Abstract:
A method and online system for recommending gifts to a user, for a gift recipient, includes determining social relational aspects between the giver and gift recipient, determining personality traits of the giver or the recipient and calculating and then displaying to the user one or more recommended gifts for purchase. Personality, occupation and style traits are numerically rated in conjunction with product attributes of a population of potential gifts for accurate calculation of optimized gift recommendations. Gifts are rated by an online community associated with the system. The system may also learn by a feedback loop for successful and unsuccessful predictions of gift desirability, thus resulting in greater gift recommendation accuracy over time.

Description:
BACKGROUND OF THE INVENTION 
       [0001]    1. Field of the Invention 
         [0002]    The present invention relates to a method and system utilizing a web-based, interactive environment. More particularly, it is directed to an online environment using personalized information for recommending a set of gifts likely to be very desirable by the intended recipient. 
         [0003]    2. Description of Related Art 
         [0004]    Gift selection has been seen as a daunting task probably since the origin of the practice in prehistory. Because of the essentially personal nature of the activity, many gift givers are intimidated by the very real chance of selecting a gift not pleasing to the recipient. Even for those who are able to discern how the gift will be perceived by the recipient, the task may still be seen as very time consuming or stressful. 
         [0005]    With the advent of online purchasing of goods, some convenience has been added to the process, yet the inherent stress remains for those givers who care about how the gift will be perceived. Some attempts have been made to recommend gifts, but have been largely directed to “collaborative filtering,” that is to say, making generalized gift recommendations based on collecting taste information from many users and/or prior purchasing patterns. 
         [0006]    These attempts however have the shortcoming of not truly “personalizing” the gift selection, not being based on aspects such as the passions, hobbies and occupation of the recipient, and not reflecting the nature of the relationship between the giver and recipient. 
       SUMMARY OF THE INVENTION 
       [0007]    The present invention solves the problems of the prior art by providing a convenient, web-based environment for an online user to identify relationship aspects between giver and recipient, as well as taking into account the passions, style and occupation of the recipient in order to provide a set of personalized gift options and to do so in a matter of minutes. 
         [0008]    The invention provides a system and method for recommending one or more gifts to a user for a gift recipient by determining social relational aspects between a giver and the recipient. The user also provides personality traits of the giver and/or recipient and then the system calculates and displays to the user one or more recommended gifts for purchase. 
         [0009]    In various embodiments, the set of all possible recommended gifts is continually expanded by fostering a community of system users who recommend new gift products. The system provides a method for the user to propose a new gift product and also provides numerical criteria for establishing when such gift product has reached a mathematical threshold of approval. The system then provides a method for each approved gift to be coded by a select team of human coders. Each approved new gift product is then coded for certain gift recommending criteria. The coding is moderated, preferably by a human with administrative privileges in the system. Those new gift products receiving a sufficient coding evaluation are then entered into the total population of potentially recommended gifts. 
         [0010]    The system learns to become a better predictor by respectively incrementing and decrementing coefficients used in calculating recommending gifts, based on a feedback loop of accuracy. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]      FIG. 1  illustrates an inventive system in block diagram form for use by a plurality of users and an administrative group; 
           [0012]      FIG. 2  is a block diagram of the system of  FIG. 1  in more detail; 
           [0013]      FIG. 3  is a screen display of The Gift Professor homepage, as generated by the system of  FIG. 1 ; 
           [0014]      FIG. 4  is a secondary display screen with reference to the homepage of  FIG. 3 ; 
           [0015]      FIG. 5  is a secondary display screen with reference to the homepage of  FIG. 3 ; 
           [0016]      FIG. 6  is a secondary display screen with reference to the homepage of  FIG. 3 ; 
           [0017]      FIG. 7  is a secondary display screen with reference to the homepage of  FIG. 3 ; 
           [0018]      FIG. 8  is a secondary display screen with reference to the homepage of  FIG. 3 ; 
           [0019]      FIG. 9  is a secondary display screen with reference to the homepage of  FIG. 3 ; 
           [0020]      FIG. 10  is a secondary display screen with reference to the homepage of  FIG. 3 ; 
           [0021]      FIG. 11  is a secondary display screen with reference to the homepage of  FIG. 3 ; 
           [0022]      FIG. 12  is a screen display of a Gift Givers Say So homepage, as generated by the system of  FIG. 1 ; 
           [0023]      FIG. 13  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0024]      FIG. 14  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0025]      FIG. 15  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0026]      FIG. 16  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0027]      FIG. 17  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0028]      FIG. 18  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0029]      FIG. 19  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0030]      FIG. 20  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0031]      FIG. 21  is a process chart for recommending new gift products; 
           [0032]      FIG. 22  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0033]      FIG. 23  is a secondary display screen with reference to the homepage of  FIG. 12 ; 
           [0034]      FIG. 24  is a box diagram for calculation of POPS predictor values; and 
           [0035]      FIG. 25  is a box diagram for calculation of Relationship Aspect predictor values. 
