Patent Publication Number: US-2018039944-A1

Title: Job referral system

Description:
TECHNICAL FIELD 
     This application relates to the technical fields of software and/or hardware technology and, in one example embodiment, to system and method to facilitate a referral process in an on-line social network system. 
     BACKGROUND 
     An on-line social network may be viewed as a platform to connect people in virtual space. An on-line social network may be a web-based platform, such as, e.g., a social networking web site, and may be accessed by a use via a web browser or via a mobile application provided on a mobile phone, a tablet, etc. An on-line social network may be a business-focused social network that is designed specifically for the business community, where registered members establish and document networks of people they know and trust professionally. Each registered member may be represented by a member profile. A member profile may be represented by one or more web pages, or a structured representation of the member&#39;s information in XML (Extensible Markup Language), JSON (JavaScript Object Notation) or similar format. A member&#39;s profile web page of a social networking web site may emphasize employment history and education of the associated member. An on-line social network system also maintains information about various companies, as well as job postings. An on-line social network system may provide a service for providing information about job postings to members. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
       Embodiments of the present invention are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like reference numbers indicate similar elements and in which: 
         FIG. 1  is a diagrammatic representation of a network environment within which an example method and system to facilitate a referral process in an on-line social network system may be implemented; 
         FIG. 2  is block diagram of a system to facilitate a referral process in an on-line social network system, in accordance with one example embodiment; 
         FIG. 3  is a flow chart illustrating a method to facilitate a referral process in an on-line social network system, in accordance with an example embodiment; 
         FIG. 4  is a User Interface screen for presenting an employee with an invitation to refer one or more of their connections for some of the job positions available at the employee&#39;s organization, in accordance with an example embodiment; and 
         FIG. 5  is a diagrammatic representation of an example machine in the form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. 
     
    
    
