WO2022172251A1

WO2022172251A1 - Method and system for auto filtering candidates

Info

Publication number: WO2022172251A1
Application number: PCT/IB2022/051310
Authority: WO
Inventors: Arie BICHLER; Matan BICHLER; Yaniv Ozana; Oren Tal
Original assignee: L.B.C Software And Digital Solutions Ltd.
Priority date: 2021-02-15
Filing date: 2022-02-15
Publication date: 2022-08-18

Abstract

Methods and systems, which employ a computerized platform, provide entities, searching to fill a position, such as a job, with a list of suitable candidates rapidly and in real time.

Description

METHOD AND SYSTEM FOR AUTO FILTERING CANDIDATES

CROSS REFERENCES TO RELATED APPLICATIONS

[0001] This application is related to and claims priority from commonly owned U.S. Provisional Patent Application, Serial No. 63/149,366, entitled: Method And System For Auto Filtering Candidates, filed on February 15, 2021, the disclosure of which is incorporated by reference in its entirety herein.

TECHNICAL FIELD

[0002] The present disclosure relates to methods and systems for auto filtering candidates for employment and other positions based on candidate qualifications and responses.

BACKGROUND

[0003] Recruiting candidates for jobs, employment and other positions, is ever challenging. While there are many potential candidates for a job, there are few candidates that are truly a good fit for the job. Traditional methods of recruiting candidates is extremely time consuming, involving manually searching through endless amounts of Resumes (Curriculum Vitals (CVs)), notifying the potential candidate and then interviewing the candidate, either by phone or internet, and/or in person, and then actually making the hiring decision. While the CVs are screened, there may be other factors unknown to the screener, which make a good candidate unsuitable for the job, which are only found out during an interview. This is too late, as valuable resources have already been expended on this candidate, who is not right for the job. Accordingly, the costs involved with these traditional methods of candidate recruiting are high, both in soft costs, in sorting through the resumes and contacting potential candidates, and hard costs, associated with telephone/internet, and in-person interviews.

[0004] For example, recruiting agencies and large companies receive thousands of CV’s, Linkedln pages, candidate submission materials, and other documents, including writing samples, presentations, and the like, in various formats, e.g., MSWORD, PDF, JPEG, and the like, collectively referred to as “candidate documents”, every day. These candidate documents are typically stored in files, if stored at all. When a job position comes up, the recruiter may search the candidate documents manually, or use computers to perform basic word searches of the candidate documents. Based on large numbers of CVs alone, substantial time and resources are spent in reviewing all of the CVs, and a manual search may simply miss the most suitable candidates. Also, a word search is just too basic, and may produce so many hits, that the search was not of much value, again, missing the most suitable candidates. Additionally, some file formats are not suitable and/or convertible for computer searching, so even if possible, these documents will not be reviewed, possibly missing suitable candidates.

[0005] Another problem with using CVs is that they may not be updated, or may contain inaccurate information. For example, candidate addresses and contact details may be old, licenses listed in the CVs may not be valid or expired, and certain information may not be fully accurate. This leads to time being wasted in recruiting these candidates, and interviewing a candidate with inaccurate CV information may be a waste of time and resources.

SUMMARY OF THE DISCLOSURE

[0006] The present disclosure provides a computerized platform and computer- implemented methods, where a job order can be submitted, and almost instantaneously, within seconds or minutes, and typically in real time, for example, find suitable candidates. The platform may then arrange the suitable candidates which have been found, into a short list, with the highest qualified candidates listed in a ranked order. The platform performs big data analysis over up to millions of data files on candidates in the system, to provide for candidate screening based on the CV as well as other information inputted and analyzed by the computerized engine of the platform. As a result, many candidates who would appear to be suitable based only on CV are eliminated from the candidate list early on, before resources are wasted on these unsuitable candidates.

[0007] The processes performed by the computerized platform are performed by computer analysis of data files stored in the system of the platform, which form breathing profiles for each of the candidates in the system, of which there may be millions, to select suitable candidates for a requested job position. The candidate selection process for a requested job position typically involves a plurality of computerized filtrations, with each filtration involving the filtering of multitudes of candidate data files, being performed on the order of seconds, and for example, each filtration taking less than one minute.

[0008] This document references terms that are used consistently or interchangeably herein. These terms, including variations thereof, are as follows.

[0009] A “computer” includes machines, computers and computing or computer systems (for example, physically separate locations or devices), servers, computer and computerized devices, processors, processing systems, computing cores (for example, shared devices), and similar systems, workstations, modules and combinations of the aforementioned. The aforementioned “computer” may be in various types, such as a personal computer (e.g., laptop, desktop, tablet computer), or any type of computing device, including mobile devices that can be readily transported from one location to another location (e.g., a smartphone, personal digital assistant (PDA), mobile telephone or cellular telephone, a watch digitally linked to a network such as the Internet, or other wearable technology.

[00010] A server is typically a remote computer or remote computer system, or computer program therein, in accordance with the “computer” defined above, that is accessible over a communications medium, such as a communications network or other computer network, including the Internet. A “server” provides services to, or performs functions for, other computer programs (and their users), in the same or other computers. A server may also include a virtual machine or a software based emulation of a computer.

[00011] An "application" or “software application”, includes executable software, and optionally, any graphical user interfaces (GUI), through which certain functionalities can be implemented.

[00012] A "client" is an application that runs on a computer, workstation or the like and relies on a server to perform some of its operations or functionality.

[00013] The terms “n” and “n^Lh” are representative of the last member of a series or sequence of members, for example, servers, databases, computers, elements, with the series being definite or indefinite.

[00014] Big Data (Big Data analysis) includes analyzing and systematically extracting information from, or otherwise dealing with data sets that are too large or complex to be dealt with by traditional data-processing application software and/or software tools, for example, by specialized computers (e.g., special purpose computers), including processors, computer hardware and/or software, to capture, curate, manage, and process data within a tolerable elapsed time, such as a short time period, on the order of seconds and in real time.

[00015] Unless otherwise defined herein, all technical and/or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the disclosure pertains. Although methods and materials similar or equivalent to those described herein may be used in the practice or testing of embodiments of the disclosure, exemplary methods and/or materials are described below. To the extent of any conflict, the patent specification, including definitions, will control. In addition, the materials, methods and examples are illustrative only and are not intended to be limiting.

[00016] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to be used to limit the scope of the claimed subject matter.

BRIEF DESCRIPTION OF FIGURES

[00017] Non-limiting examples of embodiments are described below with reference to figures attached hereto that are listed following this paragraph. Identical structures, elements or parts that appear in more than one figure are generally labeled with a same numeral in all the figures in which they appear, and a numeral labeling an icon representing a given feature in a figure may be used to reference the given feature. Dimensions of components and features shown in the figures are chosen for convenience and clarity of presentation and are not necessarily shown to scale.

[00018] FIG. 1 is a diagram of an exemplary environment for the system in which embodiments of the disclosed subject matter are performed;

[00019] FIG. 2 is a diagram of the architecture of the home server of FIG. 1 and the system thereof; and,

[00020] FIGs. 3A and 3B, collectively referred to as FIG. 3, are a flow diagram of a process in accordance with embodiments of the disclosed subject matter.

