the elements identified throughout are exemplary and may include various alternatives , equivalents , or derivations thereof . various combinations of hardware , software , and computer - executable instructions may be utilized . program modules and engines may include routines , programs , objects , components , and data structures that effectuate the performance of particular tasks when executed by a processor , which may be general purpose or application specific . computer - executable instructions and associated data structures stored in a computer - readable storage medium represent examples of programming means for executing the steps of the methods and / or implementing particular system configurations disclosed herein . fig1 illustrates an exemplary system 100 for ranking and managing user - generated game play advice . the system 100 of fig1 includes a game play advice submission engine 120 , game play advice database 130 , ranking engine 140 , game play advice display engine 150 , feedback engine 160 , feedback database 170 , and ranking database 180 . in some embodiments ( like that illustrated in fig1 ), the system 100 may also include an optional weighting engine 190 . while various engines and databases are described in the context of fig1 , an embodiment of the present invention may offer the functionality of each or certain of these engines and databases in a single ‘ game play advice management ’ engine or database . system 100 may be implemented in a network environment 110 such as the internet , a proprietary communications environment , or a combination of the two . in one example , system 100 is an integrated component of the playstation ® network . system 100 ( or components thereof ) may communicate with the network environment 110 utilizing any number of network interfaces as are known in the art . examples of such interfaces include a 1000base - t ethernet port or an ieee 802 . 11 b / g network wifi interface . system 100 may be implemented in a computing device such as a server dedicated to managing user - generated game play advice including maintenance of various databases . alternatively , system 100 may be implemented in a computing device hosting a number of applications such as community maintenance , admission , and network game data distribution . system 100 may be dedicated to a single network game , a genre of games , or any number of games having no particular affiliation at all . system 100 may also be implemented in a distributed peer - to - peer environment . in such an implementation , certain applications and / or responsibilities may be managed by a group of computing devices in the environment . a first computing may be represented by a game platform such as the playstation ® 3 . this particular computing device may be responsible for ranking operations that take place via a ranking engine and maintaining a database of related information . a second computing device such as a desktop or laptop computer may be responsible for feedback operations that take place via a feedback engine and maintaining a database of related information . various engines may be distributed to a community of users ( e . g ., players of a particular game or users in a general gaming network ) through a push operation from a tasked server in the game community . alternatively , various engines may be embodied in a computer - readable storage medium that also includes a particular game application ( e . g ., a disc ). distributed applications and engines may communicate directly via a group of peers or may be administered by a management server . game play advice submission engine 120 is configured to allow a user to communicate with the system 100 over network 110 for submission of game play advice . game play advice submission engine 120 may generate a user - interface for allowing user interaction with the system 100 . the interface may be a simple text - entry screen where users identify a game title , user identity ( i . e ., who is submitting the advice ) in the form of a ‘ real name ’ or ‘ screen name ,’ and particular game play advice . game play advice submission engine 120 may generate a ‘ drop down ’ menu to allow for easy entry of information . drop - down menus may identify a variety of game titles ( in order to maintain consistency of game title naming ). drop down menus may also allow for identification of particular types of advice such as special moves , easter eggs , unlocking weapons , or defeating particular enemies . drop down menus may also identify particular portions of an interactive gaming environment by level or environmental description ( e . g ., level 1 or ‘ the volcano ’). similar identification may occur with respect to particular objects , weapons , or enemies . menus generated by the game play advice submission engine 120 may be level - based . a level - based menu configuration may cause the selection of one item at a first level of a menu to branch out into a series of options concerning a second level of related menu items . selection of an entry at the second level may spawn a third - level and so on . spawning of various levels may continue until there is no further information to be entered . entry of the game play advice may be textual where a user enters a written description of the game play advice ( e . g ., ‘ at the castle gate , look behind the statute for a hidden treasure ’). text - entry may occur through a virtual keyboard manipulated by a game controller coupled to a gaming platform . the gaming platform , in turn , is coupled to the system 100 via network 110 . submission of game play advice may be audible and