CONSTRUCTING A DATABASE OF VERIFIED INDIVIDUALS

Abstract

A method for constructing a database, comprises permitting a plurality of users to enter individual-associated data bits (IDBs) into a computerized system, each of the IDBs comprising at least one personal identifier relating to the user and relationship data comprising data on one or more related individuals and the nature of relationship; and processing the entered IDBs to generate an individual-identifier data set (IDS), one for each identified individual, being either one of the users or one of the related individuals and construct a database comprising IDSs of identified individuals.

Claims

1. A communication management system for managing communication between various individuals via a communication network, the system comprising a processor and a non-transitory computer readable memory and being connected to the communication network, wherein said processor is configured and operable to carry out the following: selectively communicate with a verified database of individuals, storing a plurality of individual related data record in association with a plurality of individuals, the individual related data record associated with a specific individual as stored in said verified database comprising: (i) data entered by said specific individual and including information regarding said specific individual and regarding one or more related individuals, and (ii) data assigned by the verified database to said individual related data record associated with the specific individual and comprising a reliability measure indicative of a degree of reliability of said specific individual based on degree of match of the information provided by said specific individual about said one or more related individuals and data about said one or more related individuals entered by one or more other individuals having associated individual related data records stored in the verified database, the reliability measure serving to classify the specific individual as a verified individual; being responsive to request data indicative of intended communication, via the communication network, between a first individual and a second individual who is the verified individual having the associated individual related data record stored in the verified database, to perform the following: identify first individual related data and communicate with the verified database to determine whether the first individual is classified by the verified database as a verified individual, and based on whether or not the first individual is classified as a verified one, generating management data to manage said request data with regard to said intended communication.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to understand the invention and to see how it may be carried out in practice, a preferred embodiment will now be described, by way of non-limiting example only, with reference to the accompanying drawings, in which:

[0069] FIG. 1 is a simplified schematic flowchart illustrating an interactive method for developing virtual communities, in accordance with an embodiment of the present invention;

[0070] FIG. 2 is a schematic pictorial illustration of an interactive system for developing virtual communities, in accordance with an embodiment of the present invention;

[0071] FIG. 3 is a simplified schematic flowchart illustrating a method for constructing IDSs and ascribing a reliability score in accordance with an embodiment of the present invention;

[0072] FIG. 4 exemplifies an embodiment of comparing data bits on an individual obtained from two different IDBs;

[0073] FIG. 5 is a simplified schematic flowchart illustrating an embodiment of step 320 of FIG. 3;

[0074] FIG. 6 is a simplified schematic flowchart illustrating an embodiment of step 120 of FIG. 1;

[0075] FIG. 7A is a simplified schematic flowchart illustrating an embodiment of step 130 of FIG. 1;

[0076] FIG. 7B is a simplified schematic illustration showing family structures and corresponding symbols, in accordance with an embodiment of the present invention;

[0077] FIG. 8 is a simplified schematic flowchart illustrating an embodiment of step 720 of FIG. 7A; and

[0078] FIG. 9 is a simplified schematic flowchart illustrating an embodiment of step 140 of FIG. 1.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

[0079] The present invention provides a novel method and system for creating a database and linking and networking individuals. In accordance with the invention a computerized system is provided that permits users of a computer network, particularly, but not exclusively, the Internet, to input data on themselves and related individuals and based on that, optionally with verification of data input by other individuals, a database of users and the relationship is constructed. The method and system of the invention have a variety of different utilities as will be elucidated by the different aspects and embodiments described below.

[0080] In the detailed description, numerous specific details are set forth in order to provide an understanding of the invention. However, it will be understood by those skilled in the art that these are specific embodiments and that the present invention may be practiced also in different ways that embody the characterizing features of the invention as described and claimed herein.