DETAILED DESCRIPTION OF THE DRAWINGS

[00021] Before explaining at least one embodiment of the disclosure in detail, it is to be understood that the disclosure is not necessarily limited in its application to the details of construction and the arrangement of the components and/or methods set forth in the following description and/or illustrated in the drawings. The disclosed subject matter is capable of other embodiments or of being practiced or carried out in various ways.

[00022] As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or computer program product. Accordingly, aspects of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit," "module" or "system." Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more non-transitory computer readable (storage) medium(s) having computer readable program code embodied thereon.

[00023] Throughout this document, numerous textual and graphical references are made to trademarks, and domain names. These trademarks and domain names are the property of their respective owners, and are referenced only for explanation purposes herein.

[00024] The present disclosure utilizes big data techniques and analysis to select the most suitable candidates for a job or position. Initially, with the present disclosure, the pool of candidates may be in the thousands to tens of thousands, and even the millions. The disclosed platform includes search engines, which can analyze a job position, and potentially screen (e.g., filter or auto-filter) the entire pool of candidates, for example, in the tens of thousands to hundreds of thousands (and even millions), and provide a number of suitable candidates in the tens or hundreds on the order of seconds, typically less than one minute. For example, a computerized search engine of the disclosed system makes two or more filtrations (e.g., auto-filtering) - a primary or first filtration, where candidates on the order of tens to low hundreds are selected from the pool of tens of thousands or hundreds of thousands up to millions, followed by at least one secondary or second (or subsequent) filtration, where the search engine automatically analyzes data obtained from the candidates (e.g., the ten to low hundred) obtained from the primary or first filtration, and selects the suitable candidates, providing them (e.g., the ten to low hundred selected candidates from the primary filtration) to the job requestor in an ordered list, where the candidates which remain are ranked based, for example, on a suitability score. Both of the aforementioned primary and secondary filtrations are performed, for example, in real time on the order of seconds (to achieve instantaneous results) by a computer using computerized big data analysis and techniques. From this list, the job requestor can invite or otherwise communicate with, the most suitable candidates for further analysis, such as for a personal interview, to find the best fit candidate for the job. This process of the present disclosure allows for the best chances of finding the most suitable candidates, from an extremely large pool of candidates. Since only the best candidates make it through the filtrations for the interviews or final evaluations, time, money and resources are not wasted on candidates who are unsuitable from the outset.

[00025] Reference is now made to FIG. 1, which shows an exemplary operating environment, including a network(s) 100, to which is linked a home server (HS) 102, also known as a main or central server. The home server 102 also includes a system 102', which, for example, operates a platform, known as an Applicant Tracking System (ATS). The terms “system”, as denoted by element number 102’, and “platform” are used interchangeably herein.

[00026] The system 102’ , for example, may also include other computers, including servers, components, and applications, e.g., client applications, associated with home server 102, as detailed below. The system 102’ manages and controls communications between it and recruiters 106 (RE1 to REn 106a-106n), Direct Employers 107 (DEI to DEn 107a to 107n), candidates 108 (CA1 to CAn 108a-108n), both known to the system 102’ and who make themselves known to the system 102’, for example, via social media 110 and the like, the social media, such as Linkedln®, Facebook®, and the like, or directly contacting the system 102’ or an entity 112. The system 102’ also gathers information and data on the candidates by searching social media 110 which has information on the candidate, or other servers and the like (not shown but similar to the server 110 representing social media), linked to the network 100, from sources (e.g., external sources) from which information and data such as on-line information, including, for example, media articles, data, government publications and government reports, publications, and the like, on the candidate can be gathered and obtained (for use in the candidate breathing profile, as detailed further below).

[00027] Also, the entity 112, who receives candidate information (and typically enters this information into the system 102’) may be directly connected to the home server 102 or connected via the network 100. The entity 112 may communicate with the various candidates 108 CA1 to CAn, recruiters 106 RE1 to REn, and Direct Employers 107 DEI to DEn, via instant messaging systems and/or emails and/or, the social media 110 and/or any other communication system.

[00028] The network(s) 100 is, for example, a communications network, such as a Local Area Network (LAN), or a Wide Area Network (WAN), including public networks such as the Internet. As shown in FIG. 1, the network 100, may be a single network, such as the Internet, but is typically a combination of networks and/or multiple networks including, for example, cellular or Bluetooth or other networks. "Linked" as used herein includes both wired or wireless links, either direct or indirect, and placing the computers, including, servers, components and the like, in electronic and/or data communications with each other.

[00029] FIG. 2 shows an architecture for the system 102’ of the disclosure, in, for example, the home server 102. While the system 102’ is shown on the home server, the system 102’ may be spread across numerous servers, computerized components and the like, including servers in the cloud (e.g., cloud servers, not shown).

[00030] The architecture for the system 102’ includes one or more components, engines, modules and the like, for providing numerous additional server functions and operations, and, for running the processes of the system 102’ . Those components, engines and modules of the system 102’ are shown and described below, but additional components, engines and modules are also permissible as part of the system 102’, to perform any additional functions. For example, a “module” includes one or components for storing instructions, (e.g., machine readable instructions) for performing one or more processes, and including or associated with processors, for example, the CPU 202, for executing the instructions. The home server (HS) 102 may be associated with additional storage, memory, caches and databases, both internal and external thereto. For explanation purposes, the home server (HS) 102 may have a uniform resource locator (URL) of, for example, www.example.hs.com.

[00031] The architecture of the system 102' (platform), as shown, for example, in the home server 102, includes a central processing unit (CPU) 202 formed of one or more processors, electronically connected, i.e., either directly or indirectly, including in electronic and/or data communication with storage/memory 204, a communications module 206, a Job Orders module 208, Filter Questions module 210, a CV (resume) Obtaining module 212, Digital Questionnaires (for candidates) module 214, Breathing Profiles module 216, a Candidate and Jobs Database 218, Search Engine 220, and the List Generator 222. The processors are, for example, conventional processors. The aforementioned components, modules, and engines are linked to each other, either directly or indirectly, with some linkages noted below, so as to be in direct or indirect communications with each other.

[00032] The Central Processing Unit (CPU) 202 is formed of one or more processors, including microprocessors, for performing the home server 102 and system 102’ (platform) functions and operations detailed herein, including controlling the communications module 206, the Job Orders module 208, Filter Questions module 210, the CV (resume) Obtaining module 212, Digital Questionnaires (for candidates) module 214, Breathing Profiles module 216, the Candidate and Jobs Database 218, Search Engine 220, and the List Generator 222. The processors are, for example, conventional processors, such as those used in servers, computers, and other computerized devices, including hardware processors. For example, the processors may include x86 Processors from AMD (Advanced Micro Devices®) and Intel®, Xenon® and Pentium® processors from Intel, as well as any combinations thereof. [00033] The storage/memory 204 is any conventional storage media. The storage/memory 204 stores machine executable instructions for execution by the CPU 202, to perform the processes of the disclosure. The storage/memory 204 also includes machine executable instructions associated with the operation of the components, including the communications module 206, a Job Orders module 208, Filter Questions module 210, a CV (resume) Obtaining module 212, Digital Questionnaires (for candidates) module 214, Breathing Profiles module 216, the Candidate and Jobs Database 218, the Search Engine 220, and the List Generator 222, detailed herein. The storage/memory 204 also, for example, stores rules and policies for the system 102' and the home server 102.

