US20120035978A1 - System for and Method of Determining Relative Value of a Product - Google Patents

System for and Method of Determining Relative Value of a Product Download PDF

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Publication number
US20120035978A1
US20120035978A1 US12/894,100 US89410010A US2012035978A1 US 20120035978 A1 US20120035978 A1 US 20120035978A1 US 89410010 A US89410010 A US 89410010A US 2012035978 A1 US2012035978 A1 US 2012035978A1
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product
value
representative
purchasing activity
activity
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II Raymond Lee Haynes
Dave Nelson
Robb Smigielski
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COPIA INTERACTIVE LLC
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Priority to US12/894,100 priority Critical patent/US20120035978A1/en
Assigned to COPIA INTERACTIVE, LLC reassignment COPIA INTERACTIVE, LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: HAYNES, RAYMOND LEE, II, SMIGIELSKI, ROBB, NELSON, DAVE
Publication of US20120035978A1 publication Critical patent/US20120035978A1/en
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00Handling natural language data
    • G06F40/10Text processing
    • G06F40/166Editing, e.g. inserting or deleting
    • G06F40/169Annotation, e.g. comment data or footnotes
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/048Interaction techniques based on graphical user interfaces [GUI]
    • G06F3/0481Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
    • G06F3/0483Interaction with page-structured environments, e.g. book metaphor
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00Handling natural language data
    • G06F40/10Text processing
    • G06F40/166Editing, e.g. inserting or deleting
    • G06F40/171Editing, e.g. inserting or deleting by use of digital ink
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201Market modelling; Market analysis; Collecting market data

Definitions

  • the present invention relates to a system for and a method of determining the relative value of a product. More particularly, the present invention relates to a system for and a method of determining the relative value of a product based on behavior of consumers of the product.
  • the present invention provides a system for and a method of determining relative value of a product.
  • a value is obtained that is representative of purchasing activity directed toward a product.
  • This value is stored in a computer-readable storage medium.
  • a value is obtained that is representative of non-purchasing activity that is directed toward the product.
  • This value is also stored in computer-readable memory.
  • the value representative of purchasing activity and the value representative of non-purchasing activity are combined and the result is displayed on a display screen.
  • a result of the combining can be scaled and rounded so that the result is a whole number between 0 and 99. This number is referred to herein as a “Community Value” that reflects the relative value placed on the product by members of a community.
  • FIG. 1 illustrates a system that may be used to determine the relative value of a product in accordance with an embodiment of the present invention
  • FIG. 2 illustrates a flow diagram of a method for determining the relative value of a product in accordance with an embodiment of the present invention.
  • the present invention is directed toward a system for and a method of determining relative value of a product (referred to herein as “Community Value”). It is believed that the “true” value of a product can be better defined when the result is attained with a community focus. For example, a religious text normally has a low monetary value, while conversely is may have a very high value among members of a particular community.
  • the Community Value for a product preferably reflects non-purchasing, social activity directed toward the product (e.g., discussions, ratings, group associations, reviews, recommendations) as well as purchasing activity directed toward the product.
  • FIG. 1 illustrates a system 100 that may be used to determine the relative value of a product in accordance with an embodiment of the present invention.
  • a server 102 is communicatively coupled to a plurality of remote devices 104 , 106 , and 108 via a network 110 .
  • the a server 102 includes a processor 112 , a database 114 and input/output devices 116 , which may include a display, a keyboard, a mouse, and a network interface.
  • the network 110 may include, for example, a local area network, an intranet, and/or a wide area network, such as the Internet.
  • the remote devices 104 , 106 , 108 may be implemented as various computing devices, such a desktop or portable personal computer, a “smart” phone, e-book reader device, a PDA or other device.
  • a user accesses the server 102 by using a remote device 104 , 106 or 108 .
  • the server 102 may host website portal which can be accessed by users of the devices 104 , 106 or 108 .
  • the remote devices 104 , 106 , 108 may communicate with the server 102 and with each other by wireless or wired connections. While a single server 102 is shown, it will be understood that the functions of the server 102 may be performed by multiple servers or by a distributed server system.
  • the products include digital content, such as a documents which may include text, video, images, audio and combinations thereof.
  • a document may include both text and images.
