WO2001046843A2 - Intelligent peer-to-peer system and method for collaborative suggestions and propagation of media - Google Patents

Classifications

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  • H04N21/431—Generation of visual interfaces for content selection or interaction; Content or additional data rendering
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  • H04N21/4316—Generation of visual interfaces for content selection or interaction; Content or additional data rendering involving specific graphical features, e.g. screen layout, special fonts or colors, blinking icons, highlights or animations for displaying supplemental content in a region of the screen, e.g. an advertisement in a separate window
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Definitions

• the present invention relates to automated systems and methods for recommending items to users. More particularly, the invention relates to an automated peer-to-peer system and method for collaborative suggestions and propagation of media.
• 5,583,763 (December 10, 1996) describe a system for determining selections that a user is likely to be interested in. A determination is made, based on a user's prior indicated preferences, designated in a preferences list. The list is compared with other users' lists. When a large number of matches is found between two lists, the unmatched entries of the other user's list are extracted.
• these implementations require a client-server network environment and a stateful connection between the client and the server. Correlations are calculated on the server, based on data periodically supplied by the client, necessitating monitoring of the client state, thereby raising confidentiality concerns. It would be desirable to provide a collaborative suggestion system in which a stateful connection between client and server is unnecessary, thus reducing concerns about user privacy.
• Gnutella Support Pages http:// gnutella.wego.com (no date) describe a peer-to-peer network composed of a multiplicity of Gnutella clients, in which the client software includes an integrated search engine and file server.
• the Gnutella network changes constantly, according to the number of Gnutella clients that are on the network at any given time. No server exists, and the network infrastructure is provided by a publicly accessible network, such as the Internet. In order to access the Gnutella network, a user must have the network address of at least one other Gnutella client that is currently connected.
• a user in search of a particular information object, a digital music file, or a recipe, for example, may send a query over the network.
• the query is passed from client to client until the object is located or the query is terminated.
• the query process is user-initiated: queries are formulated and launched by the user with no automation of the query process.
• the Gnutella network is primarily directed to file sharing, in which media content items are shared or propagated between users. There is no capability of comparing user profiles between clients in order to generate collaborative suggestions.
• the Gnutella network is concerned exclusively with the peer-to-peer network paradigm.
• a network-based intelligent system for predicting ratings for items of media content according to how likely they are to appeal to a user provides a parallel, peer-to-peer system and method for collaborative suggestions and propagation of media.
• clients contact a server on a periodic basis, independent of the user.
• clients also make opportunistic use of the network connection to interact with one another in peer-to-peer fashion.
• the server organizes clients into groups and provides each client within a group with the network address of all other clients in the group.
• An originating client queries a targeted peer b y transmitting a list indicative of its user's preferences.
• the targeted peer evaluates the similarity of the transmitted list with a list of its own.
• the comparison continues in an interactive fashion.
• the exchange of information proceeds in a stepwise manner, with the originating client evaluating similarity at each stage. If the two clients are dissimilar, either the originating client or the targeted peer may terminate the query, depending on the stage of the interaction; or the targeted peer may route the query to a second targeted peer.
• the interaction culminates in the originating client downloading content listings from the targeted peer to generate suggestions for their user. In addition to the lists of preferences, the originating client may download actual content items from the targeted peers.
• Figure 1 provides a block diagram of a network-based video recording system, according to the invention.
• Figure 2 provides a block diagram illustrating peer-to-peer interaction among the clients of the system of Figure 1 , according to the invention.
• the co-pending application, K. Ali, et al., supra, provides an intelligent, distributed system for recommending items of content to a user, jased on the user's expressed preferences.
• the described system shown here in Figure 1 , employs a client-server network architecture in which each of a plurality of clients is periodically in contact with the server. In the described syste m, all interaction occurs between the client 11 and the server 10, as Figure 1 shows.
• the current invention extends the suggestion generating capability of the previous system by making opportunistic use of the network connection to provide peer-to-peer interaction among the clients, so that the knowledge embodied on each of the clients is further leveraged by exchanging suggestions and content directly between clients, in peer-to-peer fashion.
• the server 10 is operative to organize simultaneously connected clients 11 into one or more groups 20, whereupon the server provides each client within a group 20 the network address of all other clients in the same group. Beyond this initial function, all interaction occurs among the clients, independently of the server, in parallel with the client-server interaction.
• the client is in contact with the server for a short period of time to download current program guide data and to exchange data with the server for the purpose of generating collaborative suggestions.
• the selection of clients connected to the network at any given time is apt to be fairly random, so that, over time, each client is randomly exposed to a large population of other clients, thereby enabling a rich exchange of information.
• While the preferred embodiment of the invention employs the Internet as its network infrastructure, other publicly accessible telecommunications networks would also be suitable: for example, a cable television network.
• the presently preferred embodiment of the invention employs a dial up network connection.
• hardwired connections for example, coaxial or fiber optic cable would also be suitable, particularly in the case of broadband implementations of the invention.
• wireless connections would also be consistent with the spirit and scope of the invention.
• the type of media involved is highly variable. While the present embodiment of the invention is concerned primarily with various types of television programming, the invention also finds application with text files, web sites, books, digital music; in short, almost any type of digital media.
• PEER-TO-PEER SUGGESTION SYSTEM In the invented system, a pool of client devices is simultaneously connected to a network.
