Patent Application
20140372329
This application relates generally to candidate profile screening systems and more particularly to a technology for automatically sourcing and screening candidate profiles from online social networking systems.
Recruiting the right employee in a cost and time effective manner is vital to an organization's growth and sustainability. However, the task of gathering candidate profiles and identifying the right match from the gathered profiles can be labor intensive and challenging. One of the means of achieving this is by using technology to make the hiring process faster and simpler. However, the key barrier to the success of conventional employee referral programs is employee participation. The need for an employee to be personally involved in acts such as reading through the job posts, identifying relevant social connections, obtaining contact information or resume of the relevant social connections, submitting the contact information or resume to the employee referral app., etc., discourages the employees from actively participating in such programs. The result is a loss of potential candidates for a job opening. Moreover, the recruiting apps available in the market do not provide for screening the candidate profiles by considering any overlapping acquaintanceship of the candidates with the current employees.
Various embodiments of systems and methods for automatically sourcing and screening candidate profiles are described herein. In an aspect, the method involves receiving authorization from a participant to access the participant's account on a social networking system, where the participant is connected to one or more candidates in the social networking system. Further, the method includes extracting profiles corresponding to the one or more candidates that are connected to the participant in the social networking system. In an aspect, the profile data within each of the extracted profiles are classified into one or more categories. Further, each of the extracted profiles is scored according to a degree of match between the profile data associated with each extracted profile and a candidate search data. The candidate search data defines a set of criteria expected from a candidate profile. In another aspect, the extracted profiles are ranked based on the scores assigned to each of the extracted profiles. In yet another aspect, a feedback form is sent to the participant in response to receiving a selection of at least one of the ranked profiles.
These and other benefits and features of embodiments-will be apparent upon consideration of the following detailed description of preferred embodiments thereof, presented in connection with the following drawings.
The claims set forth the embodiments with particularity. The embodiments are illustrated by way of examples and not by way of limitation in the figures of the accompanying drawings in which like references indicate similar elements. The embodiments, together with its advantages, may be best understood from the following detailed description taken in conjunction with the accompanying drawings.
Embodiments of techniques for automatically sourcing and screening candidate profiles are described herein. In the following description, numerous specific details are set forth to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the embodiments can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail.
Reference throughout this specification to “one embodiment”, “this embodiment” and similar phrases, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one of the one or more embodiments. Thus, the appearances of these phrases in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Social networking communities, i.e., social structures hosted on social networking systems are made up of individuals (“members”) and a complex set of dyadic ties between these individuals. Online social networking systems provide a web-based services, platform, or site for facilitating the building of social relations (“connections”) among the members who may for example, share interests, activities, backgrounds, of real-life connections. Some of the web-based services include providing a representation of each member (often a profile), his/her social links, and means for members to interact over the internet, such as e-mail, instant messages, media streaming, etc. Examples of online social networking systems include Facebook.com, MySpace.com, LinkedIn.com, and EsqChat.com, where communities of individuals having virtual identities are enabled to connect and interact with other individuals. In addition to serving as a platform for members to meet and interact with fellow members, the online social networking systems facilitate the conglomeration of individuals with diverse social and professional backgrounds.
Current employees of an organization can help the organization identify and recruit talent. The Current employees may have worked with prospective employees who they think would be a good fit for the organization. Based on their past experiences with the prospective employees, the current employees may be able to provide insights into the prospective employees such as specific skills the prospective employees might have, personality traits, whether the prospective employees would be compatible with an organization's culture or get along with certain individuals in a group, and the type of positions the prospective employees would be interested in. The insights provided by the current employees help an organization identify the best employee candidates as well as filter out undesirable employee candidates. Social networking systems have become an important source of human resources due to the availability of information about relationships of users of the social networking service. In an example scenario, a recruitment team of an organization providing talent acquisition services for various departments of the organization, may, in order to identify a suitable candidate for job position, invite the current employees of the organization to sign up for a referral program hosted in a referral system. By signing up for the referral program, the employees authorize the recruitment personnel to access the social networking communities to which the employees are members to. The profiles of other members that are connected to the employees through the social networking community are accessed and a repository of such profiles is created. The repository then forms a candidate pool from which the recruitment personnel can identify suitable candidates for the job position. The concept of sourcing candidate profile and screening the candidate profiles from online social networking systems is described with reference to a conceptual system shown in
The profile ranking system 110 is communicatively coupled to a user device 130, the one or more social networking system 140 and the profiles repository 150.
