WO2016191349A1

WO2016191349A1 - Method and system for determining experts in an item valuation system

Info

Publication number: WO2016191349A1
Application number: PCT/US2016/033730
Authority: WO
Inventors: Brannen Huske; Sean Langford; Terry ANDERTON; Jack THORSEN
Original assignee: Gemr, Inc
Priority date: 2015-05-22
Filing date: 2016-05-23
Publication date: 2016-12-01
Also published as: WO2016191346A1

Abstract

The present disclosure relates to a community listing database for displaying, trading, selling, valuation, and generating clubs, where experts for given areas and types are identified based-in-part on the interactions and actions of other users. The platform system and methods can be provided by a web-based application, and/or plug-in, to identify users with an expertise or knowledge related to particular types of items in the listing database.

Description

METHOD AND SYSTEM FOR DETERMINING EXPERTS IN AN ITEM VALUATION

SYSTEM PRIORITY CLAIM

[0001] Priority is claimed to co-pending U.S. Provisional Patent Applications having the following serial numbers and filing dates: U.S. App. No. 62/165, 673, U.S. App. No.

62/165,665, U.S. App. No. 62/165,682, and U.S. App. No. 62/165,689, which were filed May 22^nd, 2015; as well as U.S. App. No. 62/250,886 which was filed on November 4^th, 2015. Further, each of the aforementioned applications are incorporated herein by reference in their entirety.

COPYRIGHT STATEMENT

[0002] A portion of the disclosure of this patent application document contains material that is subject to copyright protection including the drawings. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure as it appears in the Patent and Trademark Office file or records, but otherwise reserves all copyright rights whatsoever.

BACKGROUND OF THE INVENTION

1. Field of the Invention

[0003] The disclosure relates to the fields of valuing items through a platform, buying and selling said valued items. More specifically the present disclosure relates to a user platform relating to collectible items which aids in the identification of experts in the fields related to particular items, wherein the experts assist users identify the value of an item by identifying additional history or information about a particular item through a multi-user platform.

2. Description of the Prior Art

[0004] Presently, valuation experts in the field of antiques and other rare or unique items are sought after to assist in the valuation process of items that otherwise difficult to place a value on. Certain television shows have been created where interested persons bring items on to have experts analyze and place a value on their particular product.

[0005] One of the downsides of these television programs is the limited accessibility for more users to place products on such programs so as to be evaluated. In addition, experts are not always readily available in a particular area and the cost of having an item transported to such an expert, or getting an expert to travel to the site of the item in order to appraise the item can, as a result, be prohibitive.

[0006] Online auctions, classified listings, and other similar platforms have existed to assist in moving such items. On these platforms the desired price of the item is typically determined by the listing user or alternatively other users can often bid on the item in a typical auction format where the highest bidding price wins. If the item has not been exposed to and appraised by an expert its value may be limited by the highest bidder in a limited scope of forum where the best price may not necessarily be achieved.

[0007] Additionally, certain collectible items can often be handed down from one generation to another or otherwise be classified as an heirloom. Often the owners may wish to sell, insure, or simply collect additional information regarding the item. It will be appreciated that valuation of such items can be particularly difficult, and particularly since information regarding the historical significance of the item can often be lost or misunderstood through successive generations. It will be further appreciated that the value, both emotional and monetary, of these items can diminish without an understanding of the history surrounding a particular item.

[0008] A need therefore exists for allowing many users to have access to a platform that can assist in identifying the value and history of such items. Such a platform can identify and connect possessors of such items with those having more experience with such items, valuation experts, collectors, curators, etc. The present application seeks to address these concerns. SUMMARY OF THE INVENTION

[0009] The system and methods described herein provide an online-based platform that is accessible by a plurality of users, to aid in the valuation process of unique or rare items, identify the history of items, identify expert evaluators in a particular field, and identify objects that may be of interest to users who own or collect items in particular categories or types being associated with such unique or rare items.

[0010] In one embodiment of the present invention a system for determining experts in various categorical fields reflecting items from a listing database is provided. This system can include a network-accessible server platform, the network-accessible server platform having one or more non-transitory computer-readable media configured to store a plurality of databases, the network-accessible server platform also including processing circuitry for performing various determination, retrieval, saving, and other functions.

[0011] The non-transitory computer-readable media can be configured to have a listing database being stored thereon. In some instances the listing database can include a plurality of listings corresponding to a plurality of particular collectible items. The plurality of listings can be organized in various categorical classifications, the categorical classifications representing various features or types of collectible items.

[0012] Additionally, a user database can also be stored on the one or more non-transitory computer-readable mediums, the user database including a plurality of user profiles, each user profile being provided with an expertise score for each of the categorical classifications.

[0013] The system can then be configured to receive actionable input from various users regarding particular collectible items stored within the listing database. Once this actionable input is received, the actionable input can be further configured to then be acted upon by the various users independently.

[0014] In some instances an expertise score can be stored on the one or more non- transitory computer-readable media, the expertise score being based at least in part upon community actions of alternative various users with regard to the actionable input.