       
    
    
     DETAILED DESCRIPTION 
       [0036]    Referring to the drawings in general and  FIG. 1  in particular, a system or server  30  is illustrated in box diagram form. System  30  is accessible via a connecting link  32  to the Internet  34 . Additional connecting links  36  provide Internet connections to a set of end terminals, as denoted by reference numerals  38 - 44 . 
         [0037]    A set of human users denoted by reference numerals  46 - 52 , may access system  30  via terminals  38 - 44  for use in accordance with the invention. User  46  has three representative gift recipients associated with his use of system  30 , namely reference numerals  54 - 58 . Likewise, user  52  has three representative gift recipients associated as designated by reference numerals  60 - 64 . 
         [0038]    Another connecting link  66  provides connection to a terminal  68  for use by a human administrator  70 . It should be noted that connecting link  66  could be an Internet connection such as  32  or a local area network, or the like. System  30  allows users  46 - 52  to simultaneously, or at various times purchase gifts online for one or more of recipients such as  54 - 64 , as well as utilizing other services detailed below. 
         [0039]    Users  46 - 52  are illustrative in nature. In normal use, system  30  may accommodate a much larger number of simultaneous users. It should also be noted that user  46  will typically, though not necessarily be the gift giver. User  46  could also be a surrogate for a gift giver, such as a spouse. Finally, it should be noted that user  46  could be selecting a gift for himself, with similar effectiveness. 
         [0040]    Referring to  FIG. 2 , system  30  (which may itself be a server or be hosted on a server&#39;s facilities) is shown in more detail. System  30  includes a CPU  66 , a clock  68 , a video card  70 , a RAM element  72 , a ROM element  74 , a communications port  76  and, optionally, a video terminal  78 . System  30  also includes a software storage area  80  for non-volatile storage. Included in software storage  80  is a software operating system  82 , The Gift Professor (TGP) software  84 , Gift University (GU) software  86 , Gift Givers Say So (GGSS) software  88  and data storage  90 . 
         [0041]    TGP software  84 , GU software  86  and GGSS software  88  include elements for generating screen displays to be described in succeeding paragraphs. TGP software  84 , is capable, upon appropriate prompting, of generating a homepage as indicated by reference numeral  92  as shown at  FIG. 3 . TPG homepage  92  includes a “Get Started” link  94 , a “Learn More About” link  96 , a “Question” link  98 , a “Returning Visitors” link  100 , a “Your Profile” link  102 , a “GGSS” link  104  and a “GU” link  105 . 
         [0042]    Referring to  FIG. 4 , a display screen  106  is shown Display screen  106  is obtained by selecting the “Get Started” link  94  on display screen  92  of  FIG. 3 . Display screen  106  provides for interactive data input points at reference numerals  110 ,  112  and  114  as indicated. 
         [0043]      FIG. 5  provides a “Get Started” second page display screen  116  which is sequential to “Get Started” display screen of  106  ( FIG. 4 ). Display screen  116  provides interactive data input points  118 - 128  as indicated. 
         [0044]      FIG. 6  provides a “Get Started” third page display screen  130  which is sequential to display screen  116  of  FIG. 5 . Display screen  130  provides interactive data input points  132 - 136 . 
         [0045]      FIG. 7  provides a “Get Started” fourth page display screen  138  which is sequential to display screen  130  of  FIG. 6 . Display screen  138  provides interactive data input points  140 - 152 . 