[0081] Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as “processing”, “computing”, “calculating”, “determining”, “deriving”, “generating” or the like, refer to the action and/or processes of a computer or computing system, or processor or similar electronic computing device, that manipulate and/or transform data represented as physical, such as electronic, quantities within the computing system's registers and/or memories into other data, similarly represented as physical quantities within the computing system's memories, registers or other such information storage, transmission or display devices.

[0082] Embodiments of the present invention may use terms such as, processor, computer, apparatus, system, sub-system, module, unit, device (in single or plural form) for performing the operations herein. This may be specially constructed for the desired purposes, or it may comprise a general purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer readable storage medium, such as, but not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, Disk-on-Key, smart cards (e.g. SIM, chip cards, etc.), magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), electrically programmable read-only memories (EPROMs), electrically erasable and programmable read only memories (EEPROMs), magnetic or optical cards, or any other type of media suitable for storing electronic instructions capable of being conveyed via a computer system bus.

[0083] The processes/devices presented herein are not inherently related to any particular electronic component or other apparatus, unless specifically stated otherwise. Various general purpose components may be used in accordance with the teachings herein, or it may prove convenient to construct a more specialized apparatus to perform the desired method. The desired structure for a variety of these systems will appear from the description below. In addition, embodiments of the present invention are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the inventions as described herein.

[0084] Similarly, the computerized system described herein is also not related to any physical entity. The computerized system may use general components, such as servers, routers, etc., or may use specialized apparatuses design specifically for use in accordance with the teaching of the invention.

[0085] It should be understood that the methods of the present invention are exemplified by the figures herein, but not limited thereto.

[0086] Reference is now made to FIG. 1, which is a simplified schematic flowchart 100 illustrating an interactive method for developing virtual communities, in accordance with an embodiment of the present invention.

[0087] A plurality of users are permitted to enter individual-associated data bits (IDBs) into a computerized system (step 110). The obtained IDBs include each a personal identifier, which includes data relating to the user and relationship data. The relationship data includes data on the user himself and data on one or more related individuals, typically, although not exclusively, individuals related to the data-entering individual by family. The relationship data also includes data on the nature of relationship with the related individuals (e.g. child, parent, sibling, etc.). The IDBs are processed (step 120), to generate IDSs (step 130), one for each identified individual. A database of IDSs is then constructed (step 140) which includes the IDSs of all identified individuals 142 and a relationship web 144, the latter including data on the relationship links between identified individuals. The relationship web may be one merged relationship web from all individuals or may include a plurality of such webs for different groups of identified individuals.

[0088] In a subsequent optional step, virtual communities may be formed 150-1, 150-2 . . . 150-N, based on personal characteristics of the identified individuals. A virtual community is a community of individuals formed within the virtual environment of a computer network or system. The virtual community typically includes individuals which have something in common. An example of a virtual community is a virtual community of individuals related through family ties. Other examples include individuals with common ancestry, common background, common hobbies or interest and many others. The concept of virtual community is no doubt well familiar to a person versed in the art and need not be elaborated further herein. By some embodiments of the invention, the virtual communities are automatically generated (based on the IDBs). For example, an identified individual may be found to have a common identifier with a group of other identified individuals, e.g. all have the same hobby, and the computer system may group such individuals automatically and send an electronic notification to all individuals to join this virtual community and generate also a website through which they may communicate. The identified individuals may join the virtual community at their own choice.

[0089] Reference is now made to FIG. 2, which is a schematic pictorial illustration of a computer system 200 in accordance with an embodiment of the present invention.

[0090] It should be understood that many variations to this system are envisaged, and this embodiment should not be construed as limiting. For example, a facsimile system or a phone device (wired telephone or mobile phone) may be designed to be connectable to a computer network (e.g. the Internet). Interactive televisions may be used for inputting and receiving data from the Internet.