[0015] In some embodiments the expertise score can be categorized in relation to the one or more categorical classifications and the user's actionable input relating to particular listings within the particular categorical classifications, wherein a particular user can have multiple expertise scores based on their varying expertise between various categories.

[0016] In some embodiments the processing circuitry can be configured to determine whether the community actions of the various users with regard to a particular actionable input are positive or negative. In such instances the expertise score of a particular user with regard to the particular categorical classification can then be adjusted positively or negatively in correspondence with the positive or negative nature of the community actions. In some such embodiments the community actions of a particular user can be weighted with regard to that particular user's expert score in the particular categorical classification. [0017] In some alternative embodiments the expertise score of a particular user can be further based at least in part on the particular user's level of activity in relation to one or more listings within a particular categorical classification.

[0018] In yet additional alternative embodiments the processing circuitry can be configured to receive a predicted particular item value from a particular user, the particular item value being associated with a particular item reflected by a particular item listing, wherein the processing circuitry adjusts the expertise score of the particular user upon receipt of an actual item value input. In some such embodiments the processing circuitry can be configured to adjust the weight that the predicted particular item value has on the expertise score based on a time period between when the predicted particular item value is provided and when the actual item value input is received.

[0019] In yet additional embodiments of the present invention a method for determining experts in various categorical fields reflecting items from a listing database is contemplated. This method can include various steps, including but not limited to: providing a listing database being stored on one or more non-transitory computer-readable media being located on a network-accessible server platform, wherein the listing database includes a plurality of listings corresponding to a plurality of particular collectible items, wherein each listing is contained within a plurality of categorical classifications associated with each individual collectible item; providing a user database stored on the one or more non-transitory computer- readable mediums, the user database including a plurality of user profiles, each user profile being provided with an expertise score for each of the categorical classifications; receiving one or more actionable inputs regarding particular collectible items stored within the listing database from various users associated with the plurality of user profiles; receiving one or more community actions with regard to the actionable inputs from additional various users; calculating an expertise score for each user profile within the user database, the expertise score being based at least in part upon community actions of alternative various users with regard to the actionable input; and storing the expertise scores on the one or more non- transitory computer-readable media.

[0020] In some embodiments of the method, the expertise score can be categorized in relation to the one or more categorical classifications and the user's actionable input relating to particular listings within the particular categorical classifications.

[0021] The method can further include the steps of: determining whether the community actions of the various users with regard to a particular actionable input is positive or negative; and adjusting the expertise score with regard to the positive or negative nature of the community actions.

[0022] In some such embodiments the community actions of a particular user can be weighted with regard to that particular user's expert score in the particular categorical classification of the item being acted upon.

[0023] Similarly to the system discussed above, the expertise score of a particular user can be based at least in part on the particular user's level of activity in relation to one or more listings within a particular categorical classification.

[0024] In some embodiments, the method can further include the steps of: receiving a predicted particular item value from a particular user, the particular item value being associated with a particular item reflected by a particular item listing; and adjusting the expertise score of the particular user upon receipt of an actual item value input. In some such embodiments including the prediction of price, the method can include an additional step of adjusting the weight that the predicted particular item value has on the expertise score based on a time period between when the predicted particular item value is provided and when the actual item value input is received.

[0025] These and other embodiments are described in more detail herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The foregoing and other objects, aspects, features, and advantages of the disclosure will become more apparent and better understood by referring to the following description taken in conjunction with the accompanying drawings, in which:

[0027] FIG. 1 illustrates an exemplary system configured to carry out various steps and processes in accordance with various aspects of the present invention;

[0028] FIG. 2 illustrates a flow chart illustrating various methods and steps configured to be carried out by the system of claim 1;

[0029] FIG. 3 illustrates one or more servers and associated network-accessible non-transitory computer readable media capable of implementing various steps of the present invention;

[0030] FIG. 4 illustrates a flowchart illustrating various steps and methods in accordance with various aspects of the present invention;

[0031] FIG. 5 illustrates another flowchart illustrating various steps and methods in accordance with various aspects of the present invention;

[0032] FIG. 6 illustrates a flowchart illustrating various steps and functions which the system can perform in accordance with various aspects of the present invention; and

[0033] FIG. 7 illustrates an exemplary screen shot of an item listing or fact sheet which illustrates various steps and functions which the system can perform in accordance with various aspects of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

[0034] For purposes of this application, a web browser may refer to a software application or display produced by steps performed by processing circuitry for retrieving, presenting, interpreting, and traversing information resources provided by a remote server (e.g., on the internet). At the time of this application, web browsers may include Chrome™, Firefox™, Internet Explorer™, Opera™, and Safari™. In addition, a web application, also referred to as an application or "app" as described herein, includes computer software designed to help the user to perform specific tasks on a computer or using a mobile device. The application functions are performed by processing circuitry, such as a computer, mobile device, or server, as further described herein. For purposes of the systems and methods described herein, a plug-in may refer to a set of software components that adds specific abilities to a larger software application, such as a web browser. Plug-ins enable customizing the functionality of an application and may be implemented in any suitable architecture, such as a Flash player, Java applet, HTML5, or any other commonly used platform known in the art. For purposes of method, a plug-in is a general term which could also be synonymously associated with addons, snap-ins, and extensions. In certain contexts, the term "application" may also be used to describe a notification and/or response for an employment opportunity.

