Patent Grant
8386318
The present invention relates to peer interactions in general, more particularly, peer interactions through mobile phones. Still more particularly, the present invention is related to a system and method for supporting peer interactions in a particular domain such as classified ads.
The business models involved in classified ads are based on click-based revenue and sale-based revenue. In a click based revenue, the service provider providing classified ads service earns revenue for every click on an ad from the sponsor of the ad. On the other hand, in a sale-based revenue, the provider earns whenever a user buys the product endorsed by an ad from the classified ads portal. Obviously, returns are higher in the sale based revenue model and in order to reduce risk due to non-sale, both the models are combined and adapted in practice.
When a user clicks on a classified ad that is a part of a classified ads portal, various kinds of promotional information can be provided to the user. These kinds of promotional information are largely provided by the ad sponsors. Typically, the information provided by the sponsors is positively positioned with respect to the products of the sponsors. Hence, there is a bit of hesitation in accepting all of the information provided by the sponsors. In order to reduce the bias and enhancing of the utility value for the users, additional information sources need to be identified. One of the major issues regarding these additional information sources is the handling of spam sources. A way of identifying of these additional sources is to look for product champions within a user community and can be based on the information such as the following: People who own the product, Duration of ownership, Enquiries made, Complaints made, Enquiry duration, User feedback, Reaction to promotional offers, Products of same brand bought, User location, and General information such as likes and dislikes. The behavior of a typical user could be categorized along the following phases: Buy-Phase, Use-Phase, Advertise/Deny-Phase, and is summarized in the table below:
Information similar to the one contained in the above table is used in identifying the potential users who could provide useful information to the other peers.
U.S. Pat. No. 7,159,784 to Lapstun; Paul (Balmain, AU), Lapstun; Jacqueline Anne (Balmain, AU), Silverbrook; Kia (Balmain, AU) for “Method and system for searching classified advertising” (issued on Jan. 9, 2007 and assigned to Silverbrook Research Pty Ltd (Balmain, AU)) describes methods and systems that relate to listing classified advertising via interface surfaces printed with information and coded data. The coded data, encoded visibly or invisibly, may be queried by an appropriate sensing device. The sensing device communicates with a computer system. Together, the interface surfaces, sensing device and computer system are capable of effecting classified listing search transactions over a network.
U.S. Pat. No. 7,143,075 to Chickering; David Maxwell (Bellevue, Wash.), Heckerman; David E. (Bellevue, Wash.) for “Automated web-based targeted advertising with quotas” (issued on Nov. 28, 2006 and assigned to Microsoft Corporation (Redmond, Wash.)) describes systems and methods that can be used for targeted advertising. The system determines where to present impressions, such as advertisements, to maximize an expected utility subject to one or more constraints, which can include quotas and minimum utilities for groups of one or more impression.
U.S. Pat. No. 20080040216 by Dellovo; Danielle F.; (North Andover, Mass.) entitled “Systems, methods, and apparatuses for advertisement targeting/distribution” (filed on May 14, 2007) describes apparatuses, systems and methods for selecting a base data entry for distribution with a content provider's requested content. The system processes the advertisement request to extract content provider distribution parameters and/or web user data characteristics, if they exist. This data may be processed to create an initial a pool of potential base data entries, one (or more) of which will be distributed to a content provider.
U.S. Pat. App. No. 20070099701 by Simon; Daniel; (San Diego, Calif.); Westling; Mark Ford; (Chevy Chase, Md.); Wherry; Phillip; (Vienna, Va.) entitled “Method and system to facilitate interaction between and content delivery to users of a wireless communications network” (filed on Apr. 7, 2006) describes a system and method of creating affinity groups of portable communication device users, and distributing targeted content to said users.
U.S. Pat. App. No. 20070067405 by Eliovson; Joshua M.; Roseland, N.J.) entitled “Moderated anonymous forum” (filed on Sep. 20, 2006) describes a moderated forum that provides an arena for anonymous public discussions in and among a given on-line or virtual community as well as discussions between separate on-line or virtual communities.
“Comprehensive Analysis of Web Privacy and Anonymous Web Browsers: Are Next Generation Services Based on Collaborative Filtering?” by Gulyás, G., Schulcz, R., and Imre, S. (appeared in the Proceedings of the Second Workshop on Sustaining Privacy in Autonomous Collaborative Environments (SPACE 2008), Jun. 17, 2008) presents main web privacy issues, complex preventive solutions, and anonymous web browsers, in several aspects including a comprehensive taxonomy. Also, suggests a next generation anonymous browser scheme based on collaborative filtering concerning issues of semantic web.