A user interacts with the profile ranking system 110 and/or social networking systems 140 using a user device 130, which may be any suitable device that is capable of connecting to the profile ranking system 110 and/or social networking system 140. Examples of the user device 130 include a computer, Laptop, a Smartphone, a Personal Digital Assistant, a Notepad, Notebook, and Tablet PC. The user device is accessed by multiple participants who are members to an entity operating the profile ranking system 110.
In an example embodiment, the profile ranking system 110 is operated by the recruiting team of the organization and the participants are the employees of the organization. The participants are in turn members of online social networking communities hosted by one or more online social networking systems 140. The participants have an individual account and a virtual identity for each of the online communities that they are members of. The term “virtual identity” as used herein refers to a name, e-mail ID, login ID, or any other textual or graphical data that uniquely represents a member of an online social networking community. The participant's social networking account includes a web page that holds a “profile” of the participant that is partially or wholly visible to one or more other members (“connections”) that are connected to the participant in the social networking community. The participant's profile includes such information as the participant's contact information, academic background, employment history, current employer, skills, interests, hobbies, content posted by the participant, status updates, and other biographical data. Similarly, each of the participant's connections also has an individual profile in their respective accounts which can be viewed and accessed by the participant.
The participant being an owner of his/her account, may add a member of the community as a contact (the term “contact” having a meaning analogous to “friend” on Facehook.com or Myspace.com, or to “connection” on LinkedIn.com), whereby the added member would be a contact of the participant (and vice versa), such that, the participant can view additional web pages and/or information created by the added member from the added member's profile (and vice versa, respectively)After being added as a contact by the participant, the added member's virtual identity and profile are accessible to the participant from the participant's account. For example, the participant, can select an icon or link from his/her account, causing a web page displaying a list of links to the profiles of all contacts of the participant to be rendered, which links could be listed in alphabetical order based on the last name (or first name) of the contacts corresponding to the links, or based on other ranking criteria.
A participant in a referral program (i.e., employee of an organization) may initiate the referral process by simply authorizing the organization to access their social networking information. In an aspect, in order to access the participant's social networking information, the profile ranking system employs authorization standards such as OAuth. Such authorization standards provide for the participant to authorize third-party access to his/her server resources without sharing his/her credentials (typically, a username and password pair), using user-agent redirections. Using such authorization standards a client (herein, the profile ranking system) can access server resources on behalf of an end-user (herein, the participant). For example, when the participant signs up for the referral program, the participant is prompted by an application to grant access to the participant's social data stream. The participant may then trust his/her social networking information with the application by selecting an authorization option, for e.g., “I authorize” provided by the application on a user interface. The profile ranking system 110 may also send a request to a social networking system 140 for a participant's social information. The social networking system 140 may then send a request to the participant for authorization.
Referring back to
The profiles repository is accessed and a set of candidate profiles is invoked, at process block 220. In some embodiments, the set of candidate profiles is identified based on the candidate search data or criteria included in the candidate search data. In some embodiments, the profile repository is accessed and the set of candidate profiles is invoked responsive to receiving the candidate search data. In some embodiments, the set of candidate profiles is identified, accessed and retrieved from the profiles repository. The profiles repository stores profiles of candidates who are connected to participants of a referral program, through online social networking systems. In an aspect, the set of candidate profiles are invoked based on the relevance of the candidate profiles to the job position. In an aspect, the relevance is determined based on identifying key terms in the candidate profiles, where the key terms are determined from the candidate search data.
Further, at process block 230, the invoked candidate profiles are scored according to a degree of match between the candidate search data and profile data within the set of candidate profiles. In an aspect, the candidate search data is classified into multiple categories such as skills, work experience, education, roles, and mutual employee connections. The mutual employee connections criteria may be further classified into no. of mutual employee connections, designation of mutual employee connections, domain of mutual employee connections, overlapping work experience with mutual employee connections.