[0035] As discussed above, the collectible marketplace can be a very unpredictable and difficult field to navigate, particularly for those finding themselves in possession of collectibles who are lacking expertise in the field of a particular collectible. Such instances can arise in varying situations, for example, a person might receive such an item in an inheritance, by gift, or even find a collectible by chance. [0036] In such an instance it would be desirable for such persons to have a reliable forum in which the collectible can be valuated, or gather other important information regarding the particular item.

[0037] As such, one aspect of the present invention seeks to provide a system capable of providing storage for a plurality of item listings organized by various categories and subcategories. Each category and subcategory can include listings representing items having common themes, types, or classifications. Users of the system, each of which have a representative user profile, wherein ach profile can then be configured to track and store an expertise score relating to each listing classification, category, or subcategory.

[0038] Users can then be provided opportunities to provide input or otherwise act on the various listings provided in the listing database by providing comments, input, or other requested feedback. Some examples of such input are informational suggestions, price quotes or predictions, general comments, etc. These actions by the users are then logged in the system and can also be acted upon by the community. The system then determines whether each user action has received positive or negative feedback from the community. The positive or negative feedback from the community can then cause an associated increase or decrease on the particular user's expertise score associated with the category of the item such item is contained in. For example, positively received input from a particular user with respect to a collectible trading card will increase the expertise score of that user in the collectible card category, but will have no effect on the user's expertise score in the category of automobiles.

[0039] In particular, FIG. 1 illustrates a system 10 which is configured to store a listing database 14, and a user profile database 18 on one or more non-transitory computer-readable media 30. The system 10 can then further include processing circuitry 40. It will be appreciated that while the exemplary system is shown as being provided as a network accessible server platform 50 which is internet accessible being configured to be accessed remotely over an internet server from a user interface 60, for example from a mobile or pc driven application or similar portal. It will thus be recognized that any number of equivalent system structures, either remotely or locally based, could be implemented by those having skill in the art so as to achieve similar results.

[0040] Various aspects of the current system and methods of the present invention can therefore include a method for creating and storing listings reflective of one or more particular items. For example a comic book in a series, an artist signed guitar, a collectible automobile, or a collectible baseball card, wherein each particular item has a corresponding item listing which is stored on a non-transitory computer-readable media.

[0041] The system and methods described herein provide an online-based platform that is accessible by a plurality of users from an individual user portal. The system can thus gather information from a plurality of users so as to aid in the valuation process of unique or rare items, identify the history of items, identify expert evaluators in a particular field, and identify objects that may be of interest to users who own or collect items in particular categories or types being associated with such unique or rare items.

[0042] In one embodiment of the present invention a system for determining experts in various categorical fields reflecting items from a listing database is provided. This system can include a network-accessible server platform, the network-accessible server platform having one or more non-transitory computer-readable media configured to store a plurality of databases, the network-accessible server platform also including processing circuitry for performing various determination, retrieval, saving, and other functions. [0043] The non-transitory computer-readable media can be configured to have a listing database being stored thereon. In some instances the listing database can include a plurality of listings corresponding to a plurality of particular collectible items. The plurality of listings can be organized in various categorical classifications, the categorical classifications representing various features or types of collectible items. For example, a comic book in a series could be listed under the main category of books and a subcategory of comics, meanwhile an artist signed guitar could be listed under a main category of musical instruments and a subcategory of memorabilia, and further a collectible car could be listed under automobiles with a make or model subcategory. As such it will be appreciated that varying tiers of categories and subcategories can be provided. In this manner a particular item being represented by a corresponding item listing can thus be stored on a non-transitory computer-readable media.

[0044] Additionally, a user database can also be stored on the one or more non-transitory computer-readable mediums, the user database including a plurality of user profiles, each user profile being provided with an expertise score for each of the categorical classifications.

[0045] The system can then be configured to receive actionable input from various users regarding particular collectible items stored within the listing database. Once this actionable input is received, the actionable input can be further configured to then be acted upon by the various users independently. For example, a user can provide a comment regarding the historical significance of a piece of artwork, and other users can provide response community input, either positive or negative, regarding the comment. Processing circuitry of the system can then determine the positive or negative nature of the feedback and the user's expertise score can be increased or decreased in response to the community feedback. [0046] In this manner the expertise score can be stored on the one or more non-transitory computer-readable media, the expertise score being based at least in part upon community actions of alternative various users with regard to the actionable input.

[0047] It will be further understood that the feedback can be provided as additional comments below the original comment input, in which case the processing circuitry can be configured to recognize positive phrases or wording or alternatively negative phrases or wording so as to determine the positive or negative nature of the community response input.