[00034] The processors of the CPU 202 and the storage/memory 204, although shown as a single component for representative purposes, may be multiple components. These multiple components may be outside of the home server 102 and/or the system 102', and linked to the network 100.

[00035] The communications module 206 is designed to handle communications over the network 100, such as the Internet, cellular networks and the like.

[00036] The Job Orders module 208 receives, processes and stores all of the job orders, such as those transmitted from the recruiters RE1 to REn 106a- 106n, and/or the Direct Employers DEI to DEn 107a- 107n. With each job order, the recruiter or direct employer provides the position being searched for, as well as filter questions for the positions, so that the search engine 220 can determine criteria for the candidate search to fill that position.

[00037] The filter questions for each job or position, for example, either provided by the job requestor 106, 107, or for other jobs programmed into the system 102’, are stored and modified, and, created, for example, by rules based logic, and/or input by the system administrator (or other similar entity), in and by the Filter questions module 210. The answers to the filter questions, from the recruiter or direct employer are stored in the Database 218 as “Jobs”. For example, filter questions may be selected by the module 210, based on recognition of the requested job, preprogrammed into the module 210 for certain jobs, selected by the system administrator, and/or combinations thereof. Example filter questions include: Candidate Experience Level, Skills Necessary for the position, Licenses needed for the position, e.g., medical license, law license, Academic Degrees needed for the position, Certificates needed for the position, languages needed for the position, any specific questions the employer wants answered by the candidate, the location of the position, the salary/salary range for the position, availability of when the candidate can start work, and any special hours for the position, for example, 40 hour week, 9:00 am to 5:00 pm Monday, Tuesday, Thursday and Friday, with Wednesday being 12:00 pm to 8:00 pm, any domestic/overseas travel requirements, and the like. The filter questions, based on the answers to the filter questions, and analysis of the answers to the filter questions creates criteria for the job, the criteria including parameters, for example, derived from the criteria for the job (position) . The criteria and/or parameters are used in analyzing, for example, by a big data analysis, the breathing profiles, e.g., stored in the system, when an analysis is performed of the criteria and/or parameters (e.g., multitudes of criteria and/or parameters) against the information of the breathing profiles and also, for example, associated therewith, such as CVs (although candidate CVs are typically integrated into the candidate’ s breathing profile) to determine which breathing profiles satisfy or otherwise correlate with the criteria and/or parameters for the job, so that suitable candidates for the job are found, via their breathing profiles.

[00038] The module 210 also, for example, communicates with the Digital Questionnaires module 214, as some of the filter questions may be used by the Digital Questionnaires module 214, for presentation to candidates in digital questionnaires (the candidates for receiving the digital questionnaires having been selected in the primary or first filtration, based on their breathing profile).

[00039] The CV obtaining module 212 obtains the CV (resume) for each candidate, typically via an upload or grab. The obtained CV is then sent to the data base 218, where it is entered into a database entry (record) for each individual candidate, and this module 212 sends the CV to the breathing profile module 216, such that the CV for the candidate is incorporated into the breathing profile for the candidate, and checks that the CV for the candidate has been incorporated into in the breathing profile (module 216), and broken into a format suitable for analysis by the search engine 220.

[00040] The Digital Questionnaires for Candidates module 214 creates, e.g., automatically, and/or receives, stores and administers various questionnaires for each of the candidates to answer, typically over their smart phone computer or the like. This module 214, for example, creates lists of one or more questions, either based on automated (programmed, for example, rules based) recognition of the job position requested and/or selected from previously generated filter questions or newly generated questions by the module 214, and/or questions input by the job requestor, with the list of one or more questions incorporated into digital (electronic) questionnaires (surveys/survey forms) sent electronically to selected candidates for a requested job (position) (e.g., as a result of being selected in a primary or first filtration based on analysis of candidate breathing profiles). [00041] The digital questionnaires, created by the Digital Questionnaires Module 214, are, for example, typically distributed to candidates selected by the aforementioned first or primary filtration, by being sent electronically over the internet, cellular network or other network, to a computer or computerized device (e.g., smart phone) associated with a potential candidate (subject), selected by the primary or first filtration, for the requested job or position. The answers received, typically electronically, from the subject (e.g., sent from his computer or smart phone to the system 102’) are, for example, analyzed, to be used in performing the second or subsequent, e.g., secondary, filtration (e.g., after the first or primary filtration is complete). The answers are received and stored in the database 218 for each candidate, for analysis by the search engine 220, as well as for updating the breathing profile of each individual candidate (subject) in the system 102’.

[00042] The breathing profile module 216 creates, populates, updates and stores the breathing profiles for each candidate, in a searchable format (e.g., computer searchable format), for search and analysis by the search engine 220 (for example, the search engine 220 using criteria and/or parameters for the job position either developed by the system and/or derived from the filter questions), or other processor(s), computer, or the like. Each breathing profile is typically searched for candidates, upon the creation of new job (position) orders. A breathing profile is, for example, the actual answers received from each candidate, such as in a current or previous telephone or internet interview or discussion, or electronically from digital questionnaires, and may also include information from candidate CVs, social media, publications, and the like. Each breathing profile is continuously updated every time the candidate associated with the breathing profile provides answers to the system 102’, e.g., by answering a digital questionnaire, or the system obtains and/or receives data about the candidate, from the candidate or other sources. For example, digital questionnaires are sent to a candidate as part of a job position search, but may also be sent periodically by the system 102’, to update the breathing profile. This periodic sending may be, for example, to a candidate who has not corresponded with the system 102’ for a predetermined period of time (e.g., six months). This is typically done to determine whether the subject is still interested in receiving potential job positions. The collected information, in addition to the information detailed above, for the breathing profile, may also include data from the candidate’s CV, as well as information gathered, for example, by the module 216, on the candidate from, external sources (e.g., sources external to the system 102’) including, but not limited to social media profiles, such as Facebook®, and Linkedln® profiles, on-line information, for example, media articles, government publications, government records, and government reports, publications, and the like.

[00043] The collected data may also be based on information which the system 102’ is programmed to check for, but was not a specific answer to a question in a digital questionnaire. For example, Joe, a graphic designer with eight years of experience in graphic design, sent back an answered digital questionnaire in 2018 to the system 102’, in response to a graphic designer position in Philadelphia, for which the system 102’ was conducting a candidate search (for which Joe was selected based on Joe’s breathing profile). In 2021, in response to receiving another digital questionnaire from the system 102’ for another graphic designer position in Philadelphia (for which Joe was selected based on Joe’s breathing profile), Joe answered that he remains interested in hearing about graphic designer positions, but now in the Midwest, preferably Missouri or Illinois. Based on these answers, the system 102’, for example, infers that Joe remains a graphic designer and generally designating two Midwestern states may indicate willingness to work remotely from the Midwest. Joe’s breathing profile is updated to indicate that he is a graphic designer, now with eleven years of experience, he would be interested in graphic designer positions in the Midwest, he may be willing to work remotely, but he does not want to be physically located in Philadelphia.

