WO2011146688A1

WO2011146688A1 - Distributing content

Info

Publication number: WO2011146688A1
Application number: PCT/US2011/037101
Authority: WO
Inventors: Ant Oztaskent; Yaroslav Volovich; Raimundo Mirisola; Nicholas S. Arini; Simon M. Rowe; Iain Merrick; Andrew Gildfind; Kyle Maddison
Original assignee: Google Inc.
Priority date: 2010-05-19
Filing date: 2011-05-19
Publication date: 2011-11-24
Also published as: EP2572256A1; KR20130121695A; EP2572256A4; CA2799965A1

Abstract

Current viewer activity information regarding viewer activity in a television content distribution system is used to generate content item recommendation information regarding recommended content items that match a viewer's interests. The content item recommendation information inculdes information regarding content items that are currently viewed or recorded by the greatest number of viewers and can be based on profile information for viewers and/or content item scheduling information.

Description

TECHNICAL FIELD

This disclosure relates to distributing content.

In many different environments, content providers want to distribute content to selected recipients. For example, advertisers want to distribute their advertisement creatives through content distribution channels where the advertisement creatives will be effective in

communicating information to potential customers, and when the advertisements will lead to desired activity, such as a purchase of the advertiser's goods or services, in some instances, a content provider may rely on contextual information when making decisions regarding content distribution selections, including the selection of content distribution channels. For example, an advertiser may want to advertise goods and/or services relating to travel in travel magazines or during travel television programs.

Additionally, content distribution system operators want users of the content distribution systems to find and view content that they will enjoy. When users find and view content that they enjoy, the users are typically satisfied and continue to use the system. Furthermore, when users find and view content that they enjoy, advertisements distributed along with the content reach appropriate users based on contextual targeting.

SUMMARY

Content providers, including operators of content distribution systems, can effectively promote content to potential viewers or consumers of the content by providing advertisements, including in the form of recommendations. Many content items can be promoted to a content consumer, such as through recommendations, based on information indicating that the content consumer previously selected related content items for consumption. For example, a book publisher may include recommendations to readers of a book that include information regarding other books thai are available by the same author, or other books in a series. Similarly, previews for new movies may be shown before a movie is shown. In a television context,

recommendations for products, including television programs, can be selected for distribution to a television viewer based on historical viewing habits.

A computer system can be used to automatically generate and distribute content item recommendation information to television viewers in response to viewing activity of the television viewers, For example, recommendations of television programs can be generated based on which program currently has the most viewers. Additionally, recent viewing acti vity of a first user can be used to group the first user with other viewers who have the same or similar recent viewing activity. Recommendations can be generated based on which program currently has the most group members viewing the program. Similarly, programs which are most frequently recorded by a group of users can be recommended for viewing or recording to the members of the group that are not viewing or recording the program, Other content items, such as advertisements, can also be distributed to television viewers based on the viewers' recent viewing activity, such as where an advertisement relating to cookware is shown to a television viewer who recently viewed a program relating to cooking.

In one general aspect, distributing television content includes receiving activity information for multiple users regarding current user activity in a television content distribution system, determining, by at least one processor, current content item viewership information for one or more content items currently being distributed through the television content distribution system, the current content viewership information being determined based on the received activity information, generating, by at least one processor, content item recommendation information, the content item recommendation information being generated based on the current content viewership information, and transmitting the content item recommendation information to a user.

Implementations may incl ude one or more of the following features. For example, the activity information includes channel tune information regarding user channel selection that indicates television channels currently displayed to the multiple users. The content item recommendation information includes information indicating a content item having the greatest current viewership indicated by the current content viewership information. Distributing television content further includes generating profile information for each user based on the activity information, wherein the profile information includes information regarding at least one of a content item that an associated user recently viewed and a television channel to which the associated user recently tuned. The content item recommendation information is generated based on the profile information of the user, and the content item recommendation information includes information indicating a content item having the greatest current viewership among users having profile information similar to the profile information of the user. Distributing television content also includes receiving content item recording information regarding instructions input by the user to record content items, wherein the content item recommendation information is generated based on the content item recording information and the profile information of the user. The content item recommendation information includes an

advertisement, and wherein the advertisement is selected from among candidate advertisements based on advertisement targeting information and the profile information of the user. The advertisement targeting information includes one or more selection criteria and wherein selection of the advertisement includes at least one processor determining that a content item that the user recently viewed meets one or more ad vertisement selection criteria of the advertisement.