  • the documents can be electronic books (also referred to as e-books). Users can access the products by downloading and/or viewing the products, and can perform other actions described herein, via a website which may be hosted by the server 102 .
  • the products can include other types of products, such as paperback and hardbound books. In this case, the products may be ordered via the website.
  • each user can engage in other interactions, including the following:
  • Each user preferably has a “library.”
  • the library for a user includes a list of products that have been selected by the user (e.g., by purchasing the product or by indicating a preference for the product by adding it to his or her library).
  • users can join groups via the website and each group may have a library.
  • the library for a user or a group reflects product preferences of the corresponding user or group.
  • purchased products are automatically added to a user's library.
  • users and groups can also manually add a product to their libraries without actually purchasing it.
  • the libraries and identifications of their contents are preferably stored in computer-readable storage medium at the server 102 .
  • each user preferably has the ability and facility to apply a personally-determined rating to a product. This can be based on scale of one to five, where a higher number indicates a higher rating (one is the lowest rating and five is the highest).
  • the ratings for a product can be averaged to determine a collective average rating of the product.
  • the ratings for products, or at least a parameter that is representative of average of the ratings for each product, is preferably stored in computer-readable storage medium at the server 102 .
  • Each individual user also preferably has the ability and facility to initiate or participate in on-line discussions with other users where the discussions are related to a particular product.
  • the number of discussions that refer to product can be determined, for example, by a user that initiates a discussion indicating the particular product to which the discussion applies. Other users may then add to the discussion.
  • the discussion threads and the number of discussions that refer to a particular product (or other information that is representative of discussion activity) are preferably stored in computer-readable storage medium at the server 102 .
  • Each individual user preferably has the ability and facility to create or become a member of a group.
  • Each group may have a corresponding group library.
  • Group membership information such as the number of groups that have a particular product in their library, is also preferably stored in computer-readable storage medium at the server 102 .
  • Each individual user preferably also has the ability and facility to recommend a product to another individual user or to a group for addition to that user's or group's library.
  • the recommendations and the number of times a particular product has been recommended (or other information that is representative of recommendation activity) are also preferably stored in computer-readable storage medium at the server 102 .
  • a recommendation may be in the form of a binary indication as to whether the user recommends the product.
  • Each individual user also preferably has the ability and facility to write a personal review of a product.
  • the reviews and the number of reviews a product has received is also preferably stored in computer-readable storage medium at the server 102 .
  • a review may be in the form of text that indicates one or more reasons why the user liked or disliked the product.
  • a relative value of a product can be determined from purchasing activity as well other user interactions. This information is used to assign a value to a product relative to other products.
  • the determined value of a product is referred to herein as the “Community Value” of the product.
  • the Community Value is a “weight” or “value” assigned to a product that can be used to show a user in a quick glance if the product is considered “good” by a community as a whole.
  • the Community Value for a particular product preferably takes in account two principle factors.
  • the first factor is determined from purchasing activity directed toward the particular product. For example, this can be a number of times the particular product has been purchased by individuals within the community or by the number of individual's whose libraries than contain the product.
  • the second factor is determined from non-purchasing activity directed at the product by the community.
  • the community for a particular product (also referred to as “users”) may refer to a group consisting of all purchasers and potential purchasers of the product, or to a subset of such persons.
  • the community for a particular product may include all persons who have signed up at a website as members of the website's community or may include only a subset of these persons (e.g., only persons who have indicated a preference for a certain type of product or only persons who purchased a particular product or type of product in the past may be members of the community for a particular product).
  • FIG. 2 illustrates a flow diagram of a method 200 for determining the relative value of a product in accordance with an embodiment of the present invention.
  • a value is obtained that is representative of purchasing activity directed toward a product. This value can stored in a computer-readable storage medium, such as in the server 102 ( FIG. 1 ).
  • a value is obtained that is representative of non-purchasing activity that is directed toward the product. This value can also be stored in the computer-readable memory.
  • the value representative of purchasing activity and the value representative of non-purchasing activity are combined.
  • This result is displayed on a display screen, such as a display screen of a remote device 104 , 106 or 108 .
  • the result of the combining can be scaled and rounded so that the result is a whole number between 0 and 99. This number is referred to herein as a “Community Value” that reflects the relative value placed on the product by members of a community.