     DETAILED DESCRIPTION 
     A method and system to facilitate a referral process in an on-line social network system is described. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of an embodiment of the present invention. It will be evident, however, to one skilled in the art that the present invention may be practiced without these specific details. 
     As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Similarly, the term “exemplary” is merely to mean an example of something or an exemplar and not necessarily a preferred or ideal means of accomplishing a goal. Additionally, although various exemplary embodiments discussed below may utilize Java-based servers and related environments, the embodiments are given merely for clarity in disclosure. Thus, any type of server environment, including various system architectures, may employ various embodiments of the application-centric resources system and method described herein and is considered as being within a scope of the present invention. 
     For the purposes of this description the phrase “an on-line social networking application” may be referred to as and used interchangeably with the phrase “an on-line social network” or merely “a social network.” It will also be noted that an on-line social network may be any type of an on-line social network, such as, e.g., a professional network, an interest-based network, or any on-line networking system that permits users to join as registered members. For the purposes of this description, registered members of an on-line social network may be referred to as simply members. 
     Each member of an on-line social network is represented by a member profile (also referred to as a profile of a member or simply a profile). The profile information of a social network member may include personal information such as, e.g., the name of the member, current and previous geographic location of the member, current and previous employment information of the member, information related to education of the member, information about professional accomplishments of the member, publications, patents, etc. The profile information of a social network member may also include information about the member&#39;s professional skills, such as, e.g., “product management,” “patent prosecution,” “image processing,” etc.). The profile of a member may also include information about the member&#39;s current and past employment, such as company identifications, professional titles held by the associated member at the respective companies, as well as the member&#39;s dates of employment at those companies. 
     A member profile is also associated with social links that indicate the associated member&#39;s connection to other members of the social network. Any two members of an on-line social network may indicate their mutual willingness to be “connected” in the context of the social network, in that they can view each other&#39;s profiles, profile recommendations and endorsements for each other and otherwise be in touch via the social network. Members who are connected in the context of a social network may be termed each other&#39;s “connections” and their respective profiles are associated with respective connection links indicative of these two profiles being connected. Two members may be referred as each other&#39;s first degree connections when their respective profiles include connection links that indicate that these two profiles are connected. When a member (let&#39;s call her member A) is not connected to another member (let&#39;s call him member B), but is connected to member C, who is connected to member B, member A and member B are considered each other&#39;s second degree connections in the on-line social network. A member&#39;s connections, both first degree connections and higher degree connections are refereed to, collectively, as the member&#39;s network. 
     As mentioned above, an on-line social network system also maintains information about various companies, as well as so-called job postings. A job posting, for the purposes of this description is an electronically stored entity that includes information that an employer may post with respect to a job opening. The information in a job posting may include, e.g., the industry, job position, required and/or desirable skills, geographic location of the job, the name of a company, etc. Member profiles and job postings are represented in the on-line social network system by feature vectors. The features in the feature vectors may represent, e.g., a job industry, a professional field, a job title, a company name, professional seniority, geographic location, etc. 
     In one embodiment, the on-line social network system includes or is in communication with a so-called recommendation engine that may be part of or in communication with the on-line social network system. A recommendation engine may be configured to determine whether a member profile represents a potential good candidate for a job advertised by a particular job posting, and, if so, present that job posting to the member, e.g., via an email, on the news feed page of the member, as a pop-up message when the member accesses the on-line social network system using a browser application of a mobile app, in response to a job search request initiated by the member within the on-line social network system, etc. A recommendation engine may be provided in the form of a binary classifier that can be trained using a set of training data. The set of training data can be constructed using historical data, such as, e.g., data that indicates whether a certain job posting presented to a certain member resulted in that member applying for that job, whether the member viewed the job posting, shared it with other members, etc. A trained binary classifier may be used to generate, for a (member profile, job posting) pair, a value indicative of how well the job presented in the posting is suited for the member represented by the member profile. This value may be referred to as a relevance score and may be calculated as cosine similarity between the respective feature vectors of the member profile and the job posting from a (member profile, job posting) pair. A job posting may be recommended to a member if, e.g., the associated relevance score is greater than a predetermined threshold value. 
     When a job position opens up at a company, it may be beneficial to solicit referrals for the job from people who are currently employed at the company. A potential challenge, however, is that an employee is not necessarily aware of what jobs the company is trying to fill, and, even if provided with access to job openings listed by their company, some employees may find it inconvenient or time consuming to select, from all job openings, those jobs that would be potentially suitable for any of the employee&#39;s contacts in the on-line social network system. A technological solution to these challenges is a computer-implemented referral system that utilizes data available in the on-line social network system. A referral system may be part of or in communication with the on-line social network system and may also include or be in communication with a recommendation engine. In some embodiments, a recommendation engine may include or be in communication with a referral system. For the purposes of this description, a system comprising modules that, collectively, provide functionality of a recommendation engine and a referral system, is referred to as a referral system. 
     In one embodiment, a referral system is configured to select a set of job postings advertising jobs at a particular company for presentation to a member of the on-line social network system, who is an employee of that company, with a suggestion that the member may wish to refer someone from their network for a job from the presented set of job postings. It will be noted that, while an organization, at which employment may be offered, may be an entity other than a company, the term “company” is used for the purposes of this description to refer to any organization, at which employment may be offered. 
     The referral system accesses a member profile representing an employee of a certain company. A member profile representing an employee of a certain company may be referred to as an employee member profile. For each job posting that represents a job at the target organization, the referral system generates a so-called presentation score with respect to the employee member profile. The presentation score for a job posting calculated with respect to the employee member profile reflects the likelihood that the employee represented by the employee member profile refers someone from their network for the job represented by that job posting. The presentation score for a job posting may be expressed as P(j|E), where J is a job posting and E is the employee member profile representing an employee of a company indicated in the job posting J. The presentation score P(J|E) is calculated as shown in Equation (1) below. 
     
       
         
           
             
               
                 
                   
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     As expressed in Equation (1), the presentation score P(J|E) is the sum of intermittent scores generated for respective connected member profiles representing connections of the employee. An intermittent score presentation score is a combination of the value P(J, ci|E) reflecting the probability of candidate ci being referred for the job represented the job posting J, given employee profile E and the value P(ci). The value P(ci) indicates whether a member represented by the connected member profile Ci is a qualified candidate for the job represented the job posting J. In one embodiment, P(ci) is zero if a member represented by the connected member profile Ci is a qualified candidate for the job represented the job posting J and one if the member is not qualified candidate for the job represented the job posting J. For example, given a job posting advertising a software developer position, a candidate c1 who is currently employed as a software developer is a qualified candidate, while a candidate c2 who is currently employed as an attorney is not a qualified candidate. In this scenario, the P(c1) equals one or equals one divided by the total number n of connected member profiles. 
     The probability P(J, ci|E), which may be referred to as the referral probability, is calculated as shown in Equation (2) below. 
         P ( j,ci|E )= P ( J|i,E ) P ( ci|E )= P ( J|ci ) P ( J|E ) P ( ci|E )  Equation 2
 