In. another general aspect, a system for distributing content includes a receiver that receives activity information for multiple users regarding current user activity in a television content distribution system, at least one processor that determines current content viewership information for one or more content items currently being distributed through the television content distribution system, the current content viewership information being determined based on the received activity information, at least one processor that, generates content item

recommendation information, the content item recommendation information being generated based on the current content viewership information, and a transmitter that transmits the content item recommendation information to a user.

implementations may include one or more of the following features. For example, the activity information includes channel tune information regarding user channel selections that indicates a television channel currently displayed to the multiple users. The content item recommendation information includes information indicating a content item having the greatest current viewership indicated by the current content viewership information. The system further includes at least one processor that generates profile information for each user based on the activity information, wherein the profile information includes information regarding at least one of a content item, that an associated user recently viewed and a television channel to which the associated user recently tuned. The content item recommendation information is generated based on the profile information of the user, and the content item recommendation information includes information indicating a content item having the greatest current viewership among users having profile information similar to the profile information of the user. The receiver receives content item recording information regarding instructions input by user to record content items and wherein the content item recommendation information is generated based on the content, item recording information and the profile information of the user. The content item recommendation information includes an advertisement and wherein the advertisement is selected from among candidate advertisements based on advertisement tai'geting information and the profile information of the user. The advertisement targeting information includes one or more selection criteria and wherein advertisement selection includes at least one processor determining that a content item that the user recently viewed meets one or more advertisement selection criteria of the advertisement.

in another general aspect, distributing content includes receiving activity information for multiple users regarding current user activity in a television content distribution system, generating profile information for each user based on the activity information, wherein the profile information includes information regarding at least one of a content item that an associated user recently viewed and a television channel to which the associated user recently tuned, generating, by at least one processor, content item recommendation information, the content item recommendation information being generated based on the profile information, and transmitting the content item recommendation information to a user.

implementations may include one or more of the following features. For example, the content item recommendation information includes information indicating a content item having the greatest current viewership among users having profile information similar to the profile information of the user. The content item recommendation information includes information regarding a recording suggestion for recording a content item, and the content item

recommendation information is generated based on current content item recording information associated with users that have profile information that is similar to the profile information of the user. The content item recommendation information includes an advertisement that is targeted, to at least one of a recently- viewed content item and a recently- viewed television channel.

The details of one or more implementations are set forth in the accompanying drawings and the description below. Other features will be apparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating a system for managing content distribution.

FIG. 2 is a block diagram illustrating a system for distributing television content.

FIG, 3 is a block diagram illustrating a computer system operable in the system of FIGS. 1 and 2.

FIG. 4 is a block diagram illustrating a process for distributing content.

FIG, 5 is a diagram illustrating a data structure for storing content distribution channel user activity infonnation.

FIG. 6 is a diagram illustrating a data structure for storing profile information.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

FIG, 1 illustrates a system 100 for managing content distribution that includes an analyzer 110 that is operable to generate, for a given viewer, content item recommendation information 150 based on real-time content item viewership information, viewer profile information, and/or advertisement information. The real-time content item viewership information is stored in a real-time viewership information repository 120 and reflects, for each viewer, a content item that is currently being viewed. The viewer profile information is stored in a viewer profile information repository 130 and includes information regarding a recent viewing liistory for each viewer, The viewer profile infonnation can also include, for each viewer, infomiation regarding a profile group to which the viewer belongs based on one or more similarities between the viewer's recent viewing history and the recent viewing histories of the other viewers who belong to the profile group. The advertisement information is stored in an advertisement information repository 140, such as an advertisement index that includes information regarding advertisement creatives and campaigns provided by advertisers, including advertisement targeting information, such as targeted keywords, topics, and/or content, items.