         [0046]      FIG. 8  illustrates a “Get Started” a fifth page display screen  154  which is sequential to display screen  138  of  FIG. 7 . Display screen  154  includes three sets of recommended gifts respectively  156 ,  158  and  160 , referred to as “The Nines Page.” Additionally, display screen  154  provides a space for a user&#39;s synopsized recipient profile  161  and a space for “Saved Gifts”  162 . 
         [0047]      FIG. 9  is a “Tell Me More” display screen  164  generated by “Tell Me More” link  96  of  FIG. 3 . 
         [0048]      FIG. 10  is a “Personal Style” definitions display screen as indicated by  166 . 
         [0049]      FIG. 11  is a “Log In” display screen  168  obtained by selecting the “Returning Visitors” link  100  of  FIG. 3 . 
         [0050]      FIG. 12  is a “Gift Givers Say So” homepage display screen  170  which is obtained by selection of “GGSS” button  104  of  FIG. 3 .  FIG. 12  includes links for various other pages as indicted at reference numerals  172 - 188 . In addition, “GGSS” homepage  170  includes a blog area  190  and a “TGP” button  192 . 
         [0051]      FIG. 13  is a GGSS “Stories” display screen  194  obtained by selection of link  190  as shown in  FIG. 12 .  FIG. 13  includes interactive data input points  196  and  198  as indicated. 
         [0052]      FIG. 14  is a GGSS “Traditions” display screen  200  obtained by selection of link  176  of  FIG. 12 .  FIG. 14  includes interactive data input points  202  and  204  as indicated. 
         [0053]      FIG. 15  is a GGSS “Join Our Gift Experts” display screen  206  obtained by selection of link  178  of  FIG. 12 .  FIG. 14  includes interactive data input points  208  and  210  as indicated. 
         [0054]      FIG. 16  is a GGSS “Your Gift Wrap Ideas” display screen  212  obtained by selection of link  180  of  FIG. 12 .  FIG. 16  includes interactive data input points  214  and  216  as indicated. 
         [0055]      FIG. 17  is a GGSS “More Fun Facts” display screen  218  obtained by selection of link  182  of  FIG. 12 . 
         [0056]      FIG. 18  is a GGSS “Your Gift Ideas” display screen  220  obtained by selection of link  184  of  FIG. 12 .  FIG. 18  includes interactive data input points  222  and  224  as indicated. 
         [0057]      FIG. 19  is a GGSS “Rate Gifts” display screen  226  obtained by selection of link  186  of  FIG. 12 .  FIG. 19  includes interactive data input points  228 ,  230  and  232  as indicated. 
         [0058]      FIG. 20  is a GGSS “Solve A Gift Dilemma” display screen  234  obtained by selection of link  188  of  FIG. 12 .  FIG. 20  includes interactive data input points  236  and  238  as indicated. 
         [0059]      FIG. 21  illustrates a process of user-proposed gift products for addition to the total population of gift products available for recommendation.  FIG. 21  illustrates a three stage inventive approach to selecting gift products for a gift product population, as well as a method of selecting one or more gifts from the gift product population. In particular,  FIG. 21  illustrates three stages (separated by lines for clarity), namely a Gift Giver Say So (GGSS) stage  240 , a Gift University (GU) stage  242  and The Gift Professor (TGP) stage  244 , respectively associated with GGSS software  88 , GU software  86  and TGP software  84 . 
         [0060]    GGSS stage  240  includes GGSS homepage  170 , a GGSS proposed gift product substage  246 , a Thumbs Up/Down substage  248 , a Rate Gifts substage  250 , a Propose Gift Product Forum  252  and a Solve A Gifts Dilemma Forum  254 . 
         [0061]    GU stage  242  includes a GU substage  256 , a coding substage  258 , a moderator  260  and a coding Relationship Aspect substage  262 . Moderator  260  may be human or an automated function. 
         [0062]      FIG. 22  is a GU “Gift Coding Module” display screen  263  obtained by a selection of a link at GU Page  256  as shown at  FIG. 21 .  FIG. 22  includes interactive data input points  264  through  284  as indicated. 