     As expressed in Equation (3), the presentation score P(J, ci|E) is a combination of the value P(J|ci) reflecting fitness of a candidate represented by the connected member profile C for the target job represented by the job posting J, the value P(J|E) reflecting familiarity of the employee E with the target job represented by the job posting J. and the value P(ci|E) reflecting connection strength between the employee member profile that represents the employee E and the connected member profile ci. The value P(J|ci) may be referred to as a fitness score and may be calculated as cosine similarity between the respective feature vectors of the connected member profile ci and the job posting J. The value P(J|E) may be referred to as a familiarity score and may be calculated as cosine similarity between the respective feature vectors of the employee member profile E and the job posting J. The value P(ci|E) may be referred to as a connection strength score and may be calculated as cosine similarity between the respective feature vectors of the connected member profile ci and the employee member profile E. 
     Both values P(J|ci) and P(J|E) are relevance scores that can be calculated by a recommendation engine for the employee member profile that represents the employee E and for the connected member profile ci in relation to the target job represented by the job posting J, respectively. When relevance scores are being used to determine a presentation score for a (connected member profile, job posting) pair with respect to a particular employee who is invited to make a referral, the relevance score P(J|ci) is termed a fitness score (to indicate how fit is the candidate for the job), and the relevance score P(J|E) is termed a familiarity score (to indicate how familiar is the employee with the job). 
     In some embodiments, the referral system is also configured to determine, given a job posting that advertises a job at a target organization, a member profile of an employee of the target organization, that represents an employee who is more likely to refer qualified candidates from their network for the advertised job at their company as compared to member profiles representing other employees at the target organization. The referral system accesses a job posting that represents a job at a target organization, determines a set of member profiles that indicate that the associated members are currently employed at the target organization and select one or more member profiles that include features indicative of a high likelihood that the associated employee refers someone from their network for the advertised position. For example, for each employee member profile, the referral system calculates a presentation score with respect to a certain job posting (a target job posting), the presentation score indicative of the likelihood that the employee represented by that employee member profile refers someone from their network for the position advertised by the job posting. The referral system may then communicate a message to the employee represented by the employee member profile with the highest presentation score, inviting the employee to refer someone from their network for the target job at their company. A presentation score P(J|E) with respect to a particular employee member profile E and a job posting J may be calculated using Equation (1) shown above. 
     In some embodiments, the referral system may be configured exclude from consideration those connected member profiles that represent members who are employed at the same company as the subject employee. The referral system may also exclude from consideration those connected member profiles that represent members who have been employed at the target organization for less than a certain period of time (e.g., less than six months) or for greater than a certain period of time (e.g., greater than five years). 
     The referral system uses respective presentation scores generated for the job postings to determine which of these job postings are to be selected for inclusion into a referral user interface for presentation to the employee. For example, a certain number or a certain percentage of the job postings that have the highest presentation scores, as compared to respective presentation scores generated for other job postings, are used in generating a referral user interface for presentation to the subject employee. An example referral user interface screen  400  illustrated in  FIG. 4  presents an employee with an invitation to refer any of their connections in the on-line social network system for one or more jobs from the selected set of job postings. An example referral system may be implemented in the context of a network environment  100  illustrated in  FIG. 1 . 
     As shown in  FIG. 1 , the network environment  100  may include client systems  110  and  120  and a server system  140 . The client system  120  may be a mobile device, such as, e.g., a mobile phone or a tablet. The server system  140 , in one example embodiment, may host an on-line social network system  142 . As explained above, each member of an on-line social network is represented by a member profile that contains personal and professional information about the member and that may be associated with social links that indicate the member&#39;s connection to other member profiles in the on-line social network. Member profiles and related information may be stored in a database  150  as member profiles  152 . The database  150  also stores job postings  154 . It will be noted that, in some embodiments, the database  150  is considered to be part of the on-line social network system  142 . 
     The client systems  110  and  120  may be capable of accessing the server system  140  via a communications network  130 , utilizing, e.g., a browser application  112  executing on the client system  110 , or a mobile application executing on the client system  120 . The communications network  130  may be a public network (e.g., the Internet, a mobile communication network, or any other network capable of communicating digital data). As shown in  FIG. 1 , the server system  140  also hosts a referral system  144  and a recommendation engine  146 . It will be noted that, in some embodiments, the referral system  144  and the recommendation engine  146  are considered to be part of the on-line social network system  142 . The recommendation engine  146  is configured to match member profiles with respective job postings stored in the database  150 , as mentioned above. 