Similarly, the information (profile data) provided in each of the invoked candidate profiles are classified into multiple categories as those of the candidate search data. The profile data within each of the candidate profiles is compared with the candidate search data and a category by category match is determined. Based on a category-wise degree of match, each of the candidate profiles is scored. For example, a higher score is assigned to a candidate profile that has a greater degree of match between the profile data and the candidate search data as compared to another candidate profile that has a lesser degree of match between the profile data and the candidate search data. For example, if the candidate search data specifies “Marketing Executive with at least ten years of experience,” then those candidate profiles corresponding to candidates who have held a marketing executive position and with a minimum of ten years of experience will be assigned a higher score than other profiles that do not meet the requirement specified in the candidate search data. Specifically, the profile data within the category Roles, and Work experience is compared to the candidate search data classified as Roles and Work experience in order to determine the degree of match. In an embodiment, different weights are assigned to each of the multiple categories of the candidate search data. The candidate profiles are then scored based on determining a degree of match between the profile data and the candidate search data in each category and a score is assigned according to the degree of match and based on the weight assigned to that category. The weights and criteria which are inputs to the ranking system are configurable.
At process block 240, the candidate profiles that meet a threshold score are identified. In an aspect, the threshold score is a reference value, where profiles having a score equal to or greater than the reference value are deemed to have met the threshold score. The candidate profiles may be ranked in an ascending or descending order according to their respective scores and provided as a ranked list for further processing and/or analysis.
Further, at process block 250, the process determines whether the candidate profiles that meet the threshold scores have mutual connections with multiple participants. In other words, it is determined whether the identified candidate profiles are connected to two Of more of the multiple participants of the referral program. For example, a candidate profile may belong to a candidate who is a connection (or “Friend”) of a first participant on an online social network and also a connection of a second participant on the same or different online social network. Similarly, the candidate may be a connection to multiple other participants of the referral program. In an aspect, the mutual connections are identified based on determining that two or more participants of the referral program are linked to the same candidate profile. Also, the two or more participants serve as channels for the particular candidate profile from the online social networking system to the repository.
At process block 260, in an embodiment, a first graphical representation including the identified profiles and the mutual employee/participant connections corresponding to each of the identified profiles is generated. The first graphical representation is provided to be displayed on a graphical User Interface (GUI). At process block 270, a selection of one or more of the identified profiles is received through the GUI and in response a second graphical representation is generated. The second graphical representation shows the selected one or more identified profiles and connections to participant(s) that are connected to the one or more identified profiles. The graphical representations will be described in more detail with reference to
Further, in response to receiving a selection of one or more participants connected to a particular candidate profile, a feedback form is automatically sent to the selected one or more participants for appraisal of the candidate associated with the candidate profile. In an aspect, a participant may he selected based on a business relevance of the participant with the particular job position. The business relevance of the participant may be determined based on the individual scores assigned to the categories, namely, designation of mutual employee connections, domain of mutual employee connections, overlapping work experience with mutual employee connections etc., at process block 230. In an example, for a job position of a Business Analyst, four participants are connected to a candidate profile. If each of the four participants is employed in various functions of the organization such as HR, Marketing, Business Development, and Product development respectively, the feedback form is likely to be sent to the participant from Business Development. Alternatively, the business relevance of the participant may be determined separately using a participant score. In an aspect, the participant score is calculated based on assessing the designation of the participant in the organization, participant's period of employment with the organization, relevance of the domain in which the participant is employed in, etc. For example, a participant employed in a higher grade level than that of the job position may have a higher participant score than a participant employed in a lower or similar grade level. Similarly, a participant who has been employed in the organization for over five years may be scored higher than a participant that is employed for 1 year in the organization.
In an embodiment, the profile ranking system 110 is a computer having a processor that executes software instructions or code comprising a profile sourcing and screening tool, stored on a computer readable storage medium, to perform the processes illustrated with reference to
Further, the computer readable storage medium includes executable instructions for receiving candidate search data; invoking a set of candidate profiles from the profiles repository 150; scoring the invoked candidate profiles based on a degree of match between the candidate search data and profile data; identifying candidate profiles that meet a threshold score; identifying mutual connections of the identified profiles with multiple participants; generating a first graphical representation of the identified profiles and the mutual connections of the identified profiles with multiple participants; receiving a selection of one or more of the identified profiles through the graphical user interface; generating a second graphical representation showing the selected profile(s) and a linking of the selected profile(s) with one or more participants; and in response to receiving a selection of a participant in the second graphical representation, automatically sending a feedback form to the selected participant for appraising the candidate associated with the candidate profile linked to the participant.