[0091] System 200 typically includes a server utility 210, which may include one or a plurality of servers and one or more control computer terminals 212 for programming, trouble-shooting servicing and other functions. Server utility 210 is linked to the Internet 220 (constituting a computer network) through link 222, for running system website 223 and for communication with the users. Users may communicate with the server through a plurality of user computers 230, which may be mainframe computers with terminals that permit individual to access a network, personal computers, portable computers, small hand-held computers and other, that are linked to the Internet 220 through a plurality of links 224. The Internet link of each of computers 230 may be direct through a landline or a wireless line, or may be indirect, for example through an intranet that is linked through an appropriate server to the Internet. The system may also communicate through communication protocols of computers over the Internet which are known to a person versed in the art and will not be elaborated herein. Users may also communicate with the system through portable communication devices such as 3.sup.rd generation mobile phones 240, communicating with the Internet through a corresponding communication system (cellular system) 250 connectable to the Internet through link 252. As will readily be appreciated, this is a very simplified description, although the details should be clear to the artisan. Also, it should be noted that the invention is not limited to the user-associated communication devices—computers and portable and mobile communication devices—and a variety of others such as an interactive television system may also be used. The system 200 also typically includes at least one call and/or user support center 260. The service center typically provides both on-line and off-to line services to users from the at least one professional. The server system 210 is configured according to the invention to carry out the above-described method, based on data received from the users, being initiated in either pull or push mode.

[0092] Reference is now made to FIG. 3, which is a simplified scheme of IDBs received from two users—User-A 302 and User-B 304—and processed, for example as described above with reference to FIG. 1.

[0093] User-A and User-B input respective IDBs, IDBs-A 312 and IDBs-B 314. IDBs-A 312 includes personal identifiers of User-A 312-1 and relationship data pieces 312-2, 312-3 and 312-4 on related individuals X, C and D, respectively. The IDBs-B 314 similarly includes corresponding data pieces 314-1 through 314-4 on related individuals B, Y, E and F. As will be appreciated the personal identifiers 312-1 and 314-1 consist of a plurality of data bits that may characterize each of users A and B. Similarly, relationship data 312-2, 314-2 through 312-4, 314-4 include personal identifiers of the individuals as well as relationship data identifying the nature of the relationship between each of the users A and B to the related individuals.

[0094] As will also be appreciated, the example presented herein in which there are 3 related individuals in each of the IDBs is but an example and any number of related individuals may be included in the IDBs.

[0095] Upon processing of the IDBs (step 320) the computer system identifies that related individual X and Y are individuals B and A, respectively. In the next step 330 IDSs are generated. In total, the two IDBs 312 and 314 relate to 6 identified individuals and accordingly from these two IDBs a total of 6 IDSs 340-A, 340-B, 340-F can be generated for individuals A, B, F, respectively. A reliability score for each of these IDSs may also be generated. As IDS-A 340-A and IDS-B 340-B are generated each from data included in two IDBs, the relative reliability score that may be generated may be high as compared to that of the other illustrated IDBs for which the relative reliability score will be lower.

[0096] In fact, in this very simplified illustrative embodiment, the IDS for individual A 340-A and the IDS for individual B 340-B will include a main data record for individuals A and B which will include personal identifiers verified from two different sources. In addition, the IDS of individual A 340-A. for example, will also include relationship data on individuals B, C and D. However, as individuals C and F are related to individual B they may also be included as relationship data in the IDS of individual B 340-B.

[0097] In the case of a plurality of users entering IDBs, an IDS may be generated and may receive verification from a large number of sources.

[0098] Reference is now being made to FIG. 4 which exemplifies the comparing of data bits on an individual obtained from two different IDBs. Illustrated are data bits on individual A which are included in the IDBs inputted by User-A and in IDBs inputted by User-B.