provided by speaking into a usb microphone headset . in some embodiments , video clips or still - frame images of game play may be submitted in the context of or as game play advice . combinations of game play advice submissions are also within the scope of the present invention ( e . g ., a video clip with audible narration ). game play advice database 130 is configured to manage user - generated game play advice submitted through an interface generated by the game play advice submission engine 120 . game play advice database 130 may manage submitted game play advice by user , game title , nature of the advice , date , size , content of the advice ( e . g ., video , audio , text , combinations of content ), and so forth . game play advice database 130 may include non - user generated game play advice ( e . g ., pre - stocked game play advice from the game publisher ) that may also be ranked and displayed by system 100 . game play advice database 130 may be configured to store all game play advice received through an interface generated by game play advice submission engine 120 . alternatively , certain game play advice may expire over time or upon the occurrence of certain events . for example , the game play advice database 130 may only retain the top - 100 ranked game play advice submissions . once a particular instance of game play advice falls below a top - 100 threshold , that particular instance may be deleted from the game play advice database 130 . expiration may be temporal such that instances of game play advice that are not accessed for a particular period of time are removed from the game play advice database 130 . instances of game play advice may also be removed from the game play advice database 130 a predetermined number of days after having been submitted to the system 100 . ranking engine 140 is configured to manage the ranking of game play advice stored in game play advice database 130 . when new game play advice is received , the ranking engine 140 of fig1 will assign a default ranking to that new instance of game play advice . this default ranking and any other ranking ( including those generated as a result of user feedback ) may be measured utilizing any rubric capable of distinguishing one instance of user - generated game play advice from another . rankings may be numeric ( e . g ., 1 , 2 , 3 . . . 101 , 102 , etc .) or characteristic ( e . g ., poor , good , very good , excellent , etc .). simplistic rankings may also be used such as a binary indication of ‘ good ’/‘ bad ’ or ‘ thumbs up ’/‘ thumbs down .’ a percentage value may also be used by ranking engine 140 . for example , an ‘ 86 % ranking ’ may reflect that 86 percent of all user feedback received with respect to a particular instance of game play designated the advice as ‘ good or better .’ tie - breakers may be utilized by the ranking engine 140 with respect to multiple instances of game play advice that are allocated rankings of equal value . equally - ranked game play advice may be distinguished by an alphabetical ordering of the screen name or real name of the user submitting the game play advice . equally - ranked game play advice may also be displayed based on the time the game play advice was submitted . previously received and equally ranked game play advice may be moved to the bottom of a ranking ladder versus more recently received ( and equally ranked ) game play advice . equally - ranked game play advice may also be displayed in a random order albeit in the context of other equally - ranked advice . ranking engine 140 may operate in conjunction with ranking database 180 to maintain a record of a current or prior ranking of any particular instance of game play advice . ranking engine 140 may also work in conjunction feedback engine 160 , feedback database 170 , and , in some embodiments , optional weighting engine 190 to more accurately identify the perceived quality of game play advice as adjudicated by a community of users . game play advice display engine 150 is configured to display user - generated game play advice in accordance with a ranking result generated by ranking engine 140 . game play advice display engine 150 acquires information from the game play advice database 130 ( the advice ) and the ranking database 180 ( the ranking of the game play advice as determined by ranking engine 140 ) and displays the game play advice in accordance with an allocated ranking . the game play advice display engine 150 may utilize an asynchronous programming language to provide real - time ( or substantially near real - time ) updates to ranked game play advice for display to a community of users . game play advice display engine 150 may utilize a ladder ranking of game play advice . in such an embodiment , the highest quality advice is presented at the top of a ladder and the worst advice is relegated to the bottom of the ladder . the quality of the advice decreases as a user moves from the top of the ladder to the bottom . in some embodiments , the particular arrangement of the advice may be subject to user or system preferences ( e . g ., the advice may be listed in an inverse order where the best advice is listed at the bottom of the ladder and the worst advice at the top ). fig5 a illustrates an exemplary ladder ranking 500 of user - generated game play advice ( 510 a . . . f ). in fig5 a , the ladder ranking 500 includes six exemplary instances of user - generated game play advice ( 510 a . . . f ). each instance of game play advice identifies a title of the interactive game for which the advice is rendered 520 ( i . e ., socom 3 ); the nature of the advice 530 ( i . e ., pertaining to ‘ unlockable ’ weapons ); and the particular unlockable weapon at issue 540 ( e . g ., an iw - 80 a2 , an stg - 77 , a medium scope , and a front grip ). each instance also includes the advice itself 550 ( e . g ., “ complete the poland theater of operations ” in the case of instance 510 a ). the information displayed in each instance of game play advice ( e . g ., game title , nature of the advice , etc .) and the format of the same ( e . g ., text entries versus graphical illustrations ) may vary depending on a particular embodiment of system 100 and game play advice display engine 150 . additional information may also be displayed in each instance of game play advice . for example , an embodiment of ladder ranking 500 may include the screen name of the user submitting particular information , the date the advice was submitted , a visible indication of the ranking of the instance of game play information ( e . g ., 1 of 6 ; 86 % approval ; thumbs up ), or the number of times feedback has been rendered with respect to that particular instance of game play advice . an indication that a particular ranking is the result of a default ranking may also be displayed . in fig5 a , the best quality game play advice is displayed at ( or near ) the top of the ladder ranking 500 . with respect to this particular game title , the iw - 80 a2 may represent a particularly desirable weapon . information regarding acquisition of this weapon may , therefore , be highly valued ( i . e ., to obtain this weapon “ complete the poland theater of operations ” as reflected by advice 550 of instance 510 a ). in another instance of game play advice ( 510 f ), the weapon is the same as that discussed in the most highly ranked instance ( 510 a ) ( i . e ., the aforementioned iw - 80 a2 ) but the advice is of such poor quality that the advice is located at the lower - most rung of the ladder ranking 500 . with respect to game play advice instance 510 f , the user submitting the ‘ advice ’ has just begun playing this particular game title and does not know what an iw - 80 a2 is or how to acquire the same . as such , this unhelpful instance of game play advice is appropriately ranked and subsequently displayed at the bottom of the ladder ranking 500 . as a result of this ranking , a user searching for information concerning the acquisition of an iw - 80 a2 saves time by avoiding review of unhelpful information . further , the user searching for advice on acquiring the iw - 80 a2 is more likely to receive complete and accurate advice . game play advice display engine 150 may display advice in the context of a real - world virtual environment and / or a first - or third - person avatar . in such an embodiment , an avatar may move about a virtual environment like that offered by sony computer entertainment inc .&# 39 ; s “ home .” “ home ” is a three - dimensional online user community service that may be accessed utilizing the playstation ® 3 entertainment system . the “ home ” virtual environment offers a “ hall of fame ,” two examples of which are illustrated in fig5 b and fig5 c , and that could be used in conjunction with the display of user - generated game play advice . for example , display area 560 could be used to display a ladder ranking 500 like that discussed in the context of fig5 a . virtual objects associated with a reward or particular achievement may also be displayed such as a trophy . game play advice may be displayed in the context of particular game titles or users . in a virtual environment like that shown in fig5 b and fig5 c , game play advice display engine 150 may be integrated with the host of the virtual environment . game play advice display engine 150 may also access the virtual environment through an application programming interface ( api ) native to the environment . other means of display of game play advice beyond the aforementioned ladder and virtual environment are within the scope of the present invention . game play advice may be listed as a series of entries in a ‘ chat ’ string . game play advice may be displayed and detailed commentary ( in addition to ranking feedback ) concerning the quality of that advice may be provided by the community of users . game play advice may also be provided through a series of hyperlinks . graphic images may also be utilized , especially in the context of game play advice that incorporates full motion video or still images . links to audio files may be appropriate in the case of audio - rendered advice . all of the aforementioned means of providing game play advice to a community of users ( and in accordance with an assigned default or feedback controlled ranking ) may be managed by the game play advice display engine 150 . feedback engine 160 is configured to accept feedback from other game players following their viewing and subsequent use of game play advice provided via the game play advice display engine 150 . feedback engine 160 may be integrated or work in conjunction with game play advice display engine 150 with respect to receiving feedback . for example , feedback engine 160 may generate a prompt for receiving user - generated feedback . the prompt may be displayed in the immediate context of particular instances of game play advice , which are displayed by game play advice display engine 150 . user feedback may be any subjective assessment capable of distinguishing one instance of user - generated game play advice from another . user feedback may be numeric ( e . g ., 1 to 10 , with 10 being high quality and 1 being low ) or characteristic ( e . g ., good , very good , excellent , etc .). simplistic binary indications of ‘ good ’ or ‘ bad ’ or a ‘ thumbs up ’ or ‘ thumbs down ’ may also be used . feedback may include a textual ( or spoken ) assessment of the user - generated game play advice . feedback may be entered manually ( e . g ., entry of a ‘ 10 ’ through a virtual keyboard ), selected from drop down menus , or submitted via graphic representations such as on - screen icons ( e . g ., selecting a ‘ thumbs up ’). feedback engine 160 may also be configured to request and accept a grade for a particular user from a community of users , the user having submitting game play advice to the system 100 . the user grade may be a subjective assessment of a particular user registered with system 100 . other users in a community may grade a particular user based on their knowledge of the graded user &# 39 ; s in - game exploits in a manner similar to providing feedback with respect to game play advice . user grades may also be assessed automatically by the ranking engine 140 or an independent user grade engine ( not shown ). a grade for a particular user may be allocated with respect to the time that a user has been registered with the system 100 or played a particular game title ( thus suggesting experience ). grades may also be assessed based on the number of tasks that a user has completed in a particular game or the number of levels that the user has ‘ conquered .’ user grades may be particular to game , geographic region , or the entirety of the gaming network . the game community may also be defined by various tiers of experience ( e . g ., beginners , intermediate users , and experts ). user grades may also be allocated within the delineation of a particular tier to which a graded user belongs . feedback database 170 is configured to manage user feedback to game play advice submitted through feedback engine 160 . feedback database 170 may be configured to store all community generated feedback as it pertains to game play advice . certain feedback may expire over time ( e . g ., a predetermined number of days after having been submitted to the system 100 ). feedback database 170 may track the nature of the feedback ( e . g ., a subjective assessment ) with respect to a particular instance of game play advice . feedback database 170 may further track the identity of the user submitting user feedback via the feedback engine 160 . ranking database 180 is configured to manage ranking of user - generated game play advice as ranked by the ranking engine 140 . ranking database 180 may also store user grade information generated by the ranking engine 140 . ranking database 180 may be updated in real - time ( or substantially in real - time ) in order to provide game play advice display engine 150 with the most up - to - date and available ranking information as it pertains to particular instances of game play advice . ranking information stored in the ranking database 180 may expire after a set period of time . lower ranked game play advice ( e . g ., advice falling below a certain minimum ranking ) may be removed from the ranking database 180 while higher ranked information is maintained in the ranking database 180 . optional weighting engine 190 may be used for ranking user - generated game play advice based on the quality of the advice and the reputation or experience of the user submitting the advice . optional weighting engine 190 is configured to introduce a weighting algorithm that allocates a particular value to the grade of a user submitting game play advice and another value to the actual game play advice . for example , if the user is regarded by the game community ( i . e ., the user has a higher user grade ) but the game play advice submitted by the player is of low quality ( as reflected by user feedback ), the optional weighting engine 190 may apply a first weighting value to the user grade ( e . g ., 75 %) and a second weighting value to the game play advice ( e . g ., 25 %) to formulate ( in conjunction with the ranking engine 140 ) a ranking of the game play advice . the game play advice is then displayed through the game play advice display engine 150 whereby the first and second weighting values allocated by the optional weighting engine 190 proportionally affect the ranking of the game play advice . the actual weighting valuations applied to the user grade and the game play advice may be set and adjusted by an administrator of the system 100 . fig2 illustrates an exemplary method 200 for ranking user - generated game play advice based on the quality of the advice . the steps identified in fig2 ( and the order thereof ) are exemplary and may include various alternatives , equivalents , or derivations thereof including but not limited to the order of execution of the same . the steps of the process of fig2 ( and its various alternatives ) may be embodied in hardware or software including a computer - readable storage medium ( e . g ., optical disc , memory card , or hard drive ) including instructions executable by the processor of a computing device . in step 210 , user - generated game play advice is received from a user in the community via an interface generated by the game play advice submission engine 120 . upon receipt of the user - generated game play advice in step 210 , the advice is processed by the system 100 as described in the context of fig1 and assigned a default ranking by ranking engine 140 . the game play advice may be stored in game play advice database 130 . the default ranking may be stored in ranking database 180 . the processed and default ranked game play advice is subsequently displayed via the game play advice display engine 150 in step 220 . upon display in step 220 , the