the principles and operation of a human association search engine according to the present invention may be better understood with reference to the drawings and the accompanying description . referring now to the drawings , fig1 illustrates a schematic block - drawing of a preferred embodiment of the hardware / software architecture of the innovative association search engine of the immediate invention . server 100 includes a ram 102 , a rom 104 , a cpu 106 ( or any other processor ), a non - volatile storage unit 108 and a bus 118 connecting all the components to each other . it is clear that the high - level block diagram is only a partial representation of a server . furthermore , each of the components depicted within server 100 are not intended to be limiting but rather representative of an exemplary embodiment . some or all of the components depicted in storage unit 108 may alternatively reside in one or more additional servers which may or may not be collocated . an end user interface 110 presents a visualization of association items and chains of associations in either a linear , spatial ( 3d ) or other representation . an artificial intelligence ( ai ) mechanism 112 , included in some embodiments of the invention , learns search patterns of users , detects association trends and identifies needs for more accurate collection methods , and improvements of the search algorithm ( see “ target ticker ” below ). ai mechanism 112 can provide enhanced searching features which take into account the learned search patterns and / or detected association trends and / or other needed improvements identified by ai 112 . an association logic module 114 includes the software / algorithms which drive the search engine , including , but not limited to , association logic , filters 115 , report generators , search cart 117 and so on . association items are stored in a related — or big data — association database 120 which includes the associations and association chains between the items . a data - mining database 122 stores all the user information relating to associations and searches for the associations . a downloadable association collection application 130 resides on server 100 and instances of the software package can be downloaded in various formats : a web ( site ) application 134 can be embedded in websites ( e . g . as a facebook ™ game ); a mobile application 132 can be downloaded to mobile devices such as smartphones and tablets in the form of ‘ apps ’ or ‘ widgets ’ or any other type of mobile format ; and lastly , a pc application 136 version of the software package 130 can be downloaded to a client computer such as a desktop or laptop computer . some of the main capabilities and features of the system are enumerated below : the system collects and stores free associations received from uploading users , by presenting a stimulus / trigger which is generally selected from the association pool or according to customer needs . the collection is performed throughout the internet by flexible and dynamic means , such as , but not limited to : games , social activities , quizzes , viral activities and so on . the software modules for these online means are stored on server 100 and instances thereof can be downloaded and embedded / installed as mentioned above . uploading users are users that play the games or partake in the quizzes , social and viral activities and so on . the aforementioned dynamic means may explicitly publicize that the users &# 39 ; input is being used to improve association database 120 or not . the latter state may be preferable from a psychological stand point . on the other hand consent to make use of user input must be received where consent is required by law or accepted practice . during collection into association database 120 , the system recognizes items that already exist in the pool and registers for frequency ( e . g . keeps a counter of the number of instances that each unique association item appears ). the system also recognizes errors and lingual proximity of items and automatically corrects the spelling ( or suggests correction ), deciding whether to create a new item or change frequency of an existing item . for example , ‘ reciepf would be corrected to ‘ receipt ’ whereas ‘ cheque ’ ( british spelling for a bank check ) would be recognized as the same item as a ‘ check ’. the database contains the relationships between associations and data from the uploading process and about the uploading users . search of associations through the association database . in some embodiments , the search is textual , whereas in other embodiments the search is additionally or alternatively based on audio and / or visual . in still other embodiments , the search engine additionally contains ai ( artificial intelligence ) elements 112 which learn the search patterns of users . for example — the search engine can present enhanced searching features to a user who has performed several searches which were previously performed by another user with a result that the previous user reached eventually . the system can organize search results using filters . the filters may organize results according to media , statistic data about the associations , commonality , or even by segmentation according to the uploading - user data . in one exemplary embodiment , the filtering function removes results ( association items ) from the search results or , in another exemplary embodiment the system shades filtered items . one potential embodiment of a search result for the word ‘ bank ’ filtered by ‘ media ’ is depicted in fig3 . fig3 is a screenshot of a search result filtered by media . in this case the media is video . fig4 is a screenshot of a further exemplary search result for the word “ bank ”, which has been filtered by age of the uploading