The content item recommendation information 150 provides a recommendation, or a suggestion, of one or more content items that a viewer may enjoy or which may be relevant to one or more of the viewer's interests, For example, the recommendation information 150 can include information regarding viewership statistics for all users, such as a statistic regarding a content item that currently has the most viewers among all content items. Additionally, the recommendation information 150 can include information regarding a content item that currently has the greatest number of viewers from among viewers in a profile group, hi some

environments, such as a television environment, the content item recommendation information 150 can involve content item recording information or reminder information, such as where the content item recommendation information 150 includes a statistic regarding a content item that is currently being recorded, has been scheduled to be recorded, or for which a reminder has been set by the greatest number of viewers, in some implementations, the content item

recommendation information 150 includes information regarding one or more advertisement creatives.

The content item recommendation information 150 can be used, to distribute content items, including advertisement creatives, in the television content distribution system 200 of FIG. 2, The television content distribution system 200 includes a television content delivery platform 210 that is operable to provide television content items, such as television programs and television advertisements, to viewers through set-top boxes 213 via a network 290. For example, the television content delivery platform 210 can include a satellite television delivery system, a co-axial cable television delivery system, a fiber-optic cable television delivery system, and/or a broadcast television delivery system. Trie set-top boxes 213 are network-enabled and are operable to transmit and receive information over the network 290, which can include many forms of wired and wireless networks, and may include the Internet. An individual television viewer is able to control which content items are viewed through a set- top box 213 by inputting channel tune control signals. Additionally, the television viewer is able to control a television recorder of the set-top box 213 by Inputting recording control signals. The set-top boxes 213 are also operable to access menus or other features, such as an on-demand television delivery feature. In some implementations, the recorder and on-demand features are accessed and/or controlled by channel tune control signals. Accordingly, as used herein, channel tune

information can include information regarding control and/or access of the recorder, the on- demand feature, or other feature of the set-top box 213 or the television content delivery platfomi 210.

The television content items are delivered through the television content delivery platform 210 and the set-top boxes 213 according to distribution information stored in a content item distribution information repository 215. The distribution information includes information regarding which content items are to be displayed at each time on each television channel. The distribution information can include television program scheduling information for all of the channels available in the teJesdsion content delivery platform 210. In some implementations, the scheduling information accounts for different schedules associated with different geographical regions, service packages, live programs, or other parameter, such as where programs are time- shifted for different time zones, or where live events deviate from a scheduled airing time or duration.

Advertisement scheduling information can also be included in the distribution

information. In some implementations, an advertiser 220 selects some or all of the scheduling information for advertisement creatives provided by the advertiser 220. For example, the advertiser 220 may arrange for selected television advertisement creatives stored in an advertisement creative repository 225 to be aired before, during, and/or after a selected television program. Additionally, other types of advertisement targeting can be employed by the advertiser 220, such as demographic targeting, contextual targeting, price targeting, and/or combinations thereof. In some implementations, some or all scheduling information can be generated automatically by an advertisement distribution system based on distribution criteria selected by flic advertiser 220 and/or to achieve one or more selected outcome, such as a return on investment greater than a predetermined threshold value or an advertisement cost less than a predetermined maximum, budget. The system 200 also includes a remote recorder controller 230 that is operable to transmit recording control signals to the set-top boxes 213 to control the operation of the television recorders. For example, the viewer can access an interface of the remote recorder controller 230, such as a web page interface, and create recording information that is stored in a recording information repository 235. The remote recorder controller 230 controls the recorder of a set-top box 213 associated with the viewer to record a selected program according to the recording information. The remote recorder controller 230 can also control the set-top boxes 213 to record programs recommended for recording by the analyzer 110.