“A Profile Anonymization Model for Privacy in a Personalized Location Based Service Environment” by Shin, H., Atluri, V., and Vaidya, J. (appeared in the Proceedings of the Ninth International Conference on Mobile Data Management (MDM 2008), Apr. 27-30, 2008) addresses the problem of privacy preservation via anonymization that guarantees anonymity even when profiles of mobile users are known to untrusted entities.
“Towards Anonymous Mobile Community Services” by Demestichas, K. P., Adamopoulou, E. F., Markoulidakis, J. G., and Theologou, M. E. (appeared in Journal of Network and Computer Applications, April 2008 (available online at http://www.sciencedirect.com/science/journal/10848045) describes an innovative concept of anonymous mobile community services and thoroughly defines and describes a robust platform targeted for their deployment.
“Introducing Anonymous Real-Time Mobile Community Services” by Adamopoulou, E., Demestichas, K., Dessiniotis, C., Markoulidakis, J., and Theologou, M. (appeared in the Proceedings of the 16th IST Mobile and Wireless Communications Summit, 2007, 1-5 Jul. 2007) analyzes the concept of anonymous real-time mobile community services that enables the real-time collection of information residing in a community of mobile terminals, which can then be processed and delivered to a service requesting terminal.
“A secure and privacy-preserving web banner system for targeted advertising” by Claessens, J., D´iaz, C., Faustinelli, R., and and Preneel, B. (appeared as COSIC internal report, January, 2003) proposes a solution for privacy-preserving targeted advertising through web banners and the solution allows users to make a balance between the exposure of their privacy and the personalization of advertisements.
The known systems do not address the various issues related to the enabling of peer support in an anonymous manner in helping users to quickly take decisions while browsing classified ads. The present invention provides a system and method to enable selecting of right ads for displaying to the users, selecting of right peer users for providing additional information, and supporting of anonymous peer interactions.
The primary objective of the invention is to enable selecting of right content for to be displayed on a user's mobile phone, selecting of right peers, and facilitating of anonymous peer interactions.
One aspect of the system is to perform user grouping in order to identify peer user groups.
Another aspect of the invention is to perform ad grouping in three different ways, namely, generic ad grouping, meta ad grouping based on meta-descriptions, and custom ad grouping based on a user and an ad.
Yet another aspect of the invention is to display the ads in a radial manner based on a user grouping and a plurality of ad groupings.
Another aspect of the invention is to form ad specific peer user groups.
Yet another aspect of the invention is to facilitate real time conversational feedback to support anonymous peer interactions.
a provides another approach for Ad Group Generation.
b provides an additional approach for Ad Group Generation.
a provides an additional approach for Ad Display.
a provides additional details related to RTCF Session Management.
b provides some more details related to RTCF Session Management.
Consider a scenario of a mobile user accessing a web portal of classified ads. The user's intent is to browse the portal with one or more things in mind, locate the information about them, discuss offline with friends and colleagues, and take a buy/no-buy decision. The increase in m-commerce transactions has lead to the buying of products through classified ads and auction portals. In order to reduce the time cycle involved in decision making, especially if the access is through a mobile phone, it is essential to provide right information and right support system for decision making. As users login into a portal, there is an opportunity to collect the information about the users' profile and this would help in moving towards the objective of cycle time reduction. In a situation where a particular user has logged in several times to know about a product though the ad in a classified ads portal, the subsequent login gives an opportunity to restructure the display so that what is mostly of interest appear sooner and less interesting ads appear later. Further, if a particular peer user group is identified keeping in mind the user and the product of interest, the user could interact with the group to obtain more information that could help in decision making. The supporting of peer user group interactions requires (a) the identification of the right puggys (the peer user group members) and (b) the protection of the privacy of the puggys and the user who is seeking the support information. These two aspects together ensure a free flow of right information to help in decision making.