         [0063]      FIG. 23  is a GU “Gift Coding” display screen  286  obtained by selection of a link at GU Page  256  as shown at  FIG. 21 .  FIG. 23  includes interactive data input points  288  through  300  as indicated. 
         [0064]      FIG. 24  illustrates the calculation of POPS predictor values, discussed in detail below. 
         [0065]      FIG. 25  illustrates the calculation of Relationship Aspect predictor values, discussed in detail below. 
         [0066]    Three examples will now be given for using system  30  in accordance with the invention:
       1) user  46  utilizes system  30  to obtain online a set of nine gift products as recommended gifts for a recipient having certain social relational aspects with respect to the user/giver;   2) user adds a proposed gift product to the total population of uncoded gift products; and   3) user participates to determine whether a proposed uncoded gift should be coded.       
 
         [0070]    In the first example, user  46  utilizes system  30  via the internet and comes to  FIG. 3 . User  46  selects the “Get Started” link  94  and is taken to  FIG. 4 . The user then fills in the interactive fields beginning with field  110  of  FIG. 4 , that is giving the name of the gift recipient. User is then taken to  FIGS. 5 ,  6  and  7  sequentially and interactively provides occasion information relevant to the gift giving selection including the “Passions” and “Occupations” and “Style” of the gift recipient. The TGP software  84  (as shown in  FIG. 2 ) then calculates three recommended gifts each out of the “Best Sellers”, “POPS” and “Relationship” aspects. The top three in each of these three categories are then graphically displayed as the “Nines Page” in  FIG. 8 . The user is then free to select one or more gifts for the shopping cart to be purchased as gifts. In addition, user has the option of deselecting certain gift recommendations from the “Nines Page” and receiving alternative gift selections and the de-selection process can be repeated as often as desired. 
         [0071]    In more detail, user  46  is sent from  FIG. 4  to  FIG. 5 . At  FIG. 5  user  46  is presented with a menu of “Passions and Interests” (totaling  312  individual selections, for example “Arts and Crafts” and “Attire.” User  46  is allowed to choose up to seven “Passions and Interests,” for example he can choose seven Arts and Crafts or he can choose one Arts and Crafts and from other “Passion and Interests” subcategories such as Attire or Collectors. In this example, user  46  has selected Arts and Crafts as the first Passions and Interest Category, as indicated at reference numeral  124 . Arts and Crafts has twenty-two Passion subcategories, such as Basket Weaving and Bead Craft, from which to be selected by the selection arrow at Arts and Crafts category  124 . 
         [0072]    Upon selection of the Passions and Interests subcategory listed, namely Arts and Crafts, a menu of associated Passions as listed at reference numeral  126  is then displayed. Any one of those selected then count as one of the up to seven Passions and Interests to be selected. User  46  is prompted to rate each Passion and Interest. 
         [0073]    After picking up to seven Passions and Interests the user is then taken to  FIG. 6  where he will choose up to three Occupation categories from a total selection of nineteen, each selected category to be rated from one to seven. There are a total of  122  Occupation subcategories. 
         [0074]    Referring to  FIG. 7 , user  46  is asked to name to up three personal style subcategories, out of thirteen personal style categories, each selected subcategory to be rated from one to seven. 
         [0075]    Also at  FIG. 7 , user  46  is asked to choose up to three personality traits of the recipient at reference numeral  144  and is then asked to choose up to three personality traits of the giver of the gift at reference numeral  146 . User  46  is then asked to describe the relationship from a menu listed at reference numeral  148  and also at reference numeral  150 . 
         [0076]    Turning now to  FIG. 24 , the calculation method for the personal style, occupation and passions and interests (POPS) will now be described. The calculation begins when all gifts stored in the memory are filtered for gender at  304  and age  306  as shown at  FIG. 24 . In other words, certain gift products available from the total population are excluded from further calculation in the POPS calculation of  FIG. 24 . Note that all gift products are coded as either one gender or for both genders so that for a female gift recipient, all male-only gifts would be excluded from the reduced pool of potential gifts. 