user - generated game play advice is available for viewing by other members of the gaming community . the members of the community may then act upon that advice during the course of game play . the newly received and default ranked game play advice is also displayed in conjunction with previously received game play advice , which is also stored in game play advice database 130 . the previously received game play advice may have been previously displayed and ranked or may be displayed for the first time with a default ranking ( i . e ., multiple instances of game play advice are being displayed for the first time ). the newly received game play advice may also be displayed with pre - packaged game play advice from the game publisher . a user acting upon any displayed game play advice may return to the system 100 and provide feedback as to the quality of that particular game play advice in step 230 . the feedback may be provided via a prompt generated by feedback engine 160 . the nature of the feedback may be like that described in the context of fig1 with respect to feedback engine 160 ( e . g ., a number of ‘ stars ’ or ‘ thumbs up ’ or ‘ thumbs down ’). advice that resulted in better game play may receive a higher ranking than advice that resulted in lesser game play . the presentation of the game play advice may also affect the ranking . for example , if the advice was presented in such a way as to make the advice confusing notwithstanding the validity of the advice , the particular instance may receive a lesser ranking . after having received feedback in step 230 , the ranking engine 140 of system 100 will rank the new game play advice against previously received ( and possibly ranked ) game play advice in step 240 . ranking of the new game play advice with respect to the previously received ( and perhaps ranked ) game play advice will take into account the feedback received by the feedback engine 160 and stored in feedback database 170 . after having received an initial indication of quality based on user feedback , game play advice will lose its ‘ default ’ ranking and move up or down a ladder of all available game play advice based on its valuation against other game play advice . following the ranking operation of step 240 , the results of which may be stored in ranking database 180 , the new game play advice and previously received game play advice will be ( re ) displayed by the game play advice display engine 150 in step 250 . the ( re ) display of the game play advice will reflect any received user feedback from step 230 and the subsequent ranking operation of step 240 . based on the ranking operation of step 240 , quality game play advice will rise to the top of a list of game play advice or be communicated to the community of users such that they know the advice that has received high approval from the community versus game play advice perceived to have little or no value . the method 200 of fig2 may operate in real - time ( or substantially in real - time ) using an asynchronous programming language such as ajax . in an asynchronous language like ajax , small amounts of data are continually exchanged with a database so that an entire user interface need not be reloaded in response to each user interaction . in such an embodiment , an xmlhttprequest object may be utilized to fetch the most recent game play advice rankings from the ranking database 180 of fig1 . this ranking information , and the corresponding game play advice retrieved from game play advice database 130 , may then be displayed via an interface generated by the game play advice display engine 150 . relationships between rankings , user feedback , and game play advice may be reflected by metadata or header data stored in the various databases of system 100 . game play advice rankings may thus be updated as feedback is received and new rankings are calculated . the method 200 of fig2 may also operate subject to a predetermined schedule . for example , the ranking engine 140 may update the ranking database 180 at five minute intervals ( or any other time period as may be determined by a system administrator ). once the ranking database 180 is updated as a result of a regularly scheduled ranking operation , the newly updated ranking information may be pushed to the game play advice display engine 150 for display to the community of users in conjunction with the game play advice retrieved from game play advice database 130 . the updated ranking information in the ranking database 180 may also be available for access in response to a user request or query . a user request for ranking information may instantiate the ranking operation and the subsequent display of ranked game play advice . fig3 illustrates an exemplary method 300 for ranking user - generated game play advice based on the reputation of the user submitting the advice . the steps identified in fig3 ( and the order thereof ) are exemplary and may include various alternatives , equivalents , or derivations thereof including but not limited to the order of execution of the same . the steps of the process of fig3 ( and its various alternatives ) may be embodied in hardware or software including a computer - readable storage medium ( e . g ., optical disc , memory card , or hard drive ) including instructions executable by the processor of a computing device . in step 310 , user - generated game play advice is received at the system 100 from a user in a game community . receipt of game play advice may occur through a user interface generated by the game play advice submission engine 120 . the submitting user may be identified as part of the submission