Ad Description is as follows:
User Description is as follows:
Input: SU—a set of users; Output: GSU—a set of groups of users;
For each user U in SU,
For each user U1 in SU,
A way to Update G with U would be to add UA to GA wherein G is a set of users and the associated GA is the set of ads based on users in G;
A way to measure distance between U and G would be based on the intersection between UA and GA;
Input: SA—a set of ads; Output: GSA—a set of groups of ads (generic ad groups);
Step 1: Select an Ad Ai from SA; Set SAi′ EMPTY;
Step 2: Let UAi be the set of users who have shown interest in Ai;
Step 3. For each user U in UAi,
Step 4: Make Ai part of SAi′; Make SAi′ a part of GSA; Remove SAi′ from SA;
Step 5: Repeat from Step 1 until SA is EMPTY;
a provides another approach for Ad Group Generation. This additional approach is based on meta-description of ads to generate meta ad groups. Each ad is provided with a meta-description, say in terms of key-atomic concepts. The objective is to group ads based on their meta-description so as to be able to identify similar ads;
Input: SA—a set of ads; Output: DGSA—a set of meta ad groups
Step 1: Select an Ad A from SA;
Step 2: Determine a group G in DGSA whose distance with A is minimum as compared with the other groups in DGSA and is less than a pre-defined threshold;
Step 3: If such a group can be found, make A part of the G and update G;
Step 4: Otherwise, create a new group G with A as its element, make G a part of DGSA, and update G;
Step 5: Repeat from Step 1 until all elements of SA are selected;
A way to update G with A would be obtain the meta-description of A and Meta-description of G, and combine them based on term-frequency analysis;
A way to compute distance between A and G would be obtain the intersection of the meta-description of A and meta-description of G;
b provides an additional approach for Ad Group Generation. This ad grouping is based on a particular user U and a particular ad A to generate custom ad groups. The objective is to identify a set of ads based on a user and an ad.
Input: User U and Ad A clicked by U;
Output: Custom-Specific Ad Grouping;
Obtain the set of ads SSA that are similar to A; SSA belongs to DGSA;
Obtain the set of users SSU that are similar to U; SSU belongs to GSU;
Obtain the set of ads SOA that are also clicked by U;
SSA provides ads that are most similar to A;
Order SSA on hits and recency;
SSU provides users that are most similar to U;
For each user U in SU,
Order SSUA on hits and recency;
Order SOA based on hits and recency;
Ad Display on User Login;
Input-Logged in User U; Output-Display structure of Ads
Case: U with Open Ads
Case: U with no Open Ads
Case: U is a first time user
a provides an additional approach for Ad Display. When the selected relevant ads get scrolled out, it is necessary to select further ads. This further selection is independent of the three kinds of users discussed with respect to
For each GA in GSA,
For each GA obtained in the order of Popularity Factor
Depending on the scroll direction,
Input: An Ad A; Output: PUGa—List of users related to A;
Obtain for each user U the following:
Obtain Min and Max bounds on PUGa;
Obtain Number of CS with respect to A;
Let W1 be the weight associated with NC, W2 with FC, W3 in NI, W4 with NP, W5 with TT, W6 with NB, and W7 with RU;
Across all users, obtain Max-NC and Min-NC, Max-FC and Min-FC, Max-Ni and Min-NI, Max-NP and Min-NP, Max-TT and Min-TT, Max-NB and Min-NB, Max-RU and Min-RU;
For each User U,
Compute Ur as (W1*(NC−Min-NC)/(Max-NC−Min-NC))+(W2*(FC−Min-FC)/(Max-FC−Min-FC))+(W3*(NI−Min-NI)/(Max-NI−Min-NI))+(W4*(NP−Min-NP)/(Max-NP−Min-NP))+(W5*(TT−Min-TT)/(Max-TT−Min-TT))+(W6*(NB−Min-NB)/(Max-NB−Min-NB))+(W7*(RU−Min-RU)/(Max-RU−Min-RU));
Rank users on their rating Ur;
Select a pre-defined number of users that is less than Max, with each selected user satisfying the following:
If number of users is <Min, then add randomly selected users;
Depending on the policy, add appropriate number of CS staff,
RTCF:
On Clicking on Ad A by User U,
a provides additional details related to RTCF Session Management.
RTCF: (Contd.)
On Push To Talk by a user X (U or any from Peer User Group),
On completion of an anonymous voice conversation,
Enable Anonymous Voice Communication for user X,
A way to achieve Step 2 and 3 would be to use an automatic speech recognizer to generate textual equivalent of voice signals S, and subsequently use a text to speech synthesizer with respect to the generated text data to obtain synthetic signals SS that is equivalent of the voice signals S. This is based on the observation that the anonymous peer support is based on speech communication.
On User U hangs up,
b provides some more details related to RTCF Session Management.
On User U initiating a purchase of Product P associated with ad A:
System Moderator:
Thus, a system and method for anonymous peer support system is disclosed. Although the present invention has been described particularly with reference to the figures, it will be apparent to one of the ordinary skill in the art that the present invention may appear in any number of systems that supports providing of right information, identification of right peer group, and facilitating of anonymous peer interactions. It is further contemplated that many changes and modifications may be made by one of ordinary skill in the art without departing from the spirit and scope of the present invention.
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| Number | Date | Country | |
|---|---|---|---|
| 20100167709 A1 | Jul 2010 | US |