         [0077]    For purposes of example, say that the value selected by the user  46  was a five for the Art and Design sub-subcategory Interior Design. In other words, in this example user  46  has assigned an importance of five to the occupation of Interior Design (seven being most important, one being least important). 
         [0078]    Each product in the gift product population has a pre-coded (by a human coder) attribute value, between one and seven, for Interior Design. For example, a decorative vase is one of the population of gift products, with an attribute value of six with respect to Interior Design, while another one of the population of gifts is a video game and has an attribute value of one, with respect to Interior design. 
         [0079]    As discussed above, user  46  continues to choose up to a maximum of seven Passions and Interests. 
         [0080]    Then the following formula is applied at Passions box  308  for the entire population of product gifts (except those filtered by Gender  304  and Age  306 ): 
         [0000]      [(GS Pass1 *IF Pass1 )/49+(GS Pass2 *IF Pass2 )/49+ . . . (GS Pass7 *IF Pass7 )/49]/N 
         [0081]    GS=coding score 
         [0082]    Pass=attribute selected by user 
         [0083]    IF=importance value established by user 
         [0084]    N=the total number of attributes selected by the user 
         [0085]    Note that GS Pass1  would be the attribute value (aka “coding score”) of six for the decorative vase and IF Pass1  would be an importance value of five for Interior Design in the example given above. 
         [0086]    Now an analogous calculation is made at Occupation box based on inputs at  FIG. 6 , in particular at reference numeral  132  for each of up to three Occupation categories. The formula used for all product gifts (except those filtered by Gender  304  and Age  306 ): 
         [0000]      [(GS Occ1 *IF Occ )/49+(GS Occ2 *IF Occ2 )/49+ . . . (GS Occ7 *IF Occ7 )/49]/N 
         [0087]    Where 
         [0088]    GS=coding score 
         [0089]    Occ=occupation attribute selected by user 
         [0090]    IF=importance value established by user 
         [0091]    N=the total number of attributes selected by the user 
         [0092]    In a strictly analogous fashion, a calculation is made for each gift product at Personal Style Box  312  at  FIG. 24 . 
         [0093]    The score calculated at each of boxes  308 ,  310  and  312  are then normalized and ranked at respective boxes  314 ,  316  and  318 . Each of those values is then multiplied by a predictor or coefficient at respective boxes  320 ,  322  and  324 , and then all resultants are stored for each gift product at Gift Votes box  326 . 
         [0094]    Finally, the Passions, Occupations and Personal Style resultants for each gift product are summed for each gift product and stored at Gift Aggregation box  328 . Then each gift product is ranked numerically and the top three gift products are sent to the Nine&#39;s Page and displayed as the top row of gifts as indicated in  FIG. 8  at reference numeral  156 . 
         [0095]    As the top row of Passions, Occupations and Personal Style is calculated for display at top row  156  of  FIG. 8 , the bottom row  158  at  FIG. 8  is also being calculated for Relationship Aspects (“RA”). The RA elements are Personality of Giver, Personality of Recipient, Length of Relationship, Relationship Characterization, Relationship Type, Relationship Closeness and Occasion, as shown at  FIG. 25 , respectively at reference numerals  330  through  340 . Up to three importance values (or “trait” values) are inputted into Personality of Giver box  330  from interactive data input point  146 . Up to three trait values are inputted into Personality of Recipient box  332  from interactive data input point  144  (at  FIG. 7 ). One trait value is inputted into Length of Relationship box  334  from interactive data input point  120  (at  FIG. 5 ). One trait value is inputted into Relationship Characterization box  336  from interactive data input point  150  (at  FIG. 7 ). One trait value is inputted into Relationship Type box  338  from interactive data input point  118  (at  FIG. 5 ). One trait value is inputted into Relationship Closeness box  340  from interactive data input point  148  (at  FIG. 7 ). One trait value is inputted into Occasion box  342  from interactive data input point  122  (at  FIG. 5 ). It should be noted that these traits are not numerical, but rather characteristics. 