In an aspect, the profiles repository 150 is a storage medium internal to the computer. The profiles repository 150, apart from storing the candidate profiles, holds information relating to the source of each candidate profile, i.e., information relating to the participant's virtual account and social networking system from which the candidate profile was received. For example, the profile repository may hold information such as the virtual identity of the participant for the virtual account, the name of the online social networking system, the type of relationship with the candidate, etc. The processor, may, in order to identify the mutual connections of a candidate profile with multiple participants, invoke a mapping of the virtual identities of participants with actual names of the participants in the referral program, from a memory location in the computer. The mapping is generated and/or maintained at the time when a participant signs up for the referral program and he/she provides information regarding his/her virtual identities and the names of the online social networking systems that the participant is member to. From the mapping, the processor determines whether a candidate profile has two or more participants connected to the candidate associated with the candidate profile.
In an example, as shown in
In an embodiment, the processor of the ranking system 110, in response to receiving a candidate search data, invokes a set of candidate profiles from the profiles repository 150. As shown in an example with reference to
The candidate profiles A, H, E, F, and M, hold personal and professional information (profile data) relating to the candidates associated with each profile. The profile data is classified into multiple categories according to a classification of the candidate search data. For example, if the candidate search data is classified into categories such as skills, work experience, education, roles, mutual employee connections, etc., then the profile data within each of the profiles A, H, E, F, and M is also classified into similar categories. In an aspect, the profile data is classified automatically following the selection of the candidate profiles A, H, E, F, and M based on the preliminary screening. The profile data can he automatically classified based on matching headers of the categories in the candidate search data and the profile data if the profile data is already classified into similar categories in the profile as rendered by the social networking system. On the other hand, however, if the profile data is not classified or is classified into a set of categories different from those of the candidate search data, then the processor automatically performs a classification of the profile data based on detecting in the profile data, key terms identified from the criteria provided under each category in the candidate search data.
Once the profile data within each of the profiles A, H, E, F, and M is classified into multiple categories, the processor performs a category-wise comparison of the candidate search data and the profile data to evaluate a degree of match. For example, the candidate search data may be classified into categories 1, 2, 3, 4, and 5 as criteria 1, criteria 2, criteria 3, criteria 4, and criteria 5 under each of the categories 1, 2, 3, 4, and 5 respectively. The profile data within each of the profiles A, H, E, F, and M is in turn classified into categories 1, 2, 3, 4, and 5. However, as shown in
Based on the comparison, the processor detects a category by category match between the profile data and the candidate search data and assigns a score to the profile data in each of the categories. The score for each of the profiles A, H, E, F, and M, is calculated as a cumulative score of the category-wise profile data scores for each profile. In the given example, profiles A, H, and E are identified as the profiles having the highest three scores among the profiles A, H, E, F, and M, based on the comparison. Alternatively, the profiles A, H, and E are identified as profiles having scores that meet threshold value. In an aspect, the processors assigns a score to each of the categories based on pre-defined weights assigned to each of the categories. For example, a particular job position may concern a role that involves handling confidential business information. In such a scenario, higher weightage may be given to criteria falling under the category “mutual employee connections” and “work experience” such that those candidates possessing a greater number of employee mutual connections and an experience of working with highly ethical organizations in the past will be assigned a higher score than those other candidates that do not satisfy these two criteria.
The process of scoring the profile data within the candidate profiles is illustrated with reference to only profiles A and H for simplicity, in the table shown in
Referring back to the example in
Subsequent to identifying the profiles that meet a threshold score, the processor may automatically send a feedback form to a selective number of participants associated with the identified profiles, through e-mail or other messaging services associated with the selected participants. In an aspect, the participants to whom the feedback form is to be sent can be selected based on certain criteria such as the designation of the participant in the organization, the domain in which the participant is employed, the period of employment of the participant in the organization, etc. The selection of the participants to whom the feedback form is sent may be automatically determined based on pre-defined rules. In yet another aspect, the selection of the participants for receiving the feedback form is based on determining a referral history of the participants. The term “referral history” as used herein refers to statistics regarding the outcome of previous referral program that the participant was involved in. Such statistics may include no. of candidates that were hired that were linked to the participant, performance of the hired candidates that were linked to the participant, feedback turn-around time and level of engagement by the participant in providing feedback, etc.
In the given example, the processor may send a feedback form to all the participants P1, P2, and P3 associated with the identified candidate profiles A, H, and E. Alternatively, the processor may select any one or more of the participants P1, P2, and P3 based on certain criteria. For example, the feedback form may be sent to participants associated with the profile that has the highest number of “mutual employee connections.” In the given example, candidate profile E is identified as the profile having a mutual employee connection with participants P2 and P3 through user accounts U2 and U3. A feedback form is then sent to the participants P2 and P3 requesting appraisal or recommendation for the candidate associated with the candidate profile E.