The set-top boxes 213 are operable to transmit activity information to a viewership information server 240. For example, the set-top boxes 213 can transmit activity information that includes information regarding channel tune control signals input by viewers, recorder control signals, and/or other control signals. In some implementations, the set-top boxes 213 transmit the activity information in real-time, or near real-time, such that only a small delay exists between a channel tune event and receipt of information regarding the channel tune event. For example, the set-top boxes 213 can have a network connection that, is always on, and the activity information can be reported as soon as possible, limited only by the processing capacity of the set-top box and the viewership information server 240, and the latency of the network 290. In some implementations, an amount of delay less than approximately a few seconds is possible from a tirne when a channel tune control signal is input to a set-top box 213 by a viewer to a time when the activity information regarding the charmel time control signal is received by the viewership information sewer 240. As used herein, the terms real-time and near real-time contrast with buffered reporting systems, or other systems in which delay in reporting some activity information is built in to the system, such as dial-up modem reporting systems that connect to the network 290 only periodically to report a batch of information, at least some or whi ch is nearly as old as the period of the reporting schedule.

The viewership information server 240 stores the received activity information in an activity information repository 245, in some implementations, the activity information also includes viewership statistic information, such as information that is derived from the received activity information. For example, the analyzer 110 or the viewership information server 240 can determine which program a viewer is viewing based on a current channel being viewed and the distribution information that indicates which program is being aired on the current channel. The number of current viewers for each program aired can be determined and stored in the activity information repository 245. If some set-top boxes are not configured for real-time or near real-time reporting of activity information, the viewership informa tion server 240 can receive delayed activity mformation and integrate this activity information with the activity information received in real-time, or near real-time. For example, at any time, some fraction of set-top boxes that report periodically will have reported activity information within a

predetermined window of time, such as within the preceding ten minutes. At least some of the activity information reported in the last ten minutes will be as current, or nearly as current, as the real -time activity information reported in real-time by the set-top boxes 213.

The system 200 also includes a profiler 250 that creates and maintains profile information in a profile information repository 255. The profiler 250 is operable to receive the activity mformation from the viewership information server 240, and to determine which channel each user is currently viewing, and which channels each viewer previously viewed, such as recently- viewed channels. The profiler 250 assigns a profile group to each viewer in order to create a record of viewers that have similar recent viewing activity, including current viewing activi ty. For example, the profiler 250 can determine which viewers are currently viewing the same channel or program and/or which users recently viewed the same or similar channels or programs,

Some or all of the components of the system 200, including the analyzer 110, can be formed as or include one or more components of a computer system, such as the computer system 300 illustrated in FIG. 3. The computer system 300 includes one or more processors 310, one or more memory modules 320, one or more storage devices 330, and one or more

input/output devices 340, and a system bus 350. The one or more input/output devices 350 are operable with one or more peripheral devices 360 for inputting signals to and/or for receiving signals from the computer system. 300. One or more of the input/output devices 340 can be operable to allow the computer system 300 to communicate with one or more other computer systems or components over a computer network, such as a network 290 of FIG. 2, which can include the Internet and/or other communications networks.

In use, the television content distribution system 200 can be used to distribute television content according to a process 400, which is illustrated in FIG. 4. For example, the viewership information server 240 receives activity information regarding current user activity from the set- top boxes 213 (401), In some implementations, the viewership intbnnation server 240 creates or updates a searchable data structure that includes channel toe information for each set-top box. As illustrated in FIG. 5, a data structure associated with set-top box 001 includes a list of channel tune control inputs in chronological order, where each entry in the list includes information regarding a channel to which the set-top box was tuned, including channels associated with recorded content and/or on-demand content, and a time at which the control signal was input to the set top box. As shown in the Tune 6 entry, activity information relating to a recording feature, or other features, can be included in the data structure.