[00044] The breathing profile for each candidate is in a format suitable for search and analysis by the search engine 220. As the breathing profile for each candidate is continuously updated, the search engine 220 is able to search for the most relevant candidates at any given time, based on the most up to date information on the candidate. The number of candidates searched may, for example, be in the millions, as millions of breathing profiles, each breathing profile representing a candidate, may be stored in the module 216.

[00045] The Candidate and Jobs database 218 is a database with records (database entries) for each individual candidate 1 to n, and each individual job 1 to n. For example, for each candidate 108 CA1 to candidate CAn, a database record for the individual candidate includes, for example, the candidate’s CV (including, for example, candidate contact information, such as postal addresses, telephone numbers, email addresses, social media handles, and the like) and answers to the digital questionnaire, should the candidate have answered one. For each job, each database record includes, for example, the filter question answers. [00046] The search engine 220 operates, for example, in two stages. A first stage or primary (first) filtration involves a big data analysis of the breathing profiles, and possible additional documents, criteria and the like, based on the job request (for example, from the recruiter 106 or the direct employers 107). This big data analysis allows for upwards of millions of candidates to be analyzed with perhaps a hundred or so selected, on the order of seconds. A secondary, second or subsequent stage, for a secondary or second filtration of the candidates, activates, or otherwise triggers after the electronic responses to questions, such as those from digital questionnaires, are received from candidates selected in the first stage or first filtration. The second stage is such that the returned answers to the questions are automatically analyzed by computer processes, and therefore, a second filtration is performed to determine the suitable candidates, for example, going from an order of potentially millions to orders of hundreds or tens, typically instantaneously and in real time, and on the order of seconds.

[00047] The Search Engine 220, for example, operates on “big data” (e.g., performs big data analyses) as it searches among millions of Breathing Profiles (Breathing profile records, data files) quickly, for example, on the order of seconds, to filter the job candidates, typically to the order of tens to hundreds. As the search engine 220 is able to formulate searches based on hundreds of parameters, to perform a big data analysis, it can rapidly (on the order of seconds) find the best and most suitable candidates for the specific job, based on its having analyzed each candidate’s active breathing profile, as well as other factors, such as the candidates stored CV (which may also be part of the breathing profile). Parameters involved in the big data analysis, include, for example, updated location, salary expectations, experience, skills, qualifications, degrees, diplomas, relevant licenses, languages, answers to dynamic questions, and the like. There are typically multitudes of parameters, for example, on the order of tens to hundreds. This big data analysis of the parameters (and/or criteria) against the information (data) of the breathing profiles (e.g., stored or otherwise associated with the system 102’) is, for example, a primary or first filtration to determine suitable candidates for the job or other position. Once suitable candidates are found, for example, from the aforementioned big data or other computerized analysis, the selected candidates, from this primary or first filtration, are designated to be sent a digital questionnaire by the system 102’ (for example, in a secondary or second filtration), in order that a list of suitable candidates be provided by the system 102’ to the job requestor 106 or direct employer 107. [00048] The search engine 220, for example, communicates with the Digital Questionnaires module 214. The Digital Questionnaires module 214 creates or has created a digital questionnaire for the requested job, and sends the digital questionnaire (an electronic document) to suitable candidates from the big data analysis (first filtration), to be answered electronically be each suitable candidate. The suitable candidate, if interested in the position, or even if not interested in the position, answers one or more questions of the digital questionnaire, and electronically sends the answers and/or answered digital questionnaire to the system 102’.

[00049] The search engine 220 analyzes, for example, automatically, the dynamic questions and candidates answers thereto, from the digital questionnaire, to find the most suitable candidates for the specific job, as part of the aforementioned secondary or second filtration. This secondary filtration is, for example, a big data process involving data correlations between a data or criteria established by the search engine 220 for the job (position), with (e.g., against) the questionnaire answers and/or information obtained from the answers. The correlation(s), for example, include matches (e.g., equivalence or exact matches) and/or approximate matches (e.g., approximately equal to or congruence) of the data. This secondary or second filtration (filtering process or auto filtering process) may be, for example, a big data analysis including a mles-based analysis, matching analysis (e.g., of data, information, parameters, criteria, or combinations thereof), weighted factor analysis, or combinations thereof, or other computerized analysis, for example, also performed by the search engine 220.

[00050] In analyzing the answered digital questionnaires, the search engine 220 may or may not also look at the breathing profile of the candidate, to determine whether the candidate remains a suitable candidate, to be placed on a candidate list (for presentation to the job requestor 106 or direct employer 107).

[00051] The search engine 220 filters the suitable candidates, based on the analyzed answers, in this secondary or second filtration. This answer analysis portion of the search engine 220 activates, or otherwise triggers (e.g., begins or initiates), after the primary or first filtration of the candidates from the Big Data analysis of the breathing profiles (a first filtration of suitable candidates) is complete, and a first group or pool of candidates has been selected. This second filtration, for example, is also on the order of seconds, and results in a second group or pool of candidates, for example, less than the number of candidates in the first group or pool. The answers, as well as other information received with the returned digital questionnaire, including inferences made about the candidate by the system 102’, is used to update the breathing profile for the respective candidate.

[00052] Additionally, the search engine 220 operates continuously. Accordingly, the search engine can search for candidates for multiple jobs contemporaneously, including simultaneously, including performing numerous first (primary) filtrations, from the breathing profiles, and/or numerous second or subsequent (secondary) filtrations, automatic analysis of the answers to the digital questionnaires simultaneously. Also, within a time period, or time interval, the search engine 220 may find the same candidate suitable for more than one job. When this is the case, the communications module 206 sends a digital questionnaire for each of the one or more jobs found by the search engine for the candidate, for example, found within that time period (time interval).

[00053] Additionally, the search engine 220 may for example, operate on a rolling basis, where for a job, the first (primary) filtration is performed contemporaneous, including simultaneous, with the second or subsequent (secondary) filtration. For example, should the running first filtration find a suitable candidate, the Search engine 220 will begin the second filtration, automatically sending a digital questionnaire to that candidate, while at the same time, the search engine 220 continues to perform the first (primary) filtration to search for suitable candidates for the job.

[00054] Should the search engine 220 determine that there are suitable candidates for the job, these candidates are sent to a candidate list generator 222. The candidate list generator 222 creates a list of candidates for the position (e.g., job). This list, for example, is then sent to the recruiter 106, direct employer 107, and/or other entity associated with the job, and/or sent to one or more candidates on the list, for example, via the communications module 206, electronically (over the network(s) 100). Alternately, in rare cases, the search engine 220 may not find any suitable candidates. For example, this failure to find any suitable candidates is reported to the job requestor, such as the recruiter 106 or the direct employer 107.