In an embodiment, the graphical representation is rendered on an interactive interface such that an input can be received by means of receiving a selection of all or a portion of the elements that form the graphical representation. In the given example, the nodes and/or edges may be selected by pointing a cursor over a particular node or edge and invoking an input means of an input device. The input is received as a selection of the particular node or edge that was pointed to and a corresponding function is enabled. In an aspect, receiving a selection of one or More of the candidate nodes via the user interface generates a second graphical representation as shown in
The second graphical representation 640 in
Some embodiments may include the above-described methods being written as one or more software components. These components, and the functionality associated with each, may be used by client, server, distributed, or peer computer systems. These components may be written in a computer language corresponding to one or more programming languages such as, functional, declarative, procedural, object-oriented, lower level languages and the like. They may be linked to other components via various application programming interfaces and then compiled into one complete application for a server or a client. Alternatively, the components maybe implemented in server and client applications. Further, these components may be linked together via various distributed programming protocols. Some example embodiments may include remote procedure calls being used to implement one or more of these components across a distributed programming environment. For example, a logic level may reside on a first computer system that is remotely located from a second computer system containing an interface level (e.g., a graphical user interface). These first and second computer systems can be configured in a server-client, peer-to-peer, or some other configuration. The clients can vary in complexity from mobile and handheld devices, to thin clients and on to thick clients or even other servers.
The above-illustrated software components are tangibly stored on a computer readable storage medium as instructions. The term “computer readable storage medium” should be taken to include a single medium or multiple media that stores one or more sets of instructions. The term “computer readable storage medium” should be taken to include any physical article that is capable of undergoing a set of physical changes to physically store, encode, or otherwise carry a set of instructions for execution by a computer system which causes the computer system to perform any of the methods or process steps described, represented, or illustrated herein. A computer readable storage medium may be a non-transitory computer readable storage medium. Examples of a non-transitory computer readable storage media include, but are not limited to: magnetic media, such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs, DVDs and holographic devices; magneto-optical media; and hardware devices that are specially configured to store and execute, such as application-specific integrated circuits (“ASICs”), programmable logic devices (“PLDs”) and ROM and RAM devices. Examples of computer readable instructions include machine code, such as produced by a compiler, and files containing higher-level code that are executed by a computer using an interpreter. For example, an embodiment may be implemented using Java, C++, or other object-oriented programming language and development tools. Another embodiment may be implemented in hard-wired circuitry in place of, or in combination with machine readable software instructions.
A data source is an information resource. Data sources include sources of data that enable data storage and retrieval. Data sources may include databases, such as, relational, transactional, hierarchical, multi-dimensional (e.g., OLAP), object oriented databases, and the like. Further data sources include tabular data (e.g., spreadsheets, delimited text files), data tagged with a markup language (e.g., XML data), transactional data, unstructured data (e.g., text files, screen scrapings), hierarchical data (e.g., data in a file system, XML data), files, a plurality of reports, and any other data source accessible through an established protocol, such as. Open DataBase Connectivity (ODBC), produced by an underlying software system (e.g., ERP system), and the like. Data sources may also include a data source where the data is not tangibly stored or otherwise ephemeral such as data streams, broadcast data, and the like. These data sources can include associated data foundations, semantic layers, management systems, security systems and so on.
In the above description, numerous specific details are set forth to provide a thorough understanding of embodiments. One skilled in the relevant art will recognize, however that the embodiments can be practiced without one or more of the specific details or with other methods, components, techniques, etc. In other instances, well-known operations or structures are not shown or described in details.
Although the processes illustrated and described herein include series of steps, it will be appreciated that the different embodiments are not limited by the illustrated ordering of steps, as some steps may occur in different orders, some concurrently with other steps apart from that shown and described herein. In addition, not all illustrated steps may be required to implement a methodology in accordance with the one or more embodiments. Moreover, it will be appreciated that the processes may be implemented in association with the apparatus and systems illustrated and described herein as well as in association with other systems not illustrated.
The above descriptions and illustrations of embodiments, including what is described in the Abstract, is not intended to be exhaustive or to limit the one or more embodiments to the precise forms disclosed. While specific embodiments of, and examples for, the invention are described herein for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize. These modifications can be made in light of the above detailed description. Rather, the scope is to be determined by the following claims, which are to be interpreted in accordance with established doctrines of claim construction.