Using the received activity information, the viewership information server 240 determines current content item viewership information for each content item currently being viewed by one or more viewer (403). The analyzer 110 receives the current content item viewership information by accessing the searchable data. For example, the number of set-top boxes currently tuned to a channel of the television delivery platform 210 can be determined by the viewership information server 240, and the determined number can be used by the analyzer 110 as the number of viewers that are currently viewing the channel. This number can be determined for each channel and can be adjusted as a running total such that the number is incremented each time a viewer times a set-top box to the channel and decremented each time a user tunes a set-top box to another channel, including when the set-top box is turned off.

The profiler 250 generates profile information using the received activity information

(405). For example, the profiler 250 can access a data structure such as the d ata structure of FIG. 5 for each set-top box, and can assign each set-top box to a profile group based on which television channels or television programs were viewed recently. In some implementations, the profiler 250 can create a data structure like the data structure illustrated in FIG. 6 that includes a list of all of the set-top boxes. For each set-top box included in the list, the data structure includes information regarding recently-viewed channels and a current profile group. A current profile group can be assigned to each set-top box based on an analysis of the recently- viewed channels that are associated with the set-top box. For example, the profiler assigns two set-top boxes to the same profile group based on a determination that the activity information for both set-top boxes indicates that a first channel is currently timed on both set-top boxes, a second channel was watched most recently before the first channel on both set-top boxes, and a third channel was watched most recently before the second channel on both set-top boxes. In some implementations_:, other information can be used to group set-top boxes into profile groups, including channel tune time infonnation and/or program viewership information. Additionally, other criteria can be used in order assign, a set-top box to a profile group, such as viewer demographic matching criteria or criteria regarding geographic proximity.

The analyzer 110 receives advertisement information from the advertiser 220 and/or the television content delivery platform 210 (407). The advertisement infonnation includes targeting information for each advertisement creative that is available for distribution. For example, the advertisement targeting information for an advertisement creative may include information regarding one or more profile group, or type of profile group, that includes viewers to which an advertiser wishes the advertisement creative to be delivered. Additionally or alternatively, the advertisement targeting information for an advertisement creative may include keyword information that is used to identify viewers of television programs and/or channels to which the advertiser wishes the advertisement created to be delivered. In some implementations, the advertisement information can also include demographic targeting information that can be used to identify individuals who should receive the advertisement creatives and/or scheduling information that can be used to whether and when to deliver the advertisement creative to a viewer.

Based on the current activity information, the current content item viewership

information, the profile information, and/or the advertisement information, the analyzer 110 generates content item, recommendation information (409). As discussed above, the content item recommendation information can include information regarding global content item viewership statistics, profile group content item viewership statistics, content item recording statistics, and/or advertisement information. For example, based on the current content item viewership information, the analyzer 110 identifies the content item that is currently being viewed by the greatest number of viewers from among all content items and viewers. Hie analyzer 110 then generates a recommendation to all users to view the identified content item and transmi ts the recommendation to viewers who are viewing a pre-determined channel or set-top box menu (411). In some implementations, the recommendation may be transmitted in the form of a banner that identifies the content item that is currently viewed by the most viewers, and the banner can be displayed on a menu page or area associated with a current most-popular content item. In some implementations, the set-top boxes 213 and/or controllers for the set-top boxes may include a hard or soft control button that is operable to tune the set-top box to a channel on which the current most-popular content item is being aired. Additionally, the recommendation can be transmitted to set-top boxes that are not configured for real-time reporting and/or for delayed reporting. Similarly, the analyzer 1 ί 0 can provide real-time viewership information and/or statistical information to publishers of television content, one or more operators of a television content delivery platform, and/or to advertisers.

Similarly, for each profile group and based on the. profile information, the analyzer 110 identifies the content item that is currently being viewed by the greatest number of viewers from among all content items and all viewers in the profile group. The analyzer 110 then generates a recommendation to all users in the profile group to view the identified content item and transmits the recommendation to viewers that are members of the profile group (413). As discussed above, the recommendation can be transmitted on a pre-determined channel or though a set-top box menu.