  • the first factor which represents purchasing activity directed toward a particular product, may be determined as a ratio of the number of times that the particular product has been purchased by members of the community compared to the number of times that the best-selling product has been purchased by members of the community.
  • the first factor may be determined as a ratio of the number of times that the particular product has been included in the library of individual members of the community compared to the maximum number of times that any product has been included in individual member's libraries.
  • a record that is representative of the number of times that each product has been purchased (or other information that is representative of purchasing activity) is preferably stored in computer-readable storage medium at the server 102 .
  • the second factor may be determined based on social interactions among users in the community that are directed toward the product, such as ratings given to the product by members of the community, discussions about the product, inclusion of the product in a group library, recommendations for the product, and reviews of the product These interactions represent the popularity of the product among the community.
  • the Community Value is calculated for a product every 24 hours. However, a different frequency of calculation can be selected. For example, the frequency of the calculation may be increased if social activity increases within the community.
  • Each product is preferably given an updated Community Value during every calculation run.
  • Data used for determining the Community Value can be restricted to a certain time period (e.g., by only considering activity within the prior 12 months). Alternatively, the data can encompass all available data.
  • all historical Community Values, and possibly also the underlying data are preferably stored in computer-readable storage medium at the server 102 for future use, such as for data mining for additional features (e.g. for presenting historical graph of a product's Community Value index).
  • the first and second factors may then be weighted and combined.
  • the Community Value or “CV” can be obtained using the following formula:
  • Oa is an ownership average percentage
  • Ow is a weighting factor for ownership
  • Pa is a popularity average percentage
  • Pw is the weighting factor for popularity.
  • the ownership average percentage Oa preferably takes into account an average percentage of ownership for the product among “active” members of the community as well as ownership among all members of the community.
  • “active” members of the community can be members that have logged in within particular time period (e.g. within the last 7 days).
  • Oa can be given as follows:
  • Oc is a ratio of the current product ownership compared to the product that has the most ownership (i.e. the best-selling product) and Om is a ratio of the current product ownership among active users compared to the product that has most ownership among active users.
  • ownership refers to purchases of the product and may also include instances in which the product is included in an individual user's library without it having been purchased by the user. For example, if the particular product has been purchased 1500 times and the product that has been purchased the most has been purchased 2486 times, Oc can be determined as 1500/2486 or 0.6034.
  • S ⁇ L[B] ⁇ is current product ownership count among active users and S ⁇ L[A]x ⁇ is a maximum ownership count among all products in all Libraries for only the active users.
  • Oc and Om are equally weighted in the average Oa. However, they may be weighted differently. For example, Om may be weighted more heavily than Oc so that activity of active users has a greater influence on the resulting Community Value. Alternatively, ownership average percentage Oa can be based only on Oc or only on Om. However, taking both Oc and Om data into account is preferred since it allows the Community Value to fluctuate based on the most-current activity, while retaining some residual value from historical activity.
  • the popularity average percentage Pa is preferably based, not on purchases, as is the ownership percentage Oa, but on social interactions among users in the community that are directed toward the product. For example, these can include, one or more of the following: ratings of the product, discussions about the product, inclusion of the product in a group library, recommendations for the product, and/or reviews of the product.
  • the popularity average percentage Pa may be determined as an average of several values that reflect these interactions among users in the community. Specifically, the popularity average percentage Pa may be determined as
  • Ra is an average rating of the product
  • Dp is a ratio of the current product discussion topic associations compared to the product that has the most discussion topic associations
  • Gp is a ratio of the current product group associations compared to the product that has the most group associations
  • Ep is a ratio of the current product recommendations compared to the product that has the most recommendations
  • Vp is a ratio of the current product reviews compared to the product that has the most reviews.
  • the average rating of the product the ratings given to the product by all users can be averaged.
  • the average may be multiplied by 0.2 to obtain a number between 0.0000 and 0.9999.
  • D[B] is a total number of discussion topics that are associated with the current product and Dx[A] is the maximum number of discussions topics among all products.
  • Dx[A] refers to the number of discussion topics that are associated with the product having the highest number of discussion topics.
  • the ratio of the current product group associations compared to the product that has the most group associations the following expression may be used:
  • G[B] is a total number of groups that are associated with the current product and Gx[A] is the maximum number of associated groups among all products.