[00055] Additionally, the search engine 220 is also programmed to provide a score and/or rank, for a group of one or more candidates, for example, after the second filtration is complete. The scoring may be based on one or more factors, for example, as programmed into the search engine 220, and for example, the factors which may be weighted. The factors include, for example, the candidate’s experience, geographic location, salary expectation (the lower the salary expectation, the higher the score), education (the greater number of relevant degrees, the higher the score), availability (the sooner the availability, the higher the score), job skills, licenses and other industry standard qualifications, and, spoken and written languages. The search engine 220, for example, communicates with the candidate list generator 222.

[00056] The candidate list generator 222 creates a list of candidates for the position (i.e., job). The candidate list generator 222 may use the score and/or rank (from the search engine 220) for each selected candidate, to create the list with the candidates in a ranked order. This list can then be sent to the recruiter 106 or the direct employer 107, and/or also sent to each candidate on the list, for example, via the communications module 206.

[00057] Attention is now directed to FIGs. 3A and 3B, collectively FIG. 3, which shows a flow diagram detailing computer-implemented processes in accordance with embodiments of the disclosed subject matter. Reference is also made to elements shown in FIGs. 1 and 2. The process and sub-processes of FIG. 3 are computerized processes performed by the system 102'. The aforementioned processes and sub-processes may be, for example, performed automatically, and, for example, in real time.

[00058] The process begins at the START block 302. Prior to or contemporaneous with the START, the breathing profiles for each of the candidates in the system 102’ are as up to date as possible, based on the candidate associated with the stored breathing profile having answered digital questionnaires, providing information to the system, such as his CV, articles and publications, license renewals, as well as the system 102’ (e.g., module 216) having gathered information on the candidate from, for example, sources, such as social media profiles, such as Facebook®, and Linkedln® profiles, on-line information, such as media articles, data, government publications, government reports and government records, publications, and the like.

[00059] The process moves to block 304 where the system 102’ receives a job (position) request, from a recruiter 106, direct employer 107 or other entity, now known as a job requestor or requestor.

[00060] The system 102’ either manually or automatically, establishes criteria (requirements) for the job, at block 306. For example, the job may be for a Junior Accountant. Criteria may include a B.S. degree in Accounting, a CPA license, and the ability to Travel 10% of the time on short notice. These criteria are used, for example, to derive parameters. The derived parameters, for example, may also include the criteria itself or portions of the criteria. The search engine 220 uses some or all of the derived parameters to search breathing profiles for suitable candidates for the job, as detailed below. [00061] Next, at block 308, the system 102’ either automatically and/or manually (e.g., by a system administrator or the like with access to the system 102’) creates filter questions for the job criteria (or job), which are addressed to (and to be answered by) the job requestor (106, 107) to establish additional criteria for the job, from which parameters for the search engine 220, for example, to search for candidates by their breathing profiles, are derived. For example, filter questions may include, What Candidate Experience Level is needed? What skills are necessary for the position?, Are any licenses preferred or required for the position, e.g., medical license, law license?, What academic degrees are needed for the position?, Any certificates of courses taken/qualifications/other requirements needed for the position?, Are any languages needed for the position?, Are there any specific questions the employer wants answered by the candidate?, Where is the location of the position?, Can the position be remote?, What is the salary/salary range for the position?, What is the availability of the candidate? When the candidate can start work?, Are there any special hours for the position?, for example, 40 hour week, 9:00 am to 5:00 pm Monday, Tuesday, Thursday and Friday, with Wednesday being 12:00 pm to 8:00 pm, Is there any and how much domestic/overseas travel required?, Has the candidate received any honors, awards, peer recognition, bonuses for their work?, and the like. For example, the answers to the filter questions and/or inferences and information obtained from the answers to the filter questions, become criteria and/or parameters, which may, for example, be weighted (for example, based on system rules and policies), and used to analyze breathing profiles of candidates, to select suitable candidates for the job position from the multitudes of candidate breathing profiles stored in the system 102’.

[00062] The process moves to block 310, where the search engine 220 performs a big data analysis, for example, a primary or first filtration, by analyzing the potentially millions of breathing profiles stored in the breathing profiles module 216, against the job criteria and/or parameters which may be derived therefrom, to determine a list of suitable candidates for the job. For example, the primary or first filtration includes the search engine 220 determines correlations between the parameters (e.g., typically hundreds or thousands) derived from the job (position) criteria and/or answers to the filter questions and information obtained from these answers, against at least a portion of the information (e.g., typically hundreds of data items) of each breathing profile (e.g., typically thousands to hundreds of thousands) analyzed. The data/information of each breathing profile includes, but is not limited to, for example, questionnaire answers and system inferences based on the questionnaire answers, CV information, social media information about the candidate, on-line information, for example, media articles, government publications and government reports and records, data, publications, and the like, obtained by the breathing profiles module 216 about the candidate. For example, a correlation(s) may be a match (equivalence or exact match) and/or an approximate match (approximately equal to or congruence) or best fit, or combinations thereof, between one or more parameters derived from the job criteria, and at least a portion the information in each analyzed breathing profile.

[00063] At block 312, should suitable candidates not be found, the process returns to block 310, from where it resumes. Alternately, at block 312, should suitable candidates be found, the process moves to block 314, where a list of candidates (or candidate pool or first pool) is generated, or added to. For example, as a result of this primary (first) filtration based on analysis of breathing profiles, from potentially millions of breathing profiles, a first pool or group of suitable candidates on the order of tens to hundreds are found within seconds. However, at block 312, for example, after a predetermined number of cycles between blocks 312 and 310, should suitable candidates not be found, the process times out and ends.

[00064] From block 314, the process moves to block 316, where the system 102’ creates information requests, such as question lists for each candidate in the first pool of candidates (resulting from the primary or first filtration), and automatically sends a question list, e.g., a digital questionnaire with questions relevant to the job, as an electronic document, via the communication module 206, to each of the candidates selected in the first pool or group (resulting from the primary (first) filtration). The questions on the digital questionnaire, for example, may relate to job criteria (and/or parameters which may be derived from the criteria), and/or job requirements, and may include the filter questions. For example, for the aforementioned junior accountant position, the digital questionnaire (to be sent to the candidates selected in the primary (first) filtration), may include one or more of questions including: Where did you study for your B.S. Degree?, In which states do you hold a CPA license?, Have you ever taken courses in International Tax Accounting?, Do you have a Passport?, Can you Travel internationally on short notice?, Have you ever worked with Retail Stores?, as the job may be with a large department store chain such as Macy’s®, What are your salary expectations?, Can you work on weekends if needed?, Will you work at least two days in the office?, Can you work remote, Are you willing to relocate to New York after one year?, Have you received any honors, awards, peer recognition, bonuses for your work?, and the like [00065] The system 102’ receives replies of answered questions from candidates of the first pool or group, at block 318. Candidates, from whom replies are not received, may be prompted to reply, the questions again, or removed from the candidate list, e.g., first pool or group. The time to reply to the digital questionnaire, for example, may be for a predetermined time period, or may remain open until the system 102’ receives confirmation (e.g., from the job requestor 106 or the direct employer 107) that the job position has been filled and/or no more candidates are being considered by the job requestor 106 or the direct employer 107.