[0099] Often data bits on an individual entered from one source may include inaccuracies or may be incomplete. As is illustrated in the example of FIG. 4, 9 different parameters on individual A are included. User-A has inputted data relating to his/her age, gender, place of birth, eye colour, date of birth, father's name, mother's name, brother's name and residence (A.sub.1 to A.sub.1, respectively). User-B has inputted corresponding data relating to User-A, save for bits A.sub.8 and A.sub.9. In some embodiments, the two sets of data bits are compared to provide a binary output of “match/mismatch” (“YES”/“NO”), relating to the two pieces of data that were compared. A more complex algorithm may be applied upon comparing of pieces of data on the same individual from multiple IDBs. In some other embodiments, the output may provide a score based on the closeness of match. For example, relating to the data in FIG. 4, if a binary scoring system is used then the father's name of User-A will be accepted (as both inputs match and are “Peter”) and if a score is provided, such as ten out of ten. In contrast, if the binary comparison system is used relating to the mother's name, the input will be rejected as “Mary” and “Marie” do not match, whereas, on a scoring basis, the score may be eight out of ten. Similarly, the age of user.sub.(I) may be rejected on a binary basis, but ascribed a score of 9 on a scoring basis. Regarding the place of birth, if a binary comparison system is used, then “Baltimore” and New York” do not match, whereas on a score system, a score of 4 out of 10, for example, may be provided. For brother name and residence, no data is provided in the IDBs of User-B and while in a binary comparison system this data may be rejected, in a scoring system this may receive a medium score such as 5. In the subsequent constructed IDS, in the case of the binary system, the data bits to be entered may include only those with a full match. Against this in a scoring system the data to be included may be such with a score above a certain number, e.g. a score greater than 5, in which case data bits A.sub.1, A.sub.2, A.sub.4, A.sub.5, A.sub.6 and A.sub.7 will be included. Furthermore, the IDS may be ascribed a total reliability score based on the individuals score a typically also factoring in other factors such as the number of IDBs used to construct the IDS, the number of related individuals, the reliability score of related individuals, etc.

[0100] In some embodiments, different weightings may be given to different data bits. For example, the weighting of data provided by an individual regarding himself may be twice that of a sibling relating to that individual and three times more than that received from a cousin regarding that individual. The degree of closeness of the user providing the information relating to the individual may be used to calculate the weighting. The weighting may therefore, for example, be calculated as a function of the number of verifications multiplied by the weighting assigned to each of the verifications (each of which is itself a function of the closeness of the two users in that verification).

[0101] Thus, in some embodiments the data provided by User-A regarding the mother's name, place of birth and age may be accepted, whereas these data provided by User-B may be rejected due to the lower weighting thereof.

[0102] It should be understood that many different other weighting models and comparison algorithms, including such that are known in the art, can be applied in accordance with the invention.

[0103] Reference is now made to FIG. 5, which is a simplified schematic flowchart 500 illustrating an example of implementation of the processing step 320 of the embodiment of FIG. 3.

[0104] In a binary comparison step 510, the individual data bits in the IDBs of two users, User.sub.N and User.sub.M (data bits 1 to I of the IDB.sub.N of User.sub.N, (DB.sub.1−I).sub.N, and data bits 1 to J of the IDB.sub.M of User.sub.M, (DB.sub.I−J).sub.M), for example User-A and User-B of FIGS. 3 and 4, are compared. For example, the age of User.sub.N is compared to that provided by User.sub.M in the comparing step 510. As is seen in FIG. 4, User-A has inputted her age to be 37, whereas User-B has indicated that the age of User-A is 38. In a checking step 520, the system checks to see if ((DB.sub.I).sub.N, and (DB.sub.J).sub.M) are identical. If the two data bits are identical, as in the case, for example, with respect to data bit A2 in FIG. 4, these data bits are stored 530 in the memory and then in a subsequent step 540 the system determines whether there are more data bits in the two IDBs to compare and if positive next data bits are selected 550 in the two IDBs and processes begins again. In case the comparison step 520 yields a negative result, the system proceeds directly to determining step 540.

[0105] In case the determining step 540 concludes that there are no more data bits in the two IDBs to compare, the system determines whether there are more IDB.sub.Ms to compare. If positive the next IDB is chosen 570, the next IDB being chosen from either a random list of IDBs or from a list of IDBs predetermined to have a high probability of matching data bits with the data bits included in IDB.sub.N.