The analyzer 110 also identifies the current content item that has the greatest number of viewers who are recording a content item from analysis of current activity information. For example, the analyzer 110 can count the number of viewers who created a scheduled recording for each content item within the most recent pre-determined period of time, such as in the most recent ten minutes. Based on the number of viewers scheduling recordings for each content item within the pre-determined period of time, and optionally based on the viewers' profile information, the analyzer 110 identifies the content item that has the greatest number of scheduled recordings and transmits a recommendation for recording the identified content item (415). In some implementations, the analyzer recommends a program for recording based on a number of viewers who currently have the program scheduled to be recorded, regardless of when the receding schedule was created. For example, the top three most popular programs scheduled to be recorded within an upcoming period of time, such as the upcoming week, can be recommended. Optionally, the profile information and/or other information can also be used to generate the recommendations.

In some implementations, the recording recommendation is transmitted to viewers, and the viewers can schedule a recording of the identified content item if desired. For example, a viewer may access a menu feature in order to receive an indication of the content item that is currently being recorded by the greatest number of viewers who have a profile that is similar to the viewer's profile, if, after receiving the indication, the viewer wishes to schedule a recording of the content item, then the user can create a scheduled recording of the content item by inputting a control signal. In some implementations, a scheduled recording of the content item is created automatically. For example, the analyzer 1 10 transmits content item recording information to the remote recorder controller 230 that identifies the content item and that identifies the viewers for whom the content item is recommended. The remote recorder 230 automatically creates the scheduled recording of the content item based on the content item recording information transmitted by the analyzer 110.

Additionally, the analyzer 110 generates content item recommendation information based on the current activity information and the advertisement information. For example, the analyzer 110 can identify advertising creatives or other advertising content items that are related to one or more content items that a viewer recently viewed. The analyzer then transmits advertisement. information that indicates the identified content items to the television content delivery platfonii 210 (417). Based on the advertisement information, the television content delivery platform 210 can deliver one or more of the advertising content items to the viewer, such as in an advertising area of a menu display of the set-top box, as a banner on a portion of a display of a television channel, or as a television advertisement during an advertisement slot before, during, or after a television program or between television programs, including viewed, recordings of previously- aired programs.

In some implementations, the analyzer 110 identifies the advertising content items that are related to recently- viewed content items based on the advertisement information associated with each available advertising content item. For example, the advertisement information associated with an advertising content item can include targeting information regarding targeted television programs and/or targeted television channels, such as the advertisement scheduling information stored in the content item distribution information repository 215. If a viewer has recently viewed one or more of the targeted television programs or targeted television channels, then the analyzer 110 can identify the content items that are targeted to the program or channel as being recommended for the viewer. A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made witho ut departing from the spirit: and scope of the claims. For example, although various components have been described and illustrated as separate components, one or more of the components, such, as the analyzer 110, the television content delivery platform 210, the remote recorder controller 230, the viewership information server 240, and/or the profiler 250 may be integrated or combined as sub-components of one or more systems or compoiients. Additionally, while the ibregoing description infers user interest and/or preference from system usage information, such as channel tune information, user- provided preference or interest information can also be used in combination with the usage information. For example, user-provided tags, such as favorite tags, or rating selections, such as thumbs-up or a numerical rating selection, can be used to enhance the user profile grouping function and/or in generating recommendations. As another example, in some implementations, set-top boxes that report activity information only periodically can be used in combination with or instead of the real-time reporting set-top boxes.

Accordingly, other implementations are within the scope of the following claims.

Claims

1. A computer-implemented method for distributing television content, the method comprising:

receiving activity information for multiple users regarding current user activity in a television content distribution system;

determining, by at least one processor, current content item viewership information for one or more content items currently being distributed through the television content distribution system, the current content viewership information being determined based on the received activity information;

generating, by at least one processor, content item recommendation information, the content item recommendation information being generated based on the current content viewership information; and

transmitting the content item recommendation information to a user.