[00066] At block 320, the system 102’, for example, via the search engine 220 analyzes (e.g., automatically), for example, by computer processes including big data analysis, the answers to the questions from each responding candidate (selected in the first pool of candidates by the first or primary filtration), to determine whether the candidate is still suitable for the job. From the received answers, the system 102’, e.g., the breathing profile module 216 updates the breathing profile of each candidate with each candidate’s answers. With the answers to the digital questionnaires received and analyzed by the search engine 220, the process moves to block 322.

[00067] At block 322, a secondary or second filtration is performed to further select candidates (from the first pool from the primary filtration), based on the results of the big data analysis of the answers in the received digital questionnaires. The candidates are filtered, in this second filtration, into a second pool or group, typically on the order of tens to hundreds, for example, on the order of seconds. The secondary filtration may be a result of the best candidates from the big data analysis (when the big data analysis of block 320 is also such that candidates, such as a certain number of candidates, are selected), for example, by data correlations between a data or criteria established by the search engine 220 for the job (position) with the questionnaire answers and/or information obtained from the answers - the correlation(s), for example, including a match and/or an approximate match of the data. For example, the secondary filtration process and candidate selection process (second candidate pool) of block 320, as well as subsequent filtrations and processes performed on the now- obtained second candidate pool, may be, for example, another or subsequent big data analysis, including a mles-based analysis, matching analysis (e.g., of data, information, parameters, criteria, or combinations thereof), weighted factor analysis, or combinations thereof, or other computerized analysis, for example, performed by the search engine 220.

[00068] From block 322, the process moves to block 324, where in an optional process, a further filtration, computerized or manual, may be performed for the suitable candidates selected. The suitable remaining candidates, either directly from the secondary or second filtration, or after the aforementioned further filtration, are scored and/or ranked. This ranking takes, for example, seconds to perform by the candidate list generator 222. For example, a list of the suitable candidates, ordered by score and/or rank, is sent, for example, electronically transmitted, typically over the network 100, to the job requestor 106, 107, for example, via the communications module 206. This list may, for example, also include candidate contact information, such as postal address, telephone numbers, email addresses, social media handles, and the like). Also, this information is used to update the breathing profile (module 216) for each of the candidates, e.g., the candidates of the second pool or group are updated, at block 326. The job requestor has now been provided with an ordered list of suitable candidates who can be contacted for interviews, further examination, and the like, by the job requestor.

[00069] The process ends at block 328. The process may be repeated for as long as desired, for example, for each job request, the system 102’ receives.

[00070] Embodiments of the disclosed subject matter include, for example, a computer- implemented method for candidate selection. The method comprises: maintaining a plurality of breathing profiles, for example, in storage media, for example, in one or more databases, each breathing profile associated with at least one candidate, and including information for each at least one candidate, from both the at least one candidate and/or external sources, in a searchable format; searching one or more of the plurality of breathing profiles, including analyzing parameters for a position (e.g., a job) with the information in one or more of the said plurality of breathing profiles; selecting breathing profiles associated with candidates whose breathing profiles include information which correlates with the parameters for the position, the candidates associated with the selected breathing profiles forming a first candidate pool; analyzing, for example, automatically, received answers to questions from candidates of the first candidate pool to determine a second candidate pool, the number of candidates in the second candidate pool being less than the number of candidates in the first candidate pool; and, electronically transmitting contact information of the candidates of the second candidate pool to the entity that requested the position.

[00071] Optionally, the computer-implemented method is such that the breathing profiles are continuously updated, including adding the received answers from each candidate as the information into the breathing profile for the candidate.

[00072] Optionally, the computer-implemented method is such that it additionally comprises: receiving answers to questions from the entity requesting the position, the answers from which parameters for the position are derived. [00073] Optionally, the computer-implemented method is such that the correlation includes a match and/or an approximate match of the parameters with at least a portion of the information of each said breathing profile.

[00074] Optionally, the computer-implemented method is such that the analyzing parameters for a position with the information in one or more of the said plurality of breathing profiles is performed as a big data analysis.

[00075] Embodiments of the disclosed subject matter are directed to a computer- implemented method for candidate selection. The method comprises: maintaining a plurality of breathing profiles, each breathing profile associated with at least one candidate, and comprising information for each at least one candidate, the information obtained from the candidate and/or from external sources, the information in each of the breathing profiles in a computer searchable format; searching one or more of the breathing profiles of the plurality of breathing profiles, the searching comprising analyzing parameters for a position (e.g., a job and/or employment position) for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles; selecting breathing profiles associated with candidates whose breathing profiles include information which correlates with the parameters for the position, the candidates associated with the selected breathing profiles forming a first candidate pool; analyzing received answers to questions from candidates of the first candidate pool to determine a second candidate pool, the number of candidates in the second candidate pool being not more than equal to the number of candidates in the first candidate pool; and, electronically transmitting a list of the candidates of the second candidate pool to the entity that requested candidates for the position.

[00076] Optionally, the computer- implemented additionally comprises: continuously updating the breathing profiles for the candidates including: adding information based on the received answers to questions from individual candidates to the information into the breathing profile for the candidate.

[00077] Optionally, the computer-implemented method is such that the information based on the received answers includes: the answers to the questions and/or information derived from the answers to the questions.

[00078] Optionally, the computer-implemented method is such that the number of candidates in the second candidate pool is less than the number of candidates in the first candidate pool [00079] Optionally, the computer-implemented method additionally comprises: receiving answers to filter questions from the entity that requested candidates for the position, the answers to the filter questions from which the parameters for the position are derived.

[00080] Optionally, the computer-implemented method is such that the parameters for the position are created by a computer including a processor programmed to analyze the position received from the entity that requested candidates for the position.

[00081] Optionally, the computer-implemented method is such that the correlation includes a match and/or an approximate match of the parameters with at least a portion of the information in the breathing profile being analyzed.

[00082] Optionally, the computer-implemented method is such that the analyzing the parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles and/or the selecting the breathing profiles, to form the first candidate pool, is performed as a big data analysis.

[00083] Optionally, the computer-implemented method is such that the information obtained from the candidate for the breathing profile associated with the candidate includes one or more of: resumes, Curriculum Vitale (CV), answers to questions, and/or answers to questionnaires.

[00084] Optionally, the computer-implemented method is such that the external sources for information obtained about the candidate include one or more of: social media profiles, on line information, on-line media articles and on-line publications.

[00085] Optionally, the computer- implemented method additionally comprises: automatically sending the candidates of the first candidate pool one or more questions to which the received answers are analyzed.

[00086] Optionally, the computer-implemented method is such that the analyzing the received answers to questions from candidates of the first candidate pool to determine a second candidate pool includes performing a big data analysis comprising correlating data between data established by a search engine for the position with the answers and/or information obtained from the received answers from the candidates of the first candidate pool.