[0106] Should comparison step 560 yield a negative result, the IDB.sub.N is rejected 575 and the system proceeds to next determining step 580 to determine whether there are more IDB.sub.Ns that should be compared to other IDBs. If in the affirmative, a new IDB.sub.N is obtained and the system returns to step 510. If there is no additional IDB.sub.N the operation stops 599.

[0107] In some other embodiments, the IDBs are stored and assigned reliability values. The reliability values may be accumulated for each user so as to ascribe to each user a general reliability value (GRV). The GRV may be used to choose selected users having relatively high GRVs for providing information to the system and for eliminating the less reliable users with lower GRVs.

[0108] Reference is now made to FIG. 6, which is a simplified schematic flowchart 600 illustrating an embodiment of step 120 for obtaining individual-identifier data set (IDS) of FIG. 1.

[0109] As is described hereinabove, and particularly with reference to FIGS. 1-5, system 200 is operative to obtain IDBs for a plurality of users. The IDBs can be obtained over the internet and/or via any of the apparatus shown in FIG. 2 or any other known in the art. IDBs from different users are compared in flowchart 600. For example, the IDBs accepted in the illustrated example of FIG. 3, may be further compared taking into account the relative distances, namely the number of relationship lines, between the two or more users. In some embodiments, this is a further process in addition to the comparisons of IDBs made with reference to FIGS. 3-5.

[0110] In other embodiments, this process at least partly replaces some of the steps described in FIGS. 3-5. For example, in flowchart 600, the IDBs of multiple users designated IDB.sub.1 . . . IDB.sub.N obtained respectively from users User.sub.1 . . . User.sub.N are compared in comparison step 610. These IDBs may be pieces of information provided by a user regarding himself and one or more other relevant individual. When a comparison of multiple sources of data is employed in step 610, one or more algorithms may be applied to eliminate any extraneous data processing (such as by rational design methods, known in the art).

[0111] For example, in step 610, the IDBs obtained from a plurality of users relating to various identifiers can be compared to obtain a set of relative fits of the various IDBs.

[0112] The output of step 610 may include at least one of the following; [0113] a) a fit of IDBs obtained relative to data in a memory or database; [0114] b) a fit of IDBs obtained from one or more users relative to one or more other users; [0115] c) a plurality of IDBs pertaining to different users; [0116] d) at least one indication of a relationship and/or distance between two or more users.

[0117] In a measuring step 620, the distance between two or more users is calculated or measured. Distance may be defined according to one or more set of to rules. One none-limiting example includes at least one of the following:

[0118] a) A relationship line between two blood relatives of a first degree is standardized to one standard length away (such as a user to his child, parent, sibling or spouse); a line of two standard relationship lines may be standardized by a blood relationship of two degrees (such as a user to his grandparent or grandchild, first cousin, niece or nephew, sibling-in-law, parent-in-law) etc.; and

[0119] b) A line between friends may be defined in relative terms of, for example: a lover, first degree; best friend, first degree (one standard distance away); social group friend, second degree (two standard distances away), work acquaintance, third degree (three standard distances away). The distance between at least some of the set of users may be calculated using the one or more set of rules and outputted. Thereafter, the calculated distances are stored in the system's computerized memory.

[0120] In an assigning reliability step 630, the reliability of data obtained from a user concerning another user is calculated as a function of the distance between them calculated from step 620. For example, blood relatives of three relative lengths away, may be assigned a higher reliability value (to be designated herein as “R.sub.D value” or “R.sub.D”) than friends of the same relative length away.

[0121] In a calculating match step 640, the match is calculated as a function of the R.sub.D value. In some cases, this may be a simple multiplication of match using the corresponding fit from step 610.

[0122] In an accepting step 650, all IDBs having a match of more than a pre-determined value are accepted and others rejected. In some embodiments, only the accepted IDBs are saved to memory.