[0048] In various embodiments the expertise score can be categorized in relation to the one or more categorical classifications and the user's actionable input relating to particular listings within the particular categorical classifications, wherein a particular user can have multiple expertise scores based on their varying expertise between various categories. In this manner, positive or negative feedback with regard to one classification of category will not affect the expertise score of another. For example if a user has become an expert in the field of collectible trading cards, this expertise score will not cause any increase in the user's expertise score in the category of collectible cars. Further, the inverse is true, that if a user is a verified expert with a high score in a first category, if they make a poorly received comment in a non-related category, it will not affect their expertise in the first field.

[0049] Additionally, it will be appreciated that the processing circuitry can further take into account a relationship between various categories, and while categories may not be identical, the processing circuitry can be configured to change a particular expertise score with weighted degrees based on the category relationship. For example, a comment which is well received with regard to a particular comic book genre can increase the expertise score in related fields, for example alternative genre categories, but will have a lessening impact as the categorical relationship becomes less strong, for example, expertise score in the category of fictional fantasy books, while somewhat related, will be less impacted by positive or negative treatment of user input in comic books.

[0050] In this manner the processing circuitry can be configured to determine whether the community actions of the various users with regard to a particular actionable input is positive or negative, and calculate a weight the community actions will have with regard to a particular expertise score.

[0051] Additionally, in some such embodiments the community actions of a particular user can be weighted with regard to that particular user's expert score in the particular categorical classification. For example, if a user with a high expertise score gives a positive or negative comment or input in response to an original user comment, it will have more effect on the expertise score than the comments of a new user.

[0052] In yet additional alternative embodiments the processing circuitry can be configured to receive a predicted particular item value from a particular user, the particular item value being associated with a particular item reflected by a particular item listing, wherein the processing circuitry adjusts the expertise score of the particular user upon receipt of an actual item value input. In some such embodiments the processing circuitry can be configured to adjust the weight that the predicted particular item value has on the expertise score based on a time period between when the predicted particular item value is provided and when the actual item value input is received. For example, a listing is created for a collectible trading card and presented to the community. At this point the various users can provide a guess at the worth of the card. At some later point the listing creator can input an actual sale price. The difference between the actual sale price and the predicted worth can be determined, and the expertise score with respect to that category adjusted accordingly, where a relatively accurate prediction will increase the expertise score an relatively inaccurate prediction will cause a decrease in expertise score. It will be appreciated that predictions can and likely will become less accurate with time. As such, a timed weighting factor can be incorporated into the processing circuitry's determination of effect on the expertise score. For example, if the card were to be sold this week, the valuation should have been relatively accurate, however if the listing remains active and the card is not sold for a number of years, it may cause the prediction to essentially expire and will thus have little impact on the expertise score.

[0053] In yet additional embodiments of the present invention a method for determining experts in various categorical fields reflecting items from a listing database is contemplated.

[0054] This method can include various steps, including but not limited to, providing a listing database being stored on one or more non-transitory computer-readable media being located on a network-accessible server platform, wherein the listing database includes a plurality of listings corresponding to a plurality of particular collectible items. As discussed above each listing can be contained within a plurality of categorical classifications associated with each individual collectible item. The method can then include a step of providing a user database stored on the one or more non-transitory computer-readable mediums, the user database including a plurality of user profiles, each user profile being provided with an expertise score for each of the categorical classifications. The method can then further include receiving one or more actionable inputs regarding particular collectible items stored within the listing database from various users associated with the plurality of user profiles; receiving one or more community actions with regard to the actionable inputs from additional various users. At this point a step of calculating an expertise score for each user profile within the user database can be performed, wherein the expertise score can be based at least in part upon community actions of alternative various users with regard to the actionable input. This expertise score can then be stored on the one or more non-transitory computer-readable media.

[0055] In some embodiments of the method, the expertise score can also be categorized in relation to the one or more categorical classifications and the user's actionable input relating to particular listings within the particular categorical classifications.

[0056] The method can further include the steps of determining whether the community actions of the various users with regard to a particular actionable input is positive or negative, and adjusting the expertise score with regard to the positive or negative nature of the community actions.

[0057] As discussed in more detail above the community actions of a particular user can be weighted with regard to that particular user's expert score in the particular categorical classification of the item being acted upon.

[0058] Similarly to the system discussed above, the expertise score of a particular user can be based at least in part on the particular user's level of activity in relation to one or more listings within a particular categorical classification. In this manner, an active user who comments on things regularly, will have an increased reliability to their score wherein the expertise score is cumulative, and as such a single well or poorly received input will not have a drastic effect on their overall expertise score in that category.

[0059] Also as discussed in more detail above, in some embodiments the method can further include the steps of receiving a predicted particular item value from a particular user, the particular item value being associated with a particular item reflected by an particular item listing and adjusting the expertise score of the particular user upon receipt of an actual item value input. [0060] FIG. 3 is another structural framework diagram for implementing a community valuation and information gathering system that assists in identifying experts and pertinent information for particular items of interest. The network shown in FIG. 3 provides communication between multiple information sources, such as local storage, network servers, and application portal servers as well as interfaces for a user and peer users. In general, this information is shared, communicated, and generated via communications network by one or more processing circuitry components associated with the various information sources. The communications network may be one or more networks, including, but not limited to cable network, local area network (LAN), wireless network, telephone network, cellular network, satellite network, the internet, or any other suitable communication network. Communication paths may accordingly be any appropriate communication path, such as cable lines, fiber optic lines, wireless transmission paths, satellite transmission paths, telephone lines, or any other suitable wired or wireless communication path, or combination thereof.