     The referral system  144  may be configured to generate a set of job postings for presentation to a member of the on-line social network system who is an employee of a particular target organization (or company) with a suggestion, explicit or implicit, that the member may wish to refer someone from their network for one of the presented jobs at their company, as already described above. In one embodiment, the referral system  144  accesses a member profile representing an employee of a certain company. For each job posting that represents a job at the target organization, the referral system generates a presentation score that reflects the likelihood of the employee referring someone from their network for the job represented by that job posting. The referral system  144  uses respective presentation scores generated for the job postings to determine which of these job postings are to be selected for inclusion into a referral UI for presentation to the employee, e.g., on a display device of the client system  110  or on a display device of the client system  120 . The presentation scores may be calculated using Equation (1) and Equation (2) shown above. An example referral system  144  is illustrated in  FIG. 2 . 
       FIG. 2  is a block diagram of a system  200  to facilitate a referral process in an on-line social network system  142  of  FIG. 1 . As shown in  FIG. 2 , the system  200  includes an employee selector  210 , a subject set selector  220 , a presentation score generator  230 , a presentation set selector  240 , a referral user interface generator  250 , and a presentation module  260 . The employee selector  210  is configured to access, from the database  150  of  FIG. 1 , an employee member profile representing an employee of a target organization in the on-line social network system  142  of  FIG. 1 . 
     The subject set selector  220  is configured to access, from the database  150  of  FIG. 1 , a set of job postings in the on-line social network system and a set of connected member profiles in the on-line social network system, each item from the set of job postings representing a position at the target organization, each profile in the set of connected member profiles including a link indicating connection relationship with the employee member profile. In some embodiments, the subject set selector  220  may be configured to consider only those connected member profiles that include an indication that the associated member has worked at the target organization no less than a certain period of time (e.g., no less than 6 months or a year) and no longer that a certain period of time (e.g., not longer than five or six years). 
     The presentation score generator  230  is configured to generate, for each job posting from the set of job postings, respective presentation scores. A presentation score generated for a job posting from the set of job postings reflects a likelihood of a referral by the employee of any of the employee&#39;s connections for a job represented by the job posting. 
     In one embodiment, the presentation score generator  230  calculates the respective presentation scores using Equation (1) described above. As explained above, the presentation score for a job posting may be calculated as the sum of intermittent values calculated with respect to connected member profiles from a set of connected member profiles as a product of a qualified candidate probability and a referral probability. The presentation score generator  230  calculates the qualified candidate probability with respect to a connected member profile based, e.g., on a result of comparing a job title feature from the job posting with a job title feature from the connected member profile. 
     The referral probability is generated based on (1) fitness of a candidate represented by the connected member profile for a job represented by the job posting, (2) familiarity of the employee of the target organization with a target job represented by the job posting, and (3) connection strength between the employee member profile and the connected member profile. The familiarity value for the employee member profile and a job posting from the subject pair may be calculated as cosine similarity between respective feature vectors of the employee member profile and the job posting. The fitness value may be calculated for the connected member profile and the job posting as cosine similarity between respective feature vectors of the connected member profile and the job posting. The connection strength value may be calculated for the employee member profile and the connected member profile as cosine similarity between respective feature vectors of the employee member profile and the connected member profile. The presentation score generator  240  may be configured to assign respective weights to the familiarity value, the fitness value and the connection strength value, and to use these respective weights in combining these values for generating a presentation score. As mentioned above, the features in the feature vectors may represent, e.g., a job industry, a professional field, a job title, a company name, professional seniority, geographic location, etc. 
     The presentation set selector  240  is configured to select presentation postings from the set of job postings based on the respective presentation scores generated for the set of job postings. For example, a certain number or a certain percentage of job postings with the highest presentation score may be selected for presentation to the employee using a UI screen such as, e.g., illustrated in  FIG. 4  described above. 
     The referral user interface generator  250  is configured to generate a referral user interface, such as, e.g., illustrated in  FIG. 4 , comprising representation of the presentation postings. The referral user interface generator  250  is configured to provide a referral visual control to be displayed as associated with a presentation of a job posting from the presentation postings. The referral visual control (e.g., a “Refer” button) is actionable to communicate a referral message to the on-line social network system  142 , where the referral message indicates a referral of a candidate represented by a member profile for the job represented by the job posting. 
     The presentation module  260  is configured to cause displaying of the referral user interface on a display device, e.g., on a display device of the client system  110  of  FIG. 1  or on a display device of the client system  120  of  FIG. 1 . Some operations performed by the system  200  may be described with reference to  FIG. 3 . 
       FIG. 3  is a flow chart of a method  300  to facilitate a referral process in an on-line social network system  142  of  FIG. 1 . The method  300  may be performed by processing logic that may comprise hardware (e.g., dedicated logic, programmable logic, microcode, etc.), software (such as run on a general purpose computer system or a dedicated machine), or a combination of both. In one example embodiment, the processing logic resides at the server system  140  of  FIG. 1  and, specifically, at the system  200  shown in  FIG. 2 . 