• the presently preferred embodiment of the invention incorporates clients of a distributed personal video recording system, in which every client is a dedicated video recording unit. Resident on every client are several lists that are highly indicative of a user's preferences. Minimally, the lists include: • Lists of recorded items that are currently available for viewing;
• clients connect to a central server periodically.
• server In a larger community of users, there is a constant group of clients connected to the server, dynamic in nature, in which clients constantly come and go.
• the server organizes clients by connection time, so that clients that have connected recently are all placed in the same group; additionally, the server controls group size. A larger group size is preferable in order to maximize the opportunity for interaction among clients.
• the server provides each client in the group network with network addresses to all other clients in the group. Following group formation, each client is free to contact any other client in the group directly.
• the lists mentioned above may be hundreds or even thousands of items in length. Thus, exchanging an entire list or set of lists between clients may be impractical, particularly in the case of a narrowband dial up network connection. Therefore, a variety of methods have been provided to facilitate peer-to-peer interaction in a manner that economizes on time and network resources.
• Each client has one or more compact lists of items that are highly representative of the user's preferences. These may be the list of series to record, or the list of items currently available. Each of them armed with such a list, an originating client (A) and targeted client (B) interact as follows:
• Client A sends a query to B, consisting of the list, and the size of the other lists it has to exchange.
• Client B receives the query and compares A's list with its own corresponding list to determine the number of elements it shares in the list with client A. It now computes the similarity between A and B, according to an algorithm, resident on both A and B, in which:
• Similarity Number of elements in common between A and B / number of elements reported by A. Similarity is expressed as a value a range of approximately 0 to 1. Client B may respond in one of several ways: If the similarity value is less than a first predetermined threshold, it can respond to A that B has nothing that A might be interested in.
• B can respond that A should be interested in B.
• B sends more information with the response that indicates relative sizes of B's lists, compared to A's. For example, B might say "Yes, you are 80% interested in me, and I have twice the number of ratings data that you have, and a third your size of recording history". Client A's response is described further below.
• B may pass the query from A to a second targeted peer. Upon redirecting, a reference to B is appended to the query so that successive peers know not to pass the query to B. It also allows A to know which clients have evaluated its query when it receives a response. In any further queries originated by A, it will then skip over those that have already been queried.
• Client A receives a positive response from a targeted peer, comprising similarity values, relative list sizes and a listing of peers that have evaluated the query, further interaction is determined by A. If A determines that the similarity value is less than a second predetermined threshold, A terminates the query. Having terminated the query, A may direct additional queries to other clients within the group that have not yet been queried. If the similarity value exceeds the second threshold, client A evaluates which lists it wants to retrieve from the responding peers. If the relative size of any of the other lists is sufficient, A may request the complete list from the responding peer. For example, A may request a full recording history from one respondent and a complete list of ratings from another. Upon receiving the lists, A further evaluates the lists for correlation, and uses them to generate collaborative suggestions for the user. Appropriate methods for computing correlation and generating collaborative suggestions are described in the co-pending application previously mentioned, K. Ali, etal., supra.
• Client A takes a block that includes the first n consecutive items in it's list and transmits it to B.
• B receives the list and determines matching items; and transmits a list of matching items to A.
• A creates a temporary matching items list, where it saves the list received from B, and transmits another block of n items to B.
• B responds with another list of matching items, which A adds to its temporary list. With each succeeding response from B, A evaluates what portion of the total number of items shared with B the two peers have in common. When enough items have been tested by repeating the above steps, the ratio remains relatively constant from one iteration to the next. At that point, the similarity value for the partial data is representative of the similarity value for the entire list. The query then proceeds as described above, in which A requests from the target the lists it wishes to receive.
• a and B can determine if the correlation is high enough to proceed with sharing full lists or to terminate the connection, in the event of an insufficient correlation.
• each client within a group is both an originator and a target, wherein each client directs queries to other clients and receives queries from other clients.
• client-server system of the copending application and the present peer-to-peer system have been treated as parallel systems for the sake of description, the skilled practitioner will appreciate that they are, in fact, one system having parallel functionalities.
• the client units interact with the server in the usual client-server fashion, and simultaneously also have the peer-to-peer functionality herein described.
• the invention is implemented using conventional techniques well known to those skilled in the art of software engineering and computer programming.
• the network implementation will be apparent to those skilled in the design and administration of data networks.
• connection is by means of fiber optic or coaxial cable, DSL, T1 or T3, or the like, enable the peer-to-peer sharing of the underlying content, as well as the user preference files.

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• Engineering & Computer Science (AREA)
• Multimedia (AREA)
• Signal Processing (AREA)
• Databases & Information Systems (AREA)
• Theoretical Computer Science (AREA)
• General Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• Human Computer Interaction (AREA)
• Data Mining & Analysis (AREA)
• Social Psychology (AREA)
• Health & Medical Sciences (AREA)
• General Physics & Mathematics (AREA)
• General Health & Medical Sciences (AREA)
• Software Systems (AREA)
• Computer Networks & Wireless Communication (AREA)
• Marketing (AREA)
• Business, Economics & Management (AREA)
• Probability & Statistics with Applications (AREA)
• Computational Linguistics (AREA)
• Computing Systems (AREA)
• Information Transfer Between Computers (AREA)
• Computer And Data Communications (AREA)
• Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

Description

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Cited By (93)

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Citations (1)

• 2000
  • 2000-12-21 WO PCT/US2000/035035 patent/WO2001046843A2/en active Application Filing
  • 2000-12-21 AU AU27351/01A patent/AU2735101A/en not_active Abandoned

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