Obviousness

Obviousness Analysis of US Patent 8579710 Under 35 U.S.C. § 103

This analysis examines the obviousness of US Patent 8579710, focusing on independent claims 1 (method) and 15 (system), by considering combinations of prior art references that a person having ordinary skill in the art (POSITA) would have been motivated to combine as of the patent's priority date (January 20, 2011).

The core elements of US8579710 include:

1. Providing a game environment where a first player can acquire or develop a virtual good with a starting value.
2. Receiving at least one rating for the virtual good from a second player.
3. Automatically adjusting (increasing or decreasing) the virtual good's value based on these ratings to a new value.
4. Making the virtual good available for purchase at this new value.
5. Crucially, when a requesting player seeks to purchase the virtual good, checking whether that player previously rated the virtual good before allowing the sale.

The general concepts of virtual goods trading in a game environment, assigning initial values, and making goods available for purchase are widely known and acknowledged in the background of US8579710 itself, as well as by references like US6009458A ("Networked computer game system with persistent playing objects"). Therefore, the analysis will focus on the more specific combination of dynamic pricing based on ratings and the anti-fraud checking mechanism.

Combination of Prior Art for Dynamic Pricing Based on Player Ratings

A POSITA would have been motivated to combine existing technologies to create a system where virtual good values are dynamically adjusted by player ratings.

1. Dynamic Pricing Models for Digital Content: US20080154798A1 ("Dynamic Pricing Models for Digital Content") discloses methods and systems for dynamically adjusting the price of digital content to achieve revenue goals. While not explicitly limited to "player ratings," it provides the fundamental concept and motivation for dynamically pricing digital assets. A POSITA would understand that user feedback, including ratings, is a common and effective input for dynamic pricing algorithms in e-commerce and digital marketplaces.
2. Rating Virtual Objects in Virtual Worlds: US20100175002A1 ("Method and system for rating exchangeable gestures via communications in virtual world applications") explicitly teaches a method and system for receiving and processing ratings for "exchangeable gestures" within a virtual world application. These "exchangeable gestures" can be understood as a type of virtual good. This reference establishes the concept of players providing ratings for virtual items in a game environment. Additionally, US20100042577A1 ("Systems and methods for calibrating user ratings") demonstrates the known art of managing and understanding the credibility of user ratings.

Motivation to Combine: A POSITA in game development, recognizing the potential to enhance engagement and create more dynamic in-game economies, would be motivated to integrate player feedback into pricing mechanisms. By combining the dynamic pricing models for digital content (US20080154798A1) with the ability to receive and process player ratings for virtual items in a virtual world (US20100175002A1), it would be obvious to develop a system that automatically adjusts the value of virtual goods based on these player ratings. This would allow the price to reflect perceived value, desirability, or effectiveness, thereby creating a more responsive and immersive trading experience within the game environment. The background of US8579710 itself highlights the desire to overcome prior art limitations where "the seller assigns a value to a virtual good" and "lack the ability to take other factors into account for ascribing value to virtual goods," thereby explicitly articulating the motivation for such a dynamic, rating-driven system.

Combination of Prior Art for the Anti-Fraud Check

The specific feature of "checking whether the requesting player previously rated the virtual good prior to allowing a sale" (Claims 1 and 15) also appears obvious in light of the aforementioned combination and general knowledge in online commerce.

1. Problem Recognition: Once a system is established where user ratings directly influence the economic value of items, a clear motivation arises to prevent manipulation or fraud. Players could otherwise negatively rate an item to lower its price and buy it cheaply, or positively rate it to inflate its value for a potential sale (if the system allowed self-selling based on self-ratings, which the patent also contemplates preventing). The patent explicitly recognizes this problem: "In order to mitigate the possibility of players banding together to rate a virtual good negatively to lower its value, so that they can purchase it after its value has gone down..." and describes safeguards like preventing a negative rater from buying at the lowered price or a positive rater from selling at the higher price.
2. Known Rating Integrity Concerns: The existence of US20100042577A1, which details "Systems and methods for calibrating user ratings" and discusses "calibrating the credibility of a user in providing ratings," demonstrates that the problem of rating integrity and preventing abuse was well-known in the prior art.
3. Obvious Anti-Fraud Mechanism: Given the known issues with user-generated content influencing value in online systems (as evidenced by US20100042577A1) and the clear motivation to prevent economic manipulation in a rating-driven virtual economy, a POSITA would find it obvious to implement a safeguard that restricts a player from directly benefiting from their own rating actions. Checking a player's rating history for a specific virtual good before allowing them to purchase it at a new, potentially manipulated price is a straightforward and logical anti-fraud measure. It is a common design principle in online marketplaces to prevent users from influencing prices or reviews for personal gain.

Conclusion:
Claims 1 and 15 of US8579710, encompassing a method and system for dynamically adjusting the value of virtual goods based on player ratings and including a check for prior player ratings before purchase, would be rendered obvious by combining US20080154798A1 and US20100175002A1, along with general knowledge in online systems regarding anti-fraud measures and rating integrity (further supported by US20100042577A1). The clear motivation for combining these elements stems from the desire to create more engaging and fair in-game economies that reflect community sentiment while preventing exploitation, a problem explicitly identified and addressed within the specification of US8579710 itself.