[0061] Users may access the community valuation system application from one or more of their user equipment devices. User equipment may include, but is not limited to, computers, mobile devices, televisions, tablets or any other suitable device that can interface with the network. User equipment includes processing circuitry and storage. Processing circuitry may be used to send and receive data, commands, user input to or from other network connected systems or devices, such as server processing circuitry of a server and portal processing circuitry of portal server. As described herein, processing circuitry, such as processing circuitry for a personal computer or server, should be understood to mean circuitry, which includes one or more of a microcontroller, integrated circuit, application specific integrated circuit (ASIC), programmable logic device, field programmable gate array (FPGA), digital signal processors, application specific instruction-set processor (ASIP), or any other suitable digital or analog processors.

[0062] Processing circuitry may be coupled to electronic storage or memory. For example, processing circuitry of the server is coupled to remote storage, processing circuitry of the user interface is coupled to local storage connected with the user interface, and portal processing circuitry is coupled to a portal storage. Electronic storage, as used herein, may include any appropriate readable memory media, including, but not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, DVD, or other optical storage, magnetic storage devices, or any other physical or material medium for storing desired information, data, instructions, software, firmware, drivers, or code. For example, storage may contain software instructions for controlling the input, output, and other processes of processing circuitry.

[0063] In certain approaches, user equipment includes devices for interfacing with a user, such as display and user input interface. For example, the display may be any suitable display interface, including, but not limited to a monitor, television, LED display, LCD display, projection, mobile device, or any other suitable display system. User input interface may be a keyboard, touchscreen, mouse, microphone, stylus, or any other suitable user input interface. Display and user inputs allow processing circuitry to provide information to the user and to receive user-generated commands, responses, and data. In certain approaches, processing circuitry stores user-generated information in storage.

[0064] The network system can also allow for communication between multiple subsystems, such as user equipment, servers, and remote databases. For example, user processing circuitry may retrieve data associated with an identified item and promulgate that information to peer users, who can then use an interfacing device to add, delete, comment or otherwise modify data associated with the identified item. These interactions are also stored in memory and analyzed using processing circuitry to identify the level of expertise (confidence or reputation scores) of individual users.

[0065] In certain approaches, the community valuation system may be implemented from within a browser or browser add-on. For example, a browser may be generated from processing circuitry upon accessing computer processing commands stored on storage, which provide input for interpreting data or additional processing information from one or both of website server storage or portal storage. Additionally or alternatively, storage may include computer code read by processing circuitry for generating a browser add-on to provide additional functionality through the browser for the user. For example, an add-on may allow fast access to portal or allow automated storing of uploaded items in a collection to be accessed in the browser.

[0066] In one aspect of the present invention a user can create a profile in the system wherein their user information is stored on a storage interface which can be a web based or remotely accessible database. Within the user's profile the user can create an item inventory of one or more item listings within the mosaic or collection which reflect individual collectibles or multi-item collectibles. The system can then create a user mosaic or collection which represents the user's inventory. The mosaic or collection can be kept personal or shared with other peers having respective profiles within the system. The user can then fill in known information within each listing, wherein the listing represents the electronic profile for each item. A mosaic can be pictorial representation of a plurality of items associated with a particular collection or set.

[0067] In one embodiment, a user can identify an item which the user wishes to flag in order to valuate, sell, or gather additional information for the indicated item in the mosaic or collection. This item is then exposed to a community of users who can view the listing and then provide additional information with regards to the history, origin, unique aspects, value, etc., of the particular item.

[0068] The items can be categorized based on the type of item and listed within categories having similar types, traits, histories, etc. Part of the peer input received can include information regarding whether the item is categorized correctly, such as, whether it is time period appropriate or whether an item is a replica, which might not be determined until a member of the peer group views the item and can provide reliable or verifiable reasons for the categorization change. In other embodiments the peer network can request or provide suggestions on additional informational fields. Additionally, categories can have sub categories with respect to more detailed information regarding the particular item. For example, someone could post a car, then subcategory of brand, then subcategory of model and year. It will be appreciated that particular fields can be left blank by the user and filled in based on peer input. For purposes of illustration, a user could post a Ford™ Mustang™ and state that it is a 1971 model categorized as the same, but upon peer review an expert peer indicates that based on the fenders, it is actually a 1970 model. The notes of the expert peer can then be verified or validated by other peers in the network and the car can be

recategorized or the information corrected to reflect the peer input.

[0069] It is also possible to change the informational fields with respect to each category. For example, a vase from the Ming Dynasty will not have a need for a manufacturer field, or for a model field. For this reason, categorical informational fields can be customized across different categories. In addition, users can also input new custom fields into their own listings for items in their personal mosaics or collections. Then when a certain threshold number of uses are achieved in conjunction with other peers or the group votes to adopt the category, the category can be updated to become a standard informational field when that type of item is selected for listings in the future. This standard informational field can request input from users as they input information attached to new items and their respective listings.