[0123] In an optional filtering step 660, one or more algorithms are applied to the accepted IDBs. The filtering step is designed to reduce the number of IDBs to a minimum and to reject “non-essential IDBs”.

[0124] As already noted above, each IDB includes personal identifiers of the data-entering individual as well as data on related individuals. At the end of the process 670, an IDS, is defined for each of the identified individuals, which include the data-entering individual a well as the related individuals.

[0125] In a user checking step 680, it is checked to see if an IDS has been calculated for all of the identified individuals in all of the IDBs. If negative, a search is performed to find the next IDB in an update step 690 and then steps 610-680 are repeated until each of the identified individuals has a corresponding IDS. The IDSs are stored in the system memory 288.

[0126] The methods of the present invention for forming relationship webs are exemplified by, but not limited to the following example.

[0127] Reference is now made to FIG. 7A, which is a simplified schematic flowchart 700 for developing a relationship web, illustrating an embodiment of step 130 of FIG. 1.

[0128] In an IDS obtaining step 710, the IDSs of S users are obtained. This step may be similar to or different from flowchart 600 of FIG. 6. In some cases, the IDS of some users are stored in one database and others in another database. The databases may be merged, or combined into a third database in system 200.

[0129] The construction of an IDS should be understood in the virtual sense in the generation of an ensemble of data which serves as personal identifiers of an identified individual and his related individuals. In accordance with one embodiment, all components which constitute one IDS are stored as one data record. In accordance with other embodiments, a plurality of elements constituting a single IDS may be distributed between a plurality of data records.

[0130] In step 720 a relationship web, as described hereinabove, is created, for example on the basis of the obtained IDSs. This can include creating family trees, creating society hierarchical trees, creating work hierarchical trees, and the like. According to some embodiments of the invention, isolated relationship webs are created for each individual, showing all individuals having a certain predetermined number of relationship links to that individual. In accordance with other embodiments of the invention, the relationship web includes a plurality of individuals, e.g. all individuals residing in a geographical location, all individuals of a defined religion or sect, all individuals belonging to a certain culture, and to occasionally all individuals in the database.

[0131] One exemplary use of the invention is in the automatic construction of a family tree. Unlike many systems that permit a user to produce his family tree, in accordance with the invention the generation process is in fact automatic. Although the user enters some of the relevant data, other data relevant for the construction of a family tree for a specific individual may be entered by others, as is explained with reference to FIG. 4. Another unique feature of the invention that is permits merging of different family tree databases to one another.

[0132] FIG. 7B exemplifies family structures 760, 770, 790, in accordance with an embodiment of the present invention.

[0133] In accordance with some embodiments, each family or group of individuals can be provided with a family structure A, B or C. Family A represented by structure 760, has a mother 762, father 764 and child 766. The father and mother belong to generation N and the child to generation N+1. There may, of course, be a plurality of children (not shown). The mother and father are linked to the child with one line each 763 and 765. If married, the mother and father are linked with line 768.

[0134] In family B, represented by a one-parent family comprising structure 770, the father is (currently) unknown. The mother 772 is linked to child 776 by a solid line 773. The father 774 is linked to the child by a dotted line 775.

[0135] In some other cases, such as in family C, represented by structure 790, there are no known parents. Child 796 is linked to mother 792 and to father 794 by two dotted lines 793, 795 respectively.

[0136] The family structures of A, B and C may be denoted in “shorthand” as 782, 784 and 786 respectively, as is shown in FIG. 7B, where the child related node is denoted 783, and the parents related nodes—781 and 782 respectively.

[0137] These families may be real genetic families or families of people who have a certain social or work relationship.

[0138] Turning back to FIG. 7A, the building of the relationship web utilizes to creation of the family tree. The family units are sorted and categorized. Thereafter, they are compared and super-imposed so as to form one or more relationship webs with a proper location of each individual therein (step 730). In some cases, steps 720 and 730 may be combined or their order reversed. For example, the construction of the relationship web may comprise a combination of placing individuals and families within a web.