[00087] Optionally, the computer-implemented method is such that the correlation includes a match and/or an approximate match of the data.

[00088] Embodiments of the disclosed subject matter are directed to a computer system for selecting candidates for a position. The computer system comprises: a non-transitory storage medium for storing computer components; and, a computerized processor for executing the computer components. The computer components comprise: a first module for maintaining a plurality of breathing profiles, each breathing profile associated with at least one candidate, and comprising information for each at least one candidate, the information obtained from the candidate and/or from external sources, the information in each of the breathing profiles in a computer searchable format; a second module for: 1) searching one or more of the breathing profiles of the plurality of breathing profiles, the searching comprising analyzing parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles; and, 2) selecting breathing profiles associated with candidates whose breathing profiles include information which correlates with the parameters for the position, the candidates associated with the selected breathing profiles forming a first candidate pool; and, a third module for analyzing received answers to questions from candidates of the first candidate pool to determine a second candidate pool, the number of candidates in the second candidate pool being not more than equal to the number of candidates in the first candidate pool.

[00089] Optionally, the computer system additionally comprises: a fourth module for electronically transmitting a list of the candidates of the second candidate pool to the entity that requested candidates for the position.

[00090] Optionally, the computer system is such that the first module is additionally configured for continuously updating the breathing profiles for the candidates including: adding information based on the received answers to questions from individual candidates to the information into the breathing profile for the candidate.

[00091] Optionally, the computer system is such that the information based on the received answers includes: the answers to the questions and/or information derived from the answers to the questions.

[00092] Optionally, the computer system of claim is such that the third module is such that the number of candidates in the second candidate pool is less than the number of candidates in the first candidate pool.

[00093] Optionally, the computer system additionally comprises a receiver module for receiving answers to filter questions from the entity that requested candidates for the position, the answers to the filter questions from which the parameters for the position are derived. [00094] Optionally, the computer additionally comprises a parameter creation module for creating the parameters for the position by analyzing the position received from the entity that requested candidates for the position.

[00095] Optionally, the computer system is such that the second module is such that the correlation includes a match and/or an approximate match of the parameters with at least a portion of the information in the breathing profile being analyzed.

[00096] Optionally, the computer system is such that the second module performs the analyzing the parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles and/or the selecting the breathing profiles, to form the first candidate pool, as a big data analysis.

[00097] Optionally, the computer system is such that the first module is additionally configured wherein the information obtained from the candidate for the breathing profile associated with the candidate includes one or more of: resumes, Curriculum Vitale (CV), answers to questions, and/or answers to questionnaires.

[00098] Optionally, the computer system is such that the first module is such that the external sources for information obtained about the candidate include one or more of: social media profiles, on-line information, on-line media articles and on-line publications.

[00099] Optionally, the computer system is such that the third module is additionally configured for automatically sending the candidates of the first candidate pool one or more questions to which the received answers are analyzed.

[000100] Optionally, the computer system is such that the third module is additionally configured for the analyzing the received answers to questions from candidates of the first candidate pool to determine a second candidate pool by performing a big data analysis comprising correlating data between data established by a search engine for the position with the answers and/or information obtained from the received answers from the candidates of the first candidate pool.

[000101] Optionally, the computer system is such that the correlation includes a match and/or an approximate match of the data.

[000102] Embodiments of the disclosed subject matter are directed to a computer usable non- transitory storage medium having a computer program embodied thereon for causing a suitably programmed system to select candidates for a position, by performing the following steps when such program is executed by the system. The steps comprise: maintaining a plurality of breathing profiles, each breathing profile associated with at least one candidate, and comprising information for each at least one candidate, the information obtained from the candidate and/or from external sources, the information in each of the breathing profiles in a computer searchable format; searching one or more of the breathing profiles of the plurality of breathing profiles, the searching comprising analyzing parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles; selecting breathing profiles associated with candidates whose breathing profiles include information which correlates with the parameters for the position, the candidates associated with the selected breathing profiles forming a first candidate pool; and, analyzing received answers to questions from candidates of the first candidate pool to determine a second candidate pool, the number of candidates in the second candidate pool being not more than equal to the number of candidates in the first candidate pool.

[000103] Optionally, the computer usable non-transitory storage medium is such that the steps additionally comprise: causing the electronic transmission of a list of the candidates of the second candidate pool to the entity that requested candidates for the position.

[000104] Optionally, the computer usable non-transitory storage medium is such that the number of candidates in the second candidate pool is less than the number of candidates in the first candidate pool.

[000105] Optionally, the computer usable non-transitory storage medium is such that the correlation includes a match and/or an approximate match of the parameters with at least a portion of the information in the breathing profile being analyzed.

[000106] The implementation of the method and/or system of embodiments of the disclosure can involve performing or completing selected tasks manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of embodiments of the method and/or system of the disclosure, several selected tasks could be implemented by hardware, by software or by firmware or by a combination thereof using an operating system or a cloud-based platform (such as those provided by Amazon Web Services™ or Microsoft® Azure™).

[000107] For example, hardware for performing selected tasks according to embodiments of the disclosure could be implemented as a chip or a circuit. As software, selected tasks according to embodiments of the disclosure could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system. In an exemplary embodiment of the disclosure, one or more tasks according to exemplary embodiments of method and/or system as described herein are performed by a data processor, such as a computing platform for executing a plurality of instructions. Optionally, the data processor includes a volatile memory for storing instructions and/or data and/or a non-volatile storage, for example, non-transitory storage media such as a magnetic hard-disk and/or removable media, for storing instructions and/or data. Optionally, a network connection is provided as well. A display and/or a user input device such as a keyboard or mouse are optionally provided as well.

[000108] For example, any combination of one or more non-transitory computer readable (storage) medium(s) may be utilized in accordance with the above-listed embodiments of the present disclosure. The non-transitory computer readable (storage) medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store, a program for use by or in connection with an instruction execution system, apparatus, or device.

[000109] A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[000110] As will be understood with reference to the paragraphs and the referenced drawings, provided above, various embodiments of computer-implemented methods are provided herein, some of which can be performed by various embodiments of apparatuses and systems described herein and some of which can be performed according to instructions stored in non-transitory computer-readable storage media described herein. Still, some embodiments of computer-implemented methods provided herein can be performed by other apparatuses or systems and can be performed according to instructions stored in computer-readable storage media other than that described herein, as will become apparent to those having skill in the art with reference to the embodiments described herein. Any reference to systems and computer-readable storage media with respect to the following computer-implemented methods is provided for explanatory purposes, and is not intended to limit any of such systems and any of such non-transitory computer-readable storage media with regard to embodiments of computer-implemented methods described above. Likewise, any reference to the following computer-implemented methods with respect to systems and computer-readable storage media is provided for explanatory purposes, and is not intended to limit any of such computer-implemented methods disclosed herein.

[000111] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware- based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. The descriptions of the various embodiments of the present disclosure have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

[000112] As used herein, the singular form "a", "an" and "the" include plural references unless the context clearly dictates otherwise.