[0070] For further purposes of illustration, the history might include a history and a line of ownership, as it will be appreciated that often otherwise mundane items can gain value due to their ownership heritage. For example a teapot owned by Abraham Lincoln will have value attached to such an ownership heritage. Or a pair of shoes worn by Michael Jordan in a championship game will have increased value over their simple make and model.

Additionally, other markers of importance can include geographic relationships or storage conditions. In particular, for example, wine from a certain geographical area and from a specific vintage might have value, but only if properly stored in cellars having specific conditions. Thus, having peer customizable input with regard to categorical or field information for each item allows the system to constantly change and adapt to the specific items as a history of listings is analyzed and used.

[0071] It will also be appreciated that other various informational characteristics can prove to be a factor in valuing the items of different types, such as number of items in circulation, how many were originally produced, etc. As such the repetition of these custom fields can be recognized by the system and included for future listings as a default input query.

[0072] Within the system, the peer network can include a plurality of users, each having varying degrees of expertise with respect to the various items stored on the database. Even the users can be categorized based on experience with the items or by the relative relationship the user typically has with the items, or the role the user typically has with the item. For purposes of illustration, users can be classified as item holders, collectors, experts, and sellers, all in varying degrees of expertise. [0073] As such, the system can recognize, or request input from the user regarding levels of expertise upon profile creation. For example, a user, when creating a profile can be asked to select from a group things or categories in which they are interested or have some level of knowledge. This information can be optionally paired with or replaced with information gathered from the user's mosaic or collection, whether the user has a reserved collection in their mosaic or collection or whether the user has item listings which are marked as being for sale. Users can have different classifications for each type of item. For example, a comic book collector can have a mosaic or collection with all of the comic books they are collecting and be classified as a collector in the comic book category, and similarly the same user can have a set of baseball cards which the user wishes to sell, and be classified as a seller/holder in the baseball card category. Additionally, collections can be accorded different levels of prestige, for example having a few collectors cards of a set can have a different prestige level than a complete, new untouched collection of the same set, and additionally the holder of such a set can have a reflected weight provided to their reputation with regard to cards in such a set.

[0074] In other aspects of the present invention the user, upon adding items in a particular category, or upon profile creation, or through category browsing, can choose to join groups relating to corresponding categories. In this manner, whenever new listings are created, or items added to mosaics or collections within those categories, the user will be able to browse the changes within those categories or optionally be put into direct contact with the creators of the listings upon suggestion by the peer network during the informational gathering stage/step.

[0075] With regard to the different classes of users for each respective category, users can gain a confidence score or a reputation with regard to items within that category. For example, an expert can gain reputation by providing a valuation, and then when the item actually does sell, the quoted valuation can be checked against the expert's proposed valuation and if the valuation is within a certain threshold deviation, the user can then get an increase, or decrease when outside the threshold, to their reputation score. Or for example a collector user can gain reputation similarly but have an increased reputational score which is based on the number of similar items within their personal mosaic or collection. For example, a baseball card collector has each of the cards for each team member of the 1983 Boston Red Sox™, and has listed each of such cards on the collector's mosaic or collection. The reputational score or confidence score can then be increased to reflect the fact that by virtue of having similar items in their mosaic or collection, they likely have an increased knowledge about such items. The confidence score in their input can be increased or decreased based on the amount commonality between the items in the mosaic or collection vs the item at hand being commented upon. For example if the collector comments on a Boston Red Sox team member card from the 1984 team, the collector can be accorded a higher weighted comment confidence/reputational score, but alternatively, the same person will have less weight for members of the 2001 Yankees team, and even less when the categories match very little, like for example the Boston Bruins 2002 hockey team cards, because then the only commonality would likely be that they are professional team collector cards. A confidence score can also be effected when a user first posts a value and that value is then corroborated by a number of other users or the ratio of corroboration to oppositions is of a particular percentage e.g. 20 corroborated the initial user's valuation or 20 users corroborated while only 5 opposed the valuation, thus the ratio of 20/25 is 80% or 4 times higher than the opposition.

[0076] With reference to the above examples, varying types of classes can also exist across different categories. Such classes can include curators, historical experts, collectors (as discussed), holders, hobbyists, pickers, sellers, etc. Additionally, as new classes are established customized tracks for their respective reputational/confidence scores can be associated for each classification type.

[0077] For certain functions, for example valuation, users can be given a certain weighted score which can be correlated to their particular amount of experience, credentials, or expertise with regard to certain types of items. It will be appreciated that a professional historical art curator with years of experience handling artwork for museums will have a greater weighted score with respect to their input than compared to unidentified persons who only have a hobbyist level of experience, particularly when placing their respective valuations on the item. Using this weighted scale and range of the valuations gathered through input from the community members, a valuation can be generated for the identified item and a confidence level based on the input of users combined with their weighted score can be generated and incorporated into the valuation.