users . the filter in fig4 is “ teens ” where the results selected by teenagers are boxed . the system enables the user to add and save items of interest , during the search process , into a personal storage feature in the system . in some embodiments of the system , an end user has an account on the online search engine / system of the immediate invention . once the account is accessed then a personal search cart saves the selected associations as requested by the end user . in embodiments which do not offer an account login feature , or for user without an account , the system provides a search cart feature for the duration of the session . when exiting , the system offers to save the contents of the search cart to a local storage facility ( e . g . hard drive of the pc ). in some embodiments of the invention , the system includes data - mining database 122 . data - mining database 122 stores all data gathered from uploading users during the process of interacting with aca 130 ( and / or the various downloaded / embedded / installed instances of the aca 130 ). the data includes user information as well as information regarding the uploading process . queries about specific associations found in the pool result in reports and analysis of data about the associations and the uploading users . for example : the frequencies of different associations to a specific association item , the percentage of users who associated one item with another specific item , the length of chain of associations between two items or more , the percentage of users with a specific personal characteristic who associated two items to one another , how many different chains of associations exist between two specific items , and so on . generally , the information for the reports is drawn from data - mining database 122 . this activity can be restricted to authorized users only . the visualization of association items and chains of associations in end user interface ( eui ) 110 reflects the structure of the pool . the eui enables users to select the type of visualization they prefer : linear or spatial representations are two exemplary visualization modes . fig6 is a screenshot of a potential embodiment of a linear representation of associations . fig7 is a screenshot of a potential embodiment of a spatial ( 3d ) representation of associations . the system can potentially have a great influence on social interaction over the internet . end users can choose individual or communal activities , with the system enabling and supporting online communication between users participating in communal activities . users are able to ask their online collaborators to provide associations to specific items ( possibly taken from the database , or a new item , not found in the database ). to enable collaboration , the system enables a user to build a user profile ( which can , potentially , be imported from other social networks ). the profile itself also supplies statistical information to the system regarding the uploaded associations from those registered / profiled users as well as information relating to user activity . the system furthermore supports multi - lingual activity , thereby better facilitating wider social and communal activity within the system . an exemplary communal activity is depicted in fig5 . fig5 is a screenshot depicting a communal activity . in the image , a user going by the name “ mark ” receives a request for associations for the word “ bank ” and uploads a video . the indication for the activity appears in the middle of the screen . potentially , the system stores profile information , including personal details regarding the characteristics of the users ( primarily uploading users , but in some embodiments , anonymous personal information of end users may also be recorded ), while protecting the privacy of the users . the profile information , in general , is used for statistical purposes . to this end , a user is merely identified by a number or designation , as opposed to name and address ( or other identifying information , such as id number , credit card number , etc .). the system allows , enables and encourages end users to interface with external applications such as google ™, wikipedia ™, dictionaries , youtube ™, flickr ™ and more , in order to collect additional information about each association item in the pool . an external application interface 119 , part of association logic 114 ( fig1 ), provides an interface between such external applications and the system of the immediate invention . furthermore , the associations may be uploaded directly from the external applications . fig8 a and 8 b depict screenshots of an exemplary manner of interfacing with a 3 rd party application . in fig8 a , a video association item is dragged into the youtube ™ icon on the search menu , at the left of the screen ( expanded from previously collapsed state ). this action results in opening the video on youtube 198 , which is the place of origin of the item , as is depicted in fig8 b . the system can provide a basis for a search algorithm that uses associations ( as opposed to keywords ) for better search results through the world wide web . the system will be integral to the creation of a global communal language ( meta - language ) that provides better associative global communication between people . the system provides the basis for the creation of a decision - making mechanism based on associations . the database serves as a basis for the creation of an association dictionary for research purposes , which maps relationships between concepts and ideas . fig9 is a flow diagram representing an embodiment of the basic flow of the innovative system . association database 120 is a central feature of the system . the database / association pool contains the associations , links between associations and characteristics of uploading users . step 1 : association items drawn from association database 120 serve as stimuli for association collecting application ( aca ) 130 . aca 130 collects association items ( and relationships between the items ) from uploading users . at the same time aca 130 also collects information regarding the uploading users ( e . g . age , profession , interests , social demographics etc .) as well as information relating to the uploading process ( e . g . response time and duration of interaction with the application ). in some embodiments of the invention , this user information is stored in data - mining database 122 as discussed above . the applications are downloaded from the server and embedded in social media networks such as facebook ™ and twitter ™. mobile applications as well as pc application are also envisioned as discussed above . the applications may be generic , all purpose item collectors or may be tailor made / configured , to seek association information regarding a particular item , concept or area of interest . step 2 : the association information is uploaded from aca 130 to association database 130 . the uploaded information is assimilated into database 120 . step 3 : the end user is presented with end user interface 110 , which can be generic for all end - users , or specifically created / configured for particular clients . end - users generally have the choice between a linear and spatial ( 3d ) visualization of search results . end users interact with association database by sending search queries and fetch requests . step 4 : association database 120 responds to search queries and fetch requests submitted by end users via eui 110 by present search results . in this manner , end users can navigate through the association pool , search for items in the pool , create or apply filters to search results and supply queries to the database and receive reports in response . step 5 : in some embodiments , all the information about the user searches is gathered for ai learning mechanism 112 to grow and develop . a further feature of the innovative system dubbed a “ concept board ” which provides a multi - functional unique planning and research tool for advertising companies , brand and marketing managers , academic institutions and so on , with an insight into the all important question “ what people think ?”. the concept board makes use of the three major components of the system , namely : association collection application ( aca ) 130 ( sometimes referred to as an ‘ association feeder ’); association database 120 ; and end user interface 110 ( which may additionally or alternatively be downloadable client software ) for fetching and analyzing information . the concept board accompanies the common process of planning and creating an advertising campaign in an advertising agency , starting with planning , strategy , creative concept and design , and following the campaign results . the concept board presents the output and the final view of associations from associations database 120 which are acquired using aca 130 in order to understand people and market incentives . the appearance , data interpretations , filters and trends are the most significant parameters which define the system . the interface strives to be familiar so as not to require the user to learn a new interface . concept board provides a range of features and tools for the step - by - step process of creating and managing a advertising campaign or creative project . the questions of : “ who is your audience ?”, “ how do they think ?”, “ what relates with what ?” and so on can be addressed via the various tools and features of the immediate system . order find out who the client audience is , what other fields of defining the search is critical , although keywords can always be changed . an exemplary list of main filters includes , but is not limited to : user localization , user age groups , association strength ( i . e . only strong connections ), association trend ( i . e . connections with declining trend over time ), association linkage ( i . e . connecting with less links ), user social status ( married , single , in a relationship ), user profession and user interests . in one embodiment , association database 120 is a data base of associations , which are simply words or expressions connected to each other . initially , association database 120 only includes a basic vocabulary of words for use as target words . these words are used as triggers for aca 130 . as it is preferable to have the most interesting phrases ( to the client ) presented as target words in order to receive the most valuable association information that can be used when creating a campaign or research project . understanding which words and phrases are interesting , what is in demand and how the audience reacts to the choice of target words is the job of a module dubbed “ target picker ”. in one embodiment , a simple algorithm is used to select target words . the algorithm takes into consideration the frequency of inputs , vocabulary which is prevalent for each word and additional parameters . in other embodiments , target picker is employed . target picker is based on an engine that helps the system decide which target word is the most suitable for each searcher . the system structures data in a manner that allows for measuring trends by splitting the data to fragments and reviewing changes between each fragment . while the invention has been described with respect to a limited number of embodiments , it will be appreciated that many variations , modifications and other applications of the invention may be made . therefore , the claimed invention as recited in the claims that follow is not limited to the embodiments described herein .