present invention may be dynamic and may reflect to and /or may change with user activity levels.
[0050] As per one of the embodiments of the present invention the trends of shows and/or channels may be delivered to all the connected platforms which may facilitate user’s TV viewing and enrich their overall TV Viewing experience.
[0051] In one of the embodiment of the present invention the trends of shows and/or channels may be delivered through Cloud based technology and may be configured accordingly to fit the needs of the device to which it may be delivered.
[0052] The present invention may establish and provide trends of shows and/or channels that may be directed for the future - something that was never available as may be guiding light to TV viewers on what programs to watch may be within the specific list they were tracking. The trends of shows and/or channels are meant for the common TV viewers, it helps them decide what to watch on TV.
[0053] As per one embodiment of the present invention these trends of shows and/or channels may not be a one-time measurement gauge, it may be an allocated trend for each program that continuously changes over time based on a programs performance and environment surrounding it. These may be computed by the system continuously and updates may be made available on may be all platforms instantly. Also these trends of shows and/or channels may help Program search and discovery.
[0054] As per one embodiment of the present invention summary of Trending programs / channels may also be delivered to Trade to help them take their planning based decisions.
[0055] As per one another embodiment of the present invention trending shows and / or channels stake the Wisdom of Crowds and flash it to common TV viewers to help viewer decide what to watch on TV.
[0056] As per one embodiment of the present invention a plurality of series of objective inputs are captured through various source of input. These objective inputs consist of plurality of individual variables. The input source can be a web protal that web portal access by the viewer to get information of the programs, apps extracted, downloaded and executed on media devices or devices capable of playing media, discussions posted by the viewer on discussions platforms such as social media platforms, ratings provided by the viewer to the programs at various surveys, channel connectivity obtained by the viewer etc.
[0057] In one scenario, a plurality of program and channels be provided with a plurality of identifiers and the search for the at least one program and at least one channel and like behaviour of the viewer across various program information source is tracked and captured. Based on the plurality of variables of the objective input such as but not limited to favorites, check-ins, reminders, page visit, discussions, online news accessed, mentions, video views, IMDB ratings, user ratings, geography weights, social media communications such as facebook likes, twitter followings, shares on social media etc. the plurality of programs and the channels are profiled.
[0058] The same program or channel may also be profiled differently for the different platform viewersip. For e.g. a viewer when at home may search for family serials as the user have preference for family serials when he is at home. However, when the viewer is performing search at his personal tab device or PC his preference is for horror movies. Accordingly the programs or channels are profiled considering the media device on which the viewer is performing the search and based on the same the viewer is presented with the preferred popular program listing..
[0059] The clusters of viewer’s profiles are created by aggregating linking and behavioural similarity of the viewers for;
[0060] In another step, the method captures host of program related factors of present and future programs. The program related factors includes but not limited to the category of the program, the time of broad cast, the star cast, duration etc. The captured host of program related factors of the future programs are then prioritize and weighted to create a program potential popularity based content preference groups.
[0061] In one another scenario the viewer activities to be used as parameters are tracked for generating performance of plurality of channels and programs, where the parameter tracked includes but not limited to program browsing, favouriting, setting reminders, check-ins, mentions, share, etc.
[0062] Based on the tracked parameters, the performance of plurality ratings of channels and programs is generated at every event occurring at any of the parameters by providing weightage to the parameters and prioritizing the parameters. The plurality of programs and channels popularity level ratings are categorized and linked for each specific genre, sub-genre, hybrid genres, languages, geography and date combinations to create rankings within those specific lists of the plurality of programs and channels which includes but not limited to currently ongoing programs and channels and newly launched shows, programs and channels constituting content preference groups;
[0063] Further, the various profile clusters are mapped with the content preference groups to come up with cohesive result relating to the preferences of each unique viewer;
[0064] Based on the type of platform, that the viewer is accessing the media files, the plurality of programs and channels popularity level ratings is configured to the format receivable by the viewer device.
[0065] The plurality of programs and channels popularity level ratings are delivered to a plurality of viewers through cloud communication network to all connected platform to facilitate user’s TV viewership.
[0066] In one of the embodiment of the present invention the series of objective inputs comprise many individual variables, one of which may be the viewer feedback obtained through a plurality of feedback receiving methods.
[0067] As per one another embodiment of the present invention the program related factures are extracted from the program database.
[0068] As per one another embodiment of the present invention the program related factures are captured from the feed of the broadcasters data.
[0069] As per one another embodiment of the present invention the viewer activities are tracked across various connected platform sources wherein the list of sources may include but not limited to web & mobile portals, apps, social networks, online forums, blogs, etc.
[0070] As per one preferred embodiment of the present invention the system comprise of a plurality of input devices, at least one tracking module, at least one viewer profile database configured to store viewer profile, at least one program database configured to store current and future programs and the popularity performance of the channels and programs, at least one encoder module, a cloud computing platform and a system processor and controller module, wherein the system processor and controller module is configured for profiling a plurality of programs and channels based on a plurality of series of objective input parameters respective to the plurality of programs and channels; to create clusters of viewer’s profiles; to capturing host of program related factors of programs; to generate performance of plurality ratings of channels and programs at every event occurring at any of the parameters by providing weightage to the parameters and prioritizing the parameters; Categorize and link the plurality of programs and channels popularity level for each specific genre, sub-genre, hybrid genres, languages, geography and date combinations to create rankings within those specific lists of the plurality of programs and channels which includes but not limited to currently ongoing programs and channels and newly launched shows, programs and channels constituting content preference groups; map the various profile clusters with the content preference groups to come up with cohesive result relating to the preferences of each unique viewer.
[0071] As per one of the present invention the plurality of input devices are configured to provide a plurality of series of objective inputs comprise of plurality of individual variables.
[0072] As per one of the present invention the at least one tracking module is a processor configured for tracking viewer activities to be used as parameters for the ratings like program browsing, favoriting, setting reminders, check-ins, mentions, share, etc .
[0073] As per one of the present invention the at least one encoder module is a RISC (reduce instruction set computer) processor that configures the plurality of programs and channels popularity level rating and ranking to the format receivable by the user device.
[0074] As per one of the present invention the cloud computing platform is configured to deliver the plurality of programs and channels popularity level ratings and rankings through cloud communication network to all connected platform to facilitate user’s TV viewer-ship.
[0075] As per one of the embodiment of the present invention Trending shows and channel lists may be Real Time and dynamic giving vital clues to all stake holders on performance of certain channels and programs. Trending shows and channels may also indicate popularity levels for newly launched shows and channels. Trending shows and channels may be made available to all the users on all consumer platforms so that they can improve their TV viewing experience.
[0076] Trends of shows and/or channels as determined in the present invention may be very useful for recommending programs on TV to the users. It may provide significant suggestions to the viewers in real time. It may acts as a measure of interactivity of viewers/ prospect viewers with the programs. It may also help measure intention to view particular programs. It may facilitate TV search and discovery for the user. It may provide inputs to the tread to gauge rising / declining popularity of programs , shows and / or channels. It may enrich the overall TV viewing experience of the users.
[0077] The present invention as described in one of the embodiment can be advantageously pushed to any connected platform using the Cloud services.
[0078] The present invention as described in one of the embodiment may be compatible with all connected devices, dynamic in nature, the parameters of inputs can be changed as per the changing viewer behaviours and attain ability to help users understand the trend fluctuations of programs, shows and / or channels within the list that matter to them.
,CLAIMS:1. A method for program trending shows and channels for viewership, the method comprising:
Receiving a plurality of series of objective inputs comprise of plurality of individual variables;
Profiling a plurality of programs and channels based on a plurality of series of objective input parameters respective to the viewer;
Creating clusters of viewer’s profiles;
Capturing host of program related factors of future programs;
Prioritizing and weighting the captured host of program related factors of the plurality of programs and channels to create a plurality of program and channels potential popularity performance based content preference groups
Tracking viewer activities to be used as parameters for the ratings like program browsing, favouriting, setting reminders, check-ins, mentions, share, etc .;
Generating performance of popularity ratings of the plurality of programs and channels at every event occurring at any of the parameters by providing weightage to the parameters and prioritizing the parameters;
Categorizing and linking the plurality of programs and channels popularity level ratings for each specific genre, sub-genre, hybrid genres, languages, geography and date combinations to create rankings within those specific lists of the plurality of programs and channels which includes but not limited to currently ongoing programs and channels and newly launched shows, programs and channels constituting content preference groups;
Mapping the various profile clusters with the content preference groups to come up with cohesive result relating to the preferences of each unique viewer;
Configuring the plurality of programs and channels popularity level ratings to the format receivable by the user device;
Delivering the plurality of programs and channels popularity level ratings and rankings through cloud communication network to all connected platform to facilitate user’s TV viewership.