[0078] In some instances, the confidence score or ranking of a user can be provided as an ever inflating score, or the reputational score can be provided as a relative or capped ranking system. As each comment or peer input is received with respect to the associated item, the item's history can be tracked and the confidence/reputational score of each specific user can be increased or decreased based on the accuracy or reliability of the respective user's input. For example, a user comments that a collectible is worth a certain amount, but is fairly critical regarding the condition, and thus gives a seemingly low valuation. The peer group ranks the input low because they think that the item should be valued higher. That same item then sells at a price extremely close to the first peer's prediction later that week. In this case the first peer will receive an increase to his reputational score, and the other user's will get no increase or even can have their reputations decreased. In addition, a time weighting factor can be associated with comments and valuations with respect to certain items. For purposes of illustration, if a user provides a valuation, then the holder doesn't sell until years thereafter, the effect of that data on the user's reputation will be mitigated as opposed to valuations and sales within days of each other.

[0079] In addition, the system can further be configured to track the reliability of a sale data point and another confidence score can be accorded and associated to the price of the sale for purposes of user confidence scores. For purposes of illustration, the system can recognize that a particular item was sold, the system can then take note of or track the bidding pool size, number of bidders, and relative exposure the item received in the sale process. This information can then be used to calculate or determine a relative confidence in the particular sale price data point. For example an item that was only exposed to a handful of potential buyers will have a sale price data point with a relatively low confidence as compared to an item which was exposed to hundreds of thousands of potential buyers and hundreds of active bidders. In this manner the individual auction performance can be configured to have an effect on the particular sale price data point and its subsequent effect on the valuating user's respective reputations.

[0080] Another variable that can be used to influence the valuation score or range of the identified item is an identification of other similar items already registered in the platform. It will be appreciated that the sale prices of similar items will often have some relevance to the pricing of any given item. Such valuation is of particular use where a user is not necessarily interested in the sale of a particular item, but nevertheless needs the item valued. Such instances can include, but are not limited to, gaining insurance coverage on the item, or to determine the amount of collateral it would represent for borrowing money against the items value. [0081] In addition the system can identify similar items or associate various items as being part of a set with the particular item, or identify complementary attributes or styles and so forth. Alternatively the system can be configured to access external databases, for example Worth Point™, wherein the street value is retrieved based on certain informational markers from already compiled external databases. Such databases are common for collector cards and/or books. Then as users provide input and comments regarding valuation and their reasoning for such a valuation the initial confidence score can be adjusted based on the proximity to the data retrieved from the external database.

[0082] In certain instances within the community of users, there may be particular experts who have been identified through outside organizations or history as experts and as such they can be accorded a higher weight upon profile creation with respect to their valuations or assessment of the items.

[0083] In other embodiments, every user can initially begin with a zero or one reputational score. Then each user can only increase reputation by getting positive or verifiable input to other user' s items.

[0084] In addition, the system can be configured such that the members of the peer group can also be tracked and a history of demonstrated valuations can be assessed against external factors, such as accuracy of assessment versus final sale price, and as they show a history of accuracy, their reputation and thus their weight factor for a given field can increase over time. Also, the community will also include users who hold themselves out as experts, yet have unidentified credentials, wherein the input from these community members is accorded a reduced importance or weighted score when, for example, the community is giving valuation advice, at least initially and until accuracy and reputation has been established. [0085] As users provide comments, as discussed above, the system can be configured to allow for peer users to comment on each other's comments thus increasing the initial confidence score of a particular comment or the overall confidence score of the particular item. For example, with respect to the Mustang™ example above, the user misclassified the year, and based on the fenders, a peer gives a year correction. While the comment might not have a large initial confidence, the confidence can be increased as additional peers either agree or disagree with the comment, increasing or decreasing the weight with their respective individual weights.

[0086] Additionally, users can be incentivized to provide input faster and with greater accuracy by increasing the relative effect comments and input can affect the individual's personal confidence score, wherein for example, the first commenter has the potential of gaining more reputation points than later commenters on a particular item.

[0087] In some embodiments, certain features can only be unlocked when a user has achieved a certain level of confidence. For example, a user can only refute or disagree with a comment upon reaching a higher level. This feature can be helpful in eliminating the amount of spamming or intentional skewing of valuations through creation of numerous or repeated new profiles. Additionally, each individual user's confidence score can be configured to evaporate, or gradually reduce, when the user is inactive for certain time periods. This is useful for example when a certain category is relatively dynamic and changing, and if the user doesn't keep up to date, their relative confidence based on their outdated expertise will be reflected in their respective confidence score.

[0088] While several embodiments have been described that are exemplary of the present system and methods, one skilled in the art will recognize additional embodiments within the spirit and scope of the systems and methods described herein. Modification and variation can be made to the disclosed embodiments without departing from the scope of the disclosure. Those skilled in the art will appreciate that the applications of the embodiments disclosed herein are varied. Accordingly, additions and modifications can be made without departing from the principles of the disclosure. In this regard, it is intended that such changes would still fall within the scope of the disclosure. Therefore, this disclosure is not limited to particular embodiments, but is intended to cover modifications within the spirit and scope of the disclosure.