     As shown in  FIG. 3 , the method  300  commences at operation  310 , when the employee selector  210  accesses, from the database  150  of  FIG. 1 , an employee member profile representing an employee of a target organization in the on-line social network system  142  of  FIG. 1 . The subject set selector  220  of  FIG. 2  accesses, from the database  150 , a set of job postings and a set of connected member profiles at operation  320 . The accessed job postings and the connected member profiles are such that each item from the set of job postings represents a position at the target organization, and each profile in the set of connected member profiles includes a link indicating connection relationship with the employee member profile. At operation  330 , the presentation score generator  230  generates, for each job posting from the set of job postings, respective presentation scores using the methodology and the equation described above. A presentation score generated for a job posting from the set of job postings reflects a likelihood of a referral by the employee of any of the employee&#39;s connections for a job represented by the job posting, At operation  340 , the presentation set selector  240  selects presentation postings from the set of job postings based on their respective presentation scores. At operation  350 , the referral user interface generator  250  generates a referral user interface, such as, e.g., illustrated in  FIG. 4 . The presentation module  260  causes displaying of the referral user interface on a display device, e.g., on a display device of the client system  110  of  FIG. 1  or on a display device of the client system  120  of  FIG. 1 , at operation  360 . 
     The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules. 
     Similarly, the methods described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations. 
       FIG. 5  is a diagrammatic representation of a machine in the example form of a computer system  500  within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine operates as a stand-alone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. 
     The example computer system  500  includes a processor  502  (e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), a main memory  504  and a static memory  506 , which communicate with each other via a bus  505 . The computer system  500  may further include a video display unit  510  (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system  500  also includes an alpha-numeric input device  512  (e.g., a keyboard), a user interface (UI) navigation device  514  (e.g., a cursor control device), a disk drive unit  516 , a signal generation device  518  (e.g., a speaker) and a network interface device  520 . 
     The disk drive unit  516  includes a machine-readable medium  522  on which is stored one or more sets of instructions and data structures (e.g., software  524 ) embodying or utilized by any one or more of the methodologies or functions described herein. The software  524  may also reside, completely or at least partially, within the main memory  504  and/or within the processor  502  during execution thereof by the computer system  500 , with the main memory  504  and the processor  502  also constituting machine-readable media. 
     The software  524  may further be transmitted or received over a network  526  via the network interface device  520  utilizing any one of a number of well-known transfer protocols (e.g., Hyper Text Transfer Protocol (HTTP)). 
     While the machine-readable medium  522  is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “machine-readable medium” shall also be taken to include any medium that is capable of storing and encoding a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of embodiments of the present invention, or that is capable of storing and encoding data structures utilized by or associated with such a set of instructions. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical and magnetic media. Such media may also include, without limitation, hard disks, floppy disks, flash memory cards, digital video disks, random access memory (RAMs), read only memory (ROMs), and the like. 
     The embodiments described herein may be implemented in an operating environment comprising software installed on a computer, in hardware, or in a combination of software and hardware. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is, in fact, disclosed. 
     Modules, Components and Logic 
     Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied (1) on a non-transitory machine-readable medium or (2) in a transmission signal) or hardware-implemented modules. A hardware-implemented module is tangible unit capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more processors may be configured by software (e.g., an application or application portion) as a hardware-implemented module that operates to perform certain operations as described herein. 
     In various embodiments, a hardware-implemented module may be implemented mechanically or electronically. For example, a hardware-implemented module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC)) to perform certain operations. A hardware-implemented module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware-implemented module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. 
     Accordingly, the term “hardware-implemented module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily or transitorily configured (e.g., programmed) to operate in a certain manner and/or to perform certain operations described herein. Considering embodiments in which hardware-implemented modules are temporarily configured (e.g., programmed), each of the hardware-implemented modules need not be configured or instantiated at any one instance in time. For example, where the hardware-implemented modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware-implemented modules at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware-implemented module at one instance of time and to constitute a different hardware-implemented module at a different instance of time. 
     Hardware-implemented modules can provide information to, and receive information from, other hardware-implemented modules. Accordingly, the described hardware-implemented modules may be regarded as being communicatively coupled. Where multiple of such hardware-implemented modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the hardware-implemented modules. In embodiments in which multiple hardware-implemented modules are configured or instantiated at different times, communications between such hardware-implemented modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware-implemented modules have access. For example, one hardware-implemented module may perform an operation, and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware-implemented module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware-implemented modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information). 
     The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules. 
     Similarly, the methods described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or processors or processor-implemented modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations. 
     The one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., Application Program Interfaces (APIs).) 
     Thus, a method and system to facilitate a referral process in an on-line social network system has been described. Although embodiments have been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader scope of the inventive subject matter. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.