  • G[B] refers to the number of groups that have the product in their libraries and Gx[A] refers to the number of groups that are associated with the product for which the greatest number of groups have included it in their library.
  • Ep the ratio of the current product recommendations compared to the product that has the most recommendations
  • E[B] is the number of recommendations received by the current product and Ex[A] is the maximum number of recommendations among all products.
  • Ex[A] refers to the number of recommendations received by the product that received the most recommendations.
  • Vp the ratio of the current product reviews compared to the product that has the most reviews
  • Vp V[B ]/Vx[ A]
  • V[B] is the number of reviews received by the current product and Vx[A] is the maximum number of reviews among all products.
  • Vx[A] refers to the number of reviews received by the product that received the most reviews.
  • Ra is determined as 0.8000.
  • seven groups may have included the product within their libraries, whereas, the product included in the most group libraries may have been included in ten libraries. In this case.
  • the product may have received 356 recommendations whereas the product that received the most recommendations may have received 500 recommendations.
  • the product may have received 200 reviews, and this product may happen to be the one that received the greatest number of reviews.
  • CV ((Oa(Ow)+Pa(Pw))*100) ⁇ 1
  • the Community Value is preferably computed by the server 102 while the information from which the Community Value is derived is preferably stored by the server 102 (e.g. in database 114 ).
  • Software used to perform the calculations can be stored at the server 102 and can be executed by the processor 112 .
  • the information on which the Community Value is based is collected by the server 102 during its interactions with the devices 104 , 106 and 108 .
  • Appropriate application software is stored and executed by the server 102 and the devices 104 , 106 and 108 , respectively, in order to perform their respective functions described herein.
  • the Community Value can be used to show a user a quick and simple score as to how the community values the product. This can be accomplished by using how many users have the product in their library, groups that have the product as well as rating and review information. This will be compiled into a score for the user.
  • the Community Value can be available to the user (e.g. by displaying the Community Value at the user device 104 , 106 or 108 ).
  • the value may be displayed when a user is browsing products on the website, or when the user is sorting a catalog list such that the user can sort by highest Community Value to browse product that the community as a whole likes the most.
  • a plurality of the products can be sorted according to their relative values and displayed in order of community value.
  • the Community Value for products can be displayed in many locations throughout the website as well as being displayed by application software running on the devices 104 , 106 or 108 .
  • the Community Value for a product can appear with the title of the product while the user is browsing a catalog of products as well as in product detail pages.
  • This apparatus may be specially constricted or configured, such as application specific integrated circuits (ASICs) or Field Programmable Gate Arrays (FPGAs), as a part of an ASIC, as a part of FPGA, or it may comprise a general-purpose computer selectively activated or reconfigured by a computer program stored on a computer readable medium that can be accessed and executed by the computer.
  • ASICs application specific integrated circuits
  • FPGAs Field Programmable Gate Arrays
  • Such a computer program may be stored in a computer readable storage medium, such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any type of media suitable for storing electronic instructions, and or coupled to a computer system bus.
  • a computer readable storage medium such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any type of media suitable for storing electronic instructions, and or coupled to a computer system bus.
  • the methods described in the specification may be implemented by a single processor or be implemented in architectures employing multiple processor designs for increased computing capability. Accordingly, the disclosure of the present invention is intended to be illustrative, but not

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US37451810P 2010-08-17 2010-08-17
US37522510P 2010-08-19 2010-08-19
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US12/894,062 Active US9892104B2 (en) 2010-08-04 2010-09-29 System for and method of annotation of digital content and creation of collections of annotations of digital content
US12/894,074 Active 2032-01-08 US8566747B2 (en) 2010-08-04 2010-09-29 Method of and system for browsing and displaying items from a collection
US12/894,090 Active 2032-12-06 US9038000B2 (en) 2010-08-04 2010-09-29 Method of and system for browsing and displaying items from a collection
US12/894,100 Abandoned US20120035978A1 (en) 2010-08-04 2010-09-29 System for and Method of Determining Relative Value of a Product
US13/900,415 Active 2031-06-09 US10031903B2 (en) 2010-08-04 2013-05-22 System for and method of annotation of digital content and for sharing of annotations of digital content
US16/014,901 Abandoned US20180373689A1 (en) 2010-08-04 2018-06-21 System for and method of annotation of digital content and for sharing of annotations of digital content
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