process . identification may occur through manual entry of a screen name . identification may also occur via a user profile accessed when the user logged into the gaming community . automated grading of the submitting user by the ranking engine 140 takes place in step 320 such that a determination as to the authority of the provided game play advice may be made . for example , if a user is playing a particular game for the first time , any advice proffered by that player is likely of little value due to that player &# 39 ; s general inexperience with the game . if a user is experienced with respect to that game , however , then any advice provided by that user may be of greater value due to their vast experience with game play . experience may be derived from game play statistics or other data , which may be associated with a user profile . alternatively , the submitting user may be graded based on their actual performance in a particular game . a particular user may play a game numerous times but lack any exceptional ability with respect to that particular game . in these instances , grading the user based on the number of times that they have played the game may be misleading . grading the user based on performance in the game may be more indicative of the quality of the advice the user might offer . user performance may be based on any variety of factors . for example , a user may be graded based on a score achieved , a level reached , or a length of the user existed in a particular game environment without being ‘ killed .’ performance may also be based on objectives completed , items obtained , weapons mastered , enemies killed , and so forth . once the user is graded in step 320 , the ranking engine 140 will rank new game play advice against previously received ( and perhaps ranked ) game play advice in step 330 . after having received an initial indication of quality based on grading of the user , game play advice will be ranked and that ranking information will be stored in ranking database 180 while the game play advice is stored in game play advice database 130 . following the ranking operation of step 330 , the new game play advice and previously received game play advice will be displayed in step 340 by the game play advice display engine 150 . the display of the game play advice will reflect the grading of the user with respect to the game play advice as occurred in steps 320 and the subsequent ranking operation of step 330 . based on the ranking operation of step 330 , quality game play advice will rise to the top of a list of game play advice or be communicated to the community of users such that they know the advice was offered by a game player of exceptional ability versus having come from a user with little to no experience or ability . the method 300 of fig3 may operate in real - time or substantially in real - time . like the method of fig2 ( 200 ), such real - time functionality may be effectuated using an asynchronous programming language whereby the most recent game play advice rankings vis - à - vis a user grade are retrieved from the ranking database 180 and displayed via the game play advice display engine 150 . in this matter , game play advice rankings are updated as user grading is calculated . like the method of fig2 ( 200 ), the method of fig3 ( 300 ) may also operate subject to a predetermined schedule whereby the ranking engine 140 updates the ranking database 180 at regular intervals . once the ranking database 180 is updated as a result of a regularly scheduled ranking operation , the newly updated ranking information may be pushed to the game play advice display engine 150 for display to the community of users in conjunction with the game play advice retrieved from game play advice database 130 . alternatively , the updated information in the ranking database 180 may available for access in response to a user request or query . a user request for ranking information may instantiate the ranking operation and the subsequent display of ranked game play advice . user grading may also be in response to feedback received from the gaming community . in such an embodiment , user grading step 320 will involve feedback engine 160 calculating a community valuation of a particular user based on information retrieved from the feedback database 170 and prior ranking information retrieved from the ranking database 180 . steps 330 and 340 of the method 300 of fig3 will proceed as described above with the exception that the ranking of game play advice is now based on user feedback rather than an automated determination made solely by ranking engine 140 . in a still further embodiment , the user grade may involve a weighting algorithm imposed by optional weighting engine 190 . in such an embodiment , community feedback may be assigned a first weighting value by the weighting algorithm of optional weighting engine 190 . the automated ranking generated by the ranking engine 140 may be allocated a second weighting value . these weighted values may proportionally affect a final ranking ( also calculated by the ranking engine 140 ) that is ultimately stored in the ranking database 180 for retrieval by the game play advice display engine 150 . fig4 illustrates an exemplary method 400 for ranking user - generated game play advice based on the quality of the advice and the reputation of the user submitting the advice . the steps identified in fig4 ( and the order thereof ) are exemplary and may include various alternatives , equivalents , or derivations thereof including but not limited to the order of execution of the same . the steps of the process of fig4 ( and its various