Claims

What is claimed is:

A system for determining experts in various categorical fields reflecting items from a listing database, the system comprising:

a network-accessible server platform, the network-accessible server platform including one or more non-transitory computer-readable media configured to store a plurality of databases, the network-accessible server platform also including processing circuitry;

a listing database being stored on the one or more non-transitory computer- readable media being located on the network-accessible server platform, wherein the listing database includes a plurality of listings corresponding to a plurality of particular collectible items, wherein each listing is contained within a plurality of categorical classifications associated with each individual collectible item;

a user database stored on the one or more non-transitory computer-readable mediums, the user database including a plurality of user profiles, each user profile being provided with an expertise score for each of the categorical classifications;

wherein the system is configured to receive actionable input regarding

particular collectible items stored within the listing database from various users associated with the plurality of user profiles, and wherein the actionable input is configured to be acted upon by the various users; wherein an expertise score is stored on the one or more non-transitory

computer-readable media, the expertise score being based at least in part upon community actions of alternative various users with regard to the actionable input.

The system of claim 1, wherein the expertise score is categorized in relation to the one or more categorical classifications and the user's actionable input relating to particular listings within the particular categorical classifications.

3. The system of claim 2, wherein the processing circuitry is configured to determine whether the community actions of the various users with regard to a particular actionable input is positive or negative, and wherein the expertise score of a particular user with regard to the particular categorical classification is adjusted with regard to the positive or negative nature of the community actions.

4. The system of claim 1, wherein the community actions of a particular user are

weighted with regard to that particular user's expert score in the particular categorical classification.

5. The system of claim 1, wherein the expertise score of a particular user is further based at least in part on the particular user's level of activity in relation to one or more listings within a particular categorical classification.

6. The system of claim 1, wherein the processing circuitry is configured to receive a predicted particular item value from a particular user, the particular item value being associated with a particular item reflected by an particular item listing, wherein the processing circuitry adjusts the expertise score of the particular user upon receipt of an actual item value input.

7. The system of claim 6, wherein the processing circuitry is configured to adjust the weight that the predicted particular item value has on the expertise score based on a time period between when the predicted particular item value is provided and when the actual item value input is received.

8. A method for determining experts in various categorical fields reflecting items from a listing database, the system comprising:

providing a listing database being stored on one or more non-transitory

computer-readable media being located on a network-accessible server platform, wherein the listing database includes a plurality of listings corresponding to a plurality of particular collectible items, wherein each listing is contained within a plurality of categorical classifications associated with each individual collectible item; providing a user database stored on the one or more non-transitory computer- readable mediums, the user database including a plurality of user profiles, each user profile being provided with an expertise score for each of the categorical classifications;

receiving one or more actionable inputs regarding particular collectible items stored within the listing database from various users associated with the plurality of user profiles,

receiving one or more community actions with regard to the actionable inputs from additional various users;

calculating an expertise score for each user profile within the user database, the expertise score being based at least in part upon community actions of alternative various users with regard to the actionable input; and storing the expertise scores on the one or more non-transitory computer- readable media.

9. The method of claim 8, wherein the expertise score is categorized in relation to the one or more categorical classifications and the user's actionable input relating to particular listings within the particular categorical classifications. 10. The method of claim 9, further comprising:

determining whether the community actions of the various users with regard to a particular actionable input is positive or negative; and adjusting the expertise score with regard to the positive or negative nature of the community actions.

11. The method of claim 8, wherein the community actions of a particular user are

weighted with regard to that particular user's expert score in the particular categorical classification. 12. The method of claim 8, wherein the expertise score of a particular user is further based at least in part on the particular user's level of activity in relation to one or more listings within a particular categorical classification.

13. The method of claim 8, further comprising:

receiving a predicted particular item value from a particular user, the particular item value being associated with a particular item reflected by an particular item listing; and

adjusting the expertise score of the particular user upon receipt of an actual item value input.

14. The method of claim 13, further comprising:

adjusting the weight that the predicted particular item value has on the expertise score based on a time period between when the predicted particular item value is provided and when the actual item value input is received.

15. A method for determining experts in various categorical fields reflecting items from a listing database, the system comprising:

providing a listing database being stored on one or more non-transitory

computer-readable media being located on a network-accessible server platform, wherein the listing database includes a plurality of listings corresponding to a plurality of particular collectible items, wherein each listing is contained within a plurality of categorical classifications associated with each individual collectible item;

providing a user database stored on the one or more non-transitory computer- readable mediums, the user database including a plurality of user profiles, each user profile being provided with an expertise score for each of the categorical classifications;

receiving one or more community actions with regard to the actionable inputs from additional various users; calculating an expertise score for each user profile within the user database, the expertise score being based at least in part upon community actions of alternative various users with regard to the actionable input;

storing the expertise scores on the one or more non-transitory computer- readable media;

wherein the expertise score is categorized in relation to the one or more

categorical classifications and the user's actionable input relating to particular listings within the particular categorical classifications; wherein the community actions of a particular user are weighted with regard to that particular user's expert score in the particular categorical classification; and

wherein the expertise score of a particular user is further based at least in part on the particular user's level of activity in relation to one or more listings within a particular categorical classification.

16. The method of claim 15, further comprising:

17. The method of claim 16, further comprising