[0139] In some embodiments, the relationship web is formed by combining a plurality of family structures, particularly family trees, included in two or more IDSs. As already noted above, each IDS includes, among others, personal identifiers and relationship data on related individuals. Thus, as also already pointed out above, each IDS constitutes a sort of a family database and may be used for construction of a family tree. By combining relationship data included in different IDSs one family tree may be enlarged and merged to others.

[0140] Data included in an IDS is already verified through some mode of verification, particularly such IDSs constructed from IDBs entered by a plurality of individuals. Thus, data included in an IDS will have some degree of verification whereby each related individual included in an IDS is already a verified individual and accordingly family trees merged in that manner are verified family trees.

[0141] As already pointed out above, while an IDS contains data on related individuals, at the same time there is also an IDS for each of the related individuals. Thus, upon merging of family trees through association of family databases from two or a plurality of IDSs, all IDSs associated with their related individuals in the IDSs which constitute the basis for merger may be updated, automatically, for example, by addition of related individuals to such IDSs as a result of new individuals who now become related through such merger of family trees.

[0142] Reference is now made to FIG. 8, which is a simplified schematic flowchart 800 exemplifying the formation of a relationship web (step 720 in FIG. 7A).

[0143] In an obtaining step 810, data regarding an individual is obtained. The so obtained data may be sorted according to a number of different parameters such as, but not limited to, type and relative position (step 820). For example, data may be sorted into the type of relationship web, family, friend, work etc. The data may be sorted according to relative position, for example, age, generation, geographical location and sub-location.

[0144] In a data reduction step 830, the quantity of data regarding the individual is sifted using at least one algorithm, such as by rationally designing the required data set, as is known in the art. In some embodiments, this step may precede step 820 (the data is sifted before sorting), in some other embodiments (as shown in the figure), sifting is applied to the sorted data.

[0145] The reduced data is then processed to form a relationship web (step 840). For example, a relationship web may be formed by combining a plurality of family structures (such as 782, 784, 786 of FIG. 7B). The relationship web may typically have a multidimensional topology.

[0146] The data obtained in the previous step may then be used to associate individuals, including, but not limited, individuals belonging to a single family, in a relationship structure one versus the other. In some cases, an individual may appear in several different family structures, such as family trees. Such an individual can then be used as a reference point to connect between the different structures and/or family trees.

[0147] The methods of the present invention for verifying relative positions on relationship webs include, but are not limited to standard vector matching methods. Using algorithms known in the art, the reference points between different structures/family trees can be ascertained with a very high degree of probability.

[0148] Reference is made to FIG. 9, which is a simplified schematic flowchart 900 exemplifying formation of a virtual community according to embodiment of FIG. 1.

[0149] In a first filtering step 910, the IDSs obtained in step 130 of FIG. 1 are filtered, for example, with regard to one or more indicators such as residence, scope of interest, hobby, demographic parameters, and others. For example, cyclists in the Regent's Park area in London, UK, can be selected in this manner from all other individuals.

[0150] In a subsequent asking step 920, all such selected individuals may be asked, by the system, if they wish to join a “Regent's Park Cycling Community”. Of those asked, some may provide a positive reply by, for example, following a link which links them to a web page within the system website, that is formed for the “Regent's Park Cycling Community”. A membership list of such formed virtual community may then be drawn and may be made available to all the identified individuals who chose to join this virtual community.

[0151] In an assigning rules and fees step 940, the joining individuals are asked to pay a standard annual fee and to agree to abide by a set of rules. For example, the rules may include: a) paying the fee by April of each year, b) not riding on the pavement (sidewalk) in London, c) not riding within 50 meters of the Regent's Park mosque unless fully covered, d) always using a front and rear lamp from sunset to 8 am; and e) applying a membership sticker to the front handlebars of the bicycle so as to be easily identified.