alternatives ) may be embodied in hardware or software including a computer - readable storage medium ( e . g ., optical disc , memory card , or hard drive ) including instructions executable by the processor of a computing device . in step 410 , user - generated game play advice is received at the system 100 from a user in a game community . upon receipt of the user - generated game play advice in step 410 , the advice is processed by the system 100 and assigned a default ranking . game play advice may be initially received through an interface generated by the game play advice submission engine 120 and stored in the game play advice database 130 . allocation of a default ranking may be allocated by ranking engine 140 . the processed and default ranked game play advice is subsequently displayed by the game play advice display engine 150 in step 420 . the game play advice display engine 150 retrieves the default ranking information from ranking database 180 and the game play advice from the game play advice database 130 . upon display in step 420 , the user - generated game play advice is available for viewing by other members of the gaming community who may then act upon that advice during the course of game play . the newly received and default ranked game play advice may also be displayed in conjunction with previously received game play advice . the previously received game play advice may have been previously displayed ( and ranked ) or may be displayed for the first time with a default ranking . display may take place concurrent with pre - packaged game play advice from the game developer , which may also be ranked . in step 430 , the submitting user is graded . grading of the submitting user takes place such that a determination as to the authority of the game play advice provided may be made as was the case in fig3 . as was the case in fig3 , a user may be graded based on experience playing a particular game or performance with respect to a particular game . grading may also be based on community feedback . in step 440 , feedback as to the quality of particular game play advice may be provided by users in the community via feedback engine 160 . advice that results in better game play may receive better feedback than advice that resulted in lesser game play or that was perhaps presented in such as way as to make the advice confusing and otherwise ineffective . feedback may be stored in feedback database 170 . in step 450 , the grading of the user as occurred in step 430 and the feedback provided with respect to particular game play advice as occurred in step 440 may be weighted . weighting of the user grade and advice feedback may occur through optional weighting engine 190 . as noted in the context of fig1 , the ratio of importance of the user grade versus the user feedback may be allocated as to best overall evaluate the advice provided by the user . following weighting of the user grade and the user feedback in step 450 , the ranking engine 140 will rank the new game play advice against previously received game play advice in step 460 . after having received an initial indication of quality based on user feedback and the user grade , game play advice will lose its ‘ default ’ ranking and move up or down a ladder of all available game play advice based on its valuation against other advice as a whole . following the ranking operation of step 460 , the new game play advice and previously received game play advice will be ( re ) displayed in step 470 by game play advice display engine 150 . the ( re ) display of the game play advice will reflect the results of the ranking operation of step 460 , which may be retrieved from ranking database 180 in conjunction with the actual game play advice from game play advice database 130 . based on the ranking operation of step 460 , quality game play advice from knowledgeable game players will rise to the top of a list of game play advice or be communicated to the community of users such that they know the advice that has received a combination of high approval from the community and was offered by an otherwise experienced or well qualified game player . while the present invention has been described with reference to exemplary embodiments , it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the true spirit and scope of the present invention . for example , the aforementioned system 100 and methods discussed therein ( e . g ., fig2 - 4 ) may be utilized to receive submissions , rank , display , accept feedback , and ( re ) rank and ( re ) display various forms of information other than game play advice . for example , the present system and methods may be employed in the context of search engine results or queries for on - line audio and video content . the aforementioned system and methods may also be used with respect to ( reverse ) auctions and bidding based on valuation / feedback of a seller , vendor , and / or product . in addition , modifications may be made without departing from the essential teachings of the present invention . various alternative systems may be utilized to implement the various methodologies described herein and various methods may be used to achieve certain results from the aforementioned systems .
management of user - generated game play advice is disclosed . the present invention allows for management of game play advice that is complete and up - to - date regardless of when a particular interactive gaming title is released . game play advice is pervasive and easily accessible to game players in addition to being accurate and credible such that game players can trust or rely upon the rendered advice .