2. The computer-implemented method of claim 1 , wherein the activity information includes channel rune information regarding user channel selection that indicates television channels currently displayed to the multiple users.

3. The computer-implemented method of claim 1 , wherein the content item

recommendation information includes information indicating a content item having the greatest current viewership indicated by the current content viewership information.

4. The computer-implemented method of claim 1 , further comprising generating profile information for each user based on the activity information, wherein the profile information includes information regarding at least one of a content item that an associated user recently viewed and a television channel to which the associated user recently tuned.

5, The computer-implemented method of claim 4, wherein the content item

recommendation information is generated based on the profile information of the user, and wherein the content item recommendation information includes information indicating a content item having the greatest current viewership among users having profile information similar to the profile information of the user.

6, The computer-implemented method of claim 4, further comprising receiving content item recording information regarding instructions input by the user to record content items, wherein the content item recommendation information is generated based on the content item recording information and the profile information of the user.

7. The computer-implemented method of claim 4, wherein the content item

recommendation information includes an advertisement, and wherein the advertisement is selected from among candidate advertisements based on advertisement targeting information and the profile information of the user.

8. The computer-implemented method of claim 7, wherein the advertisement targeting information includes one or more selection criteria and wherein selection of the advertisement includes at least one processor determining that a content item that the user recently viewed meets one or more advertisement selection criteria of the advertisement.

9. A system for distributing content, the system comprising:

a receiver that receives activity information for multiple users regarding current user activity in a television content distribution system;

at least one processor that determines current content viewership information for one or more content items currently being distributed through the television content distribution system, the current content viewership information being determined based on the received activity information; at least one processor that generates content item recommendation information, the content item, recommendation information being generated based on the current content viewership information; and

a transmitter that transmits the content item recommendation information to a user.

10. The system of claim 9, wherein the activity information includes channel tune information regarding user channel selections that indicates a television channel currently displayed to the multiple users.

11. The system of claim 9, wherein the content item recommendation information includes information indicating a content item having the greatest current viewership indicated by the current content viewership information.

12. The system of claim 9, further comprising at least one processor that generates profile information for each user based on the activity information, wherein the profile information includes information regarding at least one of a content item that an associated user recently viewed and a television channel to which the associated user recently tuned.

13. The system of claim 12, wherein the content item recommendation information is generated based on the profile information of the user, and wherein the content item

recommendation information includes information indicating a content item having the greatest current viewership among users having profile information similar to the profile information of the user.

14. The system of claim 12, wherein the receiver receives content item recording information regarding instructions input by user to record content items and wherein the content item recommendation information is generated based on the content item recording information and the profile information of the user.

15. The system of claim 12, wherein the content item recommendation information includes an advertisement and wherein the advertisement is selected from among candidate

advertisements based on advertisement targeting information and the profile information of the user.

16. The system of claim 15, wherein the advertisement targeting information includes one or more selection criteria and wherein advertisement selection includes at least one processor determining that a content, item that the user recently viewed meets one or more advertisement selection criteria of the advertisement,

17. A computer-implemented method for distributing content, the method comprising: receiving activity information for multiple users regarding current user activity in a television content distribution system;

generating profile information for each user based on the activity information, wherein the profile information includes information regarding at least one of a content item that an associated user recently viewed and a television channel to which the associated user recently tuned;

generating, by at least one processor, content item recommendation information, the content item recommendation information being generated based on the profile information; and transmitting the content item recommendation information to a user.

18. The computer-implemented method of claim 17, wherein the content item

19. The computer-implemented method of claim 17, wherein the content item

recommendation information includes information regarding a recording suggestion for recording a content item, and wherein the content item recommendation information is generated based on current content item recording information associated with users that have profile information thai is similar to the profile information of the user.

20. The computer-implemented method of claim 17, wherein the content item

recommendation information includes an ad vertisement that is targeted to at least one of a recently- viewed content item and a recently- viewed television channel.