[0152] In a checking step, 950, the joining individuals if the abide by the rules. If, for example, the user does not pay the annual fee by April, he may be rejected from the community. Likewise, he may be rejected if he is found to break any of the rules b) to e). If he conforms to the rules, he is retained within the community until the April of the subsequent year.

[0153] The methods of the present invention, exemplified by FIGS. 1, 3, 5, 6, 7A, 7B, 8 and 9 enable the formation of a database in which the reliability of the IDSs are high and the probability of the verified data being incorrect is low. Furthermore, the superimposition of the family structures as shown in FIG. 7B provide a verification of identity tool superior in reliability to any other tool known in the art heretofore. The identity of an individual is verified by the methods of the present invention with a high degree of probability. Furthermore, the relationship between different family members is also verified unequivocally. Thus, the databases formed using the methods of the present invention may be used for many applications, as are exemplified herein.

[0154] The IDS containing databases of the invention contain verified data on individual and their relationships. Such databases may be used, in accordance with the invention, for a variety of uses where verification of user's identity is important. Such may include, for example, a variety of applications in interne e-commerce, for virtual networking with real and identified individuals, etc. Some applications that make use of the verified data included in the database of the invention will be exemplified further below. The fact that the IDSs containing database of the invention includes real and verified information on the individual's and individual demographics, may be used for a variety of uses for which computer network have not been used hitherto. Such may include, for example, demographic research, opinion polls, referenda and elections.

[0155] For example, demographic surveys and opinion polls can be carried out, on the basis of gender, age, ethnic type, religion, nationality, social status, and generally any breakdown of parameters of the identified individuals. All such surveys and opinion polls may have a relatively high accuracy as the data in the IDS, and hence the breakdown of the individual into groups of individuals with identified parameters, is with a relatively high reliability.

[0156] Use of the database for marketing purposes, such as for targeted marketing to individual with selected personal identifiers, is another possible application of the invention. Such targeted marketing may be to individuals selected through certain personal identifiers, may be to a group of individuals belonging to a virtual community formed in accordance with the invention, typically such which relates to the interest focus of such a virtual community. For example, a computerized chess game may be marketed to a virtual community of chess players.

[0157] It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination.

[0158] Since the relative position of family members are reliably mapped according to the present invention, the nearest scheme may be located which may be important, for example, for purposes of adoption of individuals to related individuals, in order to allow to claim an inherited estate of an heirless deceased, etc.

[0159] The applications of the database of the present invention may be divided into some categories exemplified by: [0160] a) medical applications of family tree databases; [0161] b) commercial applications of family tree databases; [0162] c) Internet commercial applications of family tree databases; [0163] d) sectorial and targeted marketing; [0164] e) statistics and demographics or family tree databases; [0165] f) identifying lost persons; and [0166] g) family applications of family tree databases.

[0167] Some further embodiments of the present invention are directed to using the database for advertising campaigns. In some cases, the advertising campaign is selected from electronic media advertising, paper media advertising and banner advertising.

[0168] This invention is further directed to methods for using the database for a medical application. The medical application may be selected from a blood-related application, a non-genetic disease-related application, a genetic disease-related application, a drug application, a treatment application, an alternative medical treatment, and a personalized medical treatment.

[0169] Some embodiments of the present invention are directed to a method for using the database for a law-enforcement application. In some cases, the law-enforcement application is selected from, locating a criminal, locating a false identity, locating a relative of a deceased person, and locating an internet illegal transaction.

[0170] Additional embodiments of this invention are directed to methods for using the database for a family application. Sometimes, the family application may be the creation of a family portal, a family calendar, a family trip, a family forum, a family chat, and a family image databank.

[0171] Additional embodiments of this invention are directed to methods for using the database for a community application. In some cases the community application may be the creation of a community portal, a community calendar, a community trip, a community forum, a community chat, and a community image databank.

[0172] Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art.