         [0096]    A digression from calculation at  FIG. 25  is now necessary to discuss permanent data in storage, obtained for the purpose of facilitating  FIG. 25  calculation. That is to say, predetermined data associated with each inputted trait for each gift is in permanent data storage for access for calculations associated with respective boxes  344 - 356 . The predetermined data are based on standard deviation values DV for associated Product Attributes for each gift product for a given trait. There are fourteen Product Attributes (for example, two are “New” and “Exciting”). The DV values have two primary data inputs: 1) coding values assigned by averaging the numerical value (one to seven) assigned by each of three human coders for each Product Attribute for each gift; and 2) target values determined by a Target Survey of a pool of human responders to questioning about each possible trait with respect to each Product Attribute. 
         [0097]    By way of example, a specific gift, say a tennis racquet, was previously coded by three human coders as an average value of six on “Exciting.” This is the coding value. 
         [0098]    Further by way of example, in the Target Survey, a pool of human responders was asked how “exciting” a gift each responder wanted for a New relationship, rated from one to seven. The mean of all answers was 4.5. That is the “target value.” Therefore the deviation value for the tennis racquet for a new relationship is 1.5 (absolute value of 6-4.5). In this fashion standard deviation values, DV, are predetermined according to the following formula: 
         [0000]        DV =|( PA   1   G   Y   −PA   1   IV   m )|+|( PA   2   G   y   −PA   2   IV   m )|+ . . . |( PA   14   G   y   PA   14   IV   m )/49 
         [0099]    For all fourteen Product Attributes, where 
         [0100]    PA x G y  is the predetermined coded score on Product Attribute x for gift y; and 
         [0101]    PA x IV m  is the target value on Product Attribute x for trait m. 
         [0102]    In the preceding example, the first term (indicated between the first set of absolute value symbols would be 1.5 (6-4.5), where PA 1  was “New,” G y  was “Tennis Racquet,” IV m  was “Exciting.” Hence, a standard deviation value has been predetermined and stored for each trait (such as “Exciting” for each Product Attribute for all gift products. 
         [0103]    Now the calculations associated with respective boxes  344 - 356  will be described. 
         [0104]    At Personality of Giver box  344 , an RV value is calculated as follows: 
         [0105]    Personality of Giver 
         [0000]        RV =( DV   Pers1   +DV   Pers2   +DV   Pers3 )/ N    
         [0106]    DV=deviation value for the selected attribute for gift y 
         [0107]    Pers=personality trait selected by the user 
         [0108]    N=the total number of attributes selected by the user 
         [0109]    At Personality of Recipient box  346 , an RV value is calculated as follows: 
         [0110]    Personality of Recipient 
         [0000]        RV =( DV   Per1   +DV   Per2   +DV   Per3 )/ N    
         [0111]    DV=deviation value for the selected attribute for gift y 
         [0112]    Pers=personality trait selected by the user 
         [0113]    N=the total number of attributes selected by the user 
         [0114]    At Length of Relationship box  348 , an RV value is calculated as follows: 
         [0115]    Length of Relationship 
         [0000]      RV=DVLR 
         [0116]    DV=deviation value for the selected attribute for gift y 
         [0117]    LR=trait selected by the user 
         [0118]    At Relationship Characterization box  350 , an RV value is calculated as follows: 
         [0119]    Relationship Characterization 
         [0000]        RV =( DV   RC1   +DV   RC2   =DV   RC3 )/ N    
         [0120]    DV=deviation value for the selected attribute for gift y 
         [0121]    RC trait selected by the user 
         [0122]    N=the total number of attributes selected by the user 
         [0123]    At Relationship Type box  352 , an RV value is calculated as follows: 
         [0124]    Relationship Type 
         [0000]      RV=DVRT 
         [0125]    DV=deviation value for the selected attribute for gift y 
         [0126]    RT=trait selected by the user 
         [0127]    At Relationship Closeness box  354 , an RV value is calculated as follows: 
         [0128]    Relationship Closeness 
         [0000]      RV=DV RC1    
         [0129]    DV=deviation value for the selected attribute for gift y 
         [0130]    RC1=trait selected by the user 
         [0131]    At Occasion box  356 , an RV value is calculated as follows: 
       Occasion 
       [0132]      RV=DV Occ    
         [0133]    DV=deviation value for the selected attribute for gift y 
         [0134]    Occ=trait selected by the user 
         [0135]    The RV value for each gift in each of boxes  344 - 356  is ranked from lowest to highest, since the calculation is based on standard deviation. Then each gift product is given a normalized rank value (the lower the RV deviation value, the higher the rank value). Then the normalized rank value for each gift product is multiplied by corresponding RA predictor coefficients respectively illustrated at boxes  358  through  370 . The resulting Relationship Aspect (RA) values for each gift product are then collated by gift product as shown at Voting box  372 . 