2. The method as claimed in the claim 1. wherein the series of objective inputs comprise many individual variables, one of which may be the viewer feedback obtained through a plurality of feedback receiving methods.

3. The method as claimed in the claim 1, wherein the program related factures are extracted from the program database.

4. The method as claimed in the claim 1, wherein the program related factures are captured from the feed of the broadcasters data.

5. The method as claimed in claim 1, wherein the viewer activities are tracked across various connected platform sources wherein the list of sources may include but not limited to web & mobile portals, apps, social networks, online forums, blogs, etc.

6. A system for program ratings and rankings for future viewership, the system comprising:
a plurality of input devices, at least one tracking module, at least one viewer profile database configured to store viewer profile, at least one program database configured to store current and future programs and the popularity performance of the channels and programs, at least one encoder module, a cloud computing platform and a system processor and controller module, wherein the system processor and controller module is configured for profiling a plurality programs and channels based on a plurality of series of objective input parameters respective to the plurality programs and channels; to create clusters of viewer’s profiles; to capturing host of program related factors of future programs; to generate performance of plurality ratings of channels and programs at every event occurring at any of the parameters by providing weightage to the parameters and prioritizing the parameters; Categorize and link the plurality programs and channels popularity level for each specific genre, sub-genre, hybrid genres, languages, geography and date combinations to create rankings within those specific lists of the plurality of programs and channels constituting content preference groups; map the various profile clusters with the content preference groups to come up with cohesive result relating to the preferences of each unique viewer.
7. The system as claimed in claim 6, wherein the plurality of input devices are configured to provide a plurality of series of objective inputs comprise of plurality of individual variables.

8. The system as claimed in claim 6, wherein the at least one tracking module is a processor configured for tracking viewer activities to be used as parameters for the ratings like program browsing, favouriting, setting reminders, check-ins, mentions, share, etc .

9. The system as claimed in claim 6, wherein the at least one encoder module is a RISC processor that configures the plurality of programs and channels popularity level rating and ranking to the format receivable by the user device.

10. The system as claimed in claim 6, wherein the cloud computing platform configured to deliver the plurality of programs and channels popularity level ratings and rankings through cloud communication network to all connected platform to facilitate user’s TV viewership.