         [0136]    Then the RA values for each gift product are summed as shown in Aggregator box  374 . Then the gift product scores are compared and the top three gift products are selected from Aggregator box  374  for display on middle row  158  of the “Nine&#39;s Page,” as shown at  FIG. 8 . In this example, Gifts A, B and D had the highest gift product scores and would thus be the three gift recommendations displayed on the “Nine&#39;s Page.” It should be remembered that in practice the total number of gift products with associated gift product scores will typically be much higher than the five gifts illustrated in  FIG. 25 , usually numbering in the hundreds. 
         [0137]    Gift products are also ranked numerically for Best Seller values and sent to the Nine&#39;s Page and displayed as the bottom row of gifts as indicated in  FIG. 8  at reference numeral  160 . Those skilled in the art will recognize that there are many different suitable approaches for calculating and ranking best sellers. There is currently no preferred method for selecting best sellers but one method under consideration is, in addition to initial filtering of gender and age and factoring in POPS and Relationship aspects, sales and other marketing considerations would also be factored in. This concludes the first example. Also, it should be noted that if any gift recommendation from rows  156 - 160  should be discarded, the next ranked gift from that row, whether POPS, Best Seller or RA, will be substituted, thereby restoring the total number of gift recommendations to nine. It should also be noted that the selection system can be a learning system by, for example, incrementing coefficients (such as shown at  FIG. 24  and  FIG. 25 ) when the associated calculative path has been successful for a particular gift, i.e. user  46  selects that particular gift. Likewise, system  30  can also learn by decrementing unsuccessful calculative path for a particular gift, e.g. when that particular gift has been discarded from the Nine&#39;s Page by user  46 . 
         [0138]    The second example of using system  30  will now be discussed. Referring to  FIG. 21 , user  46  will access system  30  (see  FIG. 1 ) via the Internet as a previously registered user so as to be taken directly to  FIG. 11  for log-in (TGP). User  46  then selects reference numeral  184  for the link “Your Gift Ideas” and proposes a gift along with text, graphics or other descriptive subject matter as desired. Then the proposed gift product may be voted on at the “Thumbs Up-Thumbs Down” GGSS page  252  then a group of users will then be invited to vote on the suitability of the gift and if 75% or more of the votes are positive the gift will be approved for coding at the GU stage  256  (i.e. “Gift University”). In addition, gifts may be proposed for “Thumbs Up-Thumbs Down” by recommendation at the “Gift Dilemmas” forum at  FIG. 20 . 
         [0139]    In the third example, a set of trained and selected coders are used to code a proposed gift in GU to be added to The Gift Professor. In this process, the coders are rewarded or compensated for coding a gift and gift product in the GU stage  258  at  FIG. 21 . After the proposed gift product has been coded by five coders, the proposed gift product will be reviewed by a human or automated moderator at stage  260  of  FIG. 21  for final approval as a published Gift Product in the TGP stage and therefore selectable as a gift for purchase. 
         [0140]    Each interactive step of GGSS will have a point value assigned for contributor&#39;s who wish to participate. The interaction between GU and the moderator will entail a training system. Those who are selected as coders, through a series of tests, will also be rewarded, but to a greater extent. Points accumulated can be redeemed for cash or gifts to be chosen by the recipient. 
         [0141]    It should be apparent that the invention not only accomplishes the major functions required from such articles but does so in a particularly advantageous manner. It should be equally apparent, however, that various minor and equivalent modifications from the embodiments disclosed herein for illustrative purposes could be employed without departing from the essence of the invention. It is to be understood, therefore, that the invention should be regarded as encompassing not only the subject matter literally defined by the claims which follow, but also technical equivalents thereof.