[000113] The word “exemplary” is used herein to mean “serving as an example, instance or illustration”. Any embodiment described as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments and/or to exclude the incorporation of features from other embodiments.

[000114] It is appreciated that certain features of the disclosure, 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 disclosure, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination or as suitable in any other described embodiment of the disclosure. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements.

[000115] The above-described processes including portions thereof can be performed by software, hardware and combinations thereof. These processes and portions thereof can be performed by computers, computer-type devices, workstations, cloud-based platforms, processors, micro-processors, other electronic searching tools and memory and other non- transitory storage-type devices associated therewith. The processes and portions thereof can also be embodied in programmable non-transitory storage media, for example, compact discs (CDs) or other discs including magnetic, optical, etc., readable by a machine or the like, or other computer usable storage media, including magnetic, optical, or semiconductor storage, or other source of electronic signals.

[000116] The processes (methods) and systems, including components thereof, herein have been described with exemplary reference to specific hardware and software. The processes (methods) have been described as exemplary, whereby specific steps and their order can be omitted and/or changed by persons of ordinary skill in the art to reduce these embodiments to practice without undue experimentation. The processes (methods) and systems have been described in a manner sufficient to enable persons of ordinary skill in the art to readily adapt other hardware and software as may be needed to reduce any of the embodiments to practice without undue experimentation and using conventional techniques.

[000117] In the description and claims of the present application, each of the verbs, “comprise,” “include” and “have”, and conjugates thereof, are used to indicate that the object or objects of the verb are not necessarily a complete listing of components, elements or parts of the subject or subjects of the verb.

[000118] Descriptions of embodiments of the disclosure in the present application are provided by way of example and are not intended to limit the scope of the disclosure. The

Claims

described embodiments comprise different features, not all of which are required in all embodiments of the disclosure. Some embodiments utilize only some of the features or possible combinations of the features. Variations of embodiments of the disclosure that are described, and embodiments of the disclosure comprising different combinations of features noted in the described embodiments, will occur to persons of the art. The scope of the disclosure is limited only by the claims. CLAIMS

1. A computer-implemented method for candidate selection comprising: maintaining a plurality of breathing profiles, each breathing profile associated with at least one candidate, and comprising information for each at least one candidate, the information obtained from the candidate and/or from external sources, the information in each of the breathing profiles in a computer searchable format; searching one or more of the breathing profiles of the plurality of breathing profiles, the searching comprising analyzing parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles; selecting breathing profiles associated with candidates whose breathing profiles include information which correlates with the parameters for the position, the candidates associated with the selected breathing profiles forming a first candidate pool; analyzing received answers to questions from candidates of the first candidate pool to determine a second candidate pool, the number of candidates in the second candidate pool being not more than equal to the number of candidates in the first candidate pool; and, electronically transmitting a list of the candidates of the second candidate pool to the entity that requested candidates for the position.

2. The computer- implemented method of claim 1, additionally comprising: continuously updating the breathing profiles for the candidates including: adding information based on the received answers to questions from individual candidates to the information into the breathing profile for the candidate.

3. The computer- implemented method of claim 2, wherein the information based on the received answers includes: the answers to the questions and/or information derived from the answers to the questions.

4. The computer-implemented method of claim 1, wherein the number of candidates in the second candidate pool is less than the number of candidates in the first candidate pool

5. The computer-implemented method of claim 1, additionally comprising: receiving answers to filter questions from the entity that requested candidates for the position, the answers to the filter questions from which the parameters for the position are derived.

6. The computer- implemented method of claim 1, wherein the parameters for the position are created by a computer including a processor programmed to analyze the position received from the entity that requested candidates for the position.

7. The computer-implemented method of claim 1, wherein the correlation includes a match and/or an approximate match of the parameters with at least a portion of the information in the breathing profile being analyzed.

8. The computer- implemented method of claim 1, wherein the analyzing the parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles and/or the selecting the breathing profiles, to form the first candidate pool, is performed as a big data analysis.

9. The computer- implemented method of claim 1, wherein the information obtained from the candidate for the breathing profile associated with the candidate includes one or more of: resumes, Curriculum Vitale (CV), answers to questions, and/or answers to questionnaires.

10. The computer- implemented method of claim 1, wherein the external sources for information obtained about the candidate include one or more of: social media profiles, on-line information, on-line media articles and on-line publications.

11. The computer- implemented method of claim 1, additionally comprising: automatically sending the candidates of the first candidate pool one or more questions to which the received answers are analyzed.

12. The computer-implemented method of claim 1, wherein the analyzing the received answers to questions from candidates of the first candidate pool to determine a second candidate pool includes performing a big data analysis comprising correlating data between data established by a search engine for the position with the answers and/or information obtained from the received answers from the candidates of the first candidate pool.

13. The computer-implemented method of claim 12, wherein the correlation includes a match and/or an approximate match of the data.

14. A computer system for selecting candidates for a position comprising: a non-transitory storage medium for storing computer components; and a computerized processor for executing the computer components comprising: a first module for maintaining a plurality of breathing profiles, each breathing profile associated with at least one candidate, and comprising information for each at least one candidate, the information obtained from the candidate and/or from external sources, the information in each of the breathing profiles in a computer searchable format; a second module for: 1) searching one or more of the breathing profiles of the plurality of breathing profiles, the searching comprising analyzing parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles; and, 2) selecting breathing profiles associated with candidates whose breathing profiles include information which correlates with the parameters for the position, the candidates associated with the selected breathing profiles forming a first candidate pool; and a third module for analyzing received answers to questions from candidates of the first candidate pool to determine a second candidate pool, the number of candidates in the second candidate pool being not more than equal to the number of candidates in the first candidate pool.

15. The computer system of claim 14, additionally comprising: a fourth module for electronically transmitting a list of the candidates of the second candidate pool to the entity that requested candidates for the position.

16. The computer system of claim 14, wherein the first module is additionally configured for continuously updating the breathing profiles for the candidates including: adding information based on the received answers to questions from individual candidates to the information into the breathing profile for the candidate.

17. The computer system of claim 16, wherein the information based on the received answers includes: the answers to the questions and/or information derived from the answers to the questions.

18. The computer system of claim 14, wherein the third module is such that the number of candidates in the second candidate pool is less than the number of candidates in the first candidate pool.

19. The computer system of claim 14, additionally comprising a receiver module for receiving answers to filter questions from the entity that requested candidates for the position, the answers to the filter questions from which the parameters for the position are derived.

20. The computer system of claim 14, additionally comprising a parameter creation module for creating the parameters for the position by analyzing the position received from the entity that requested candidates for the position.

21. The computer system of claim 14, wherein the second module is such that the correlation includes a match and/or an approximate match of the parameters with at least a portion of the information in the breathing profile being analyzed.

22. The computer system of claim 14, wherein the second module performs the analyzing the parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles and/or the selecting the breathing profiles, to form the first candidate pool, as a big data analysis.

23. The computer system of claim 14, wherein the first module is additionally configured wherein the information obtained from the candidate for the breathing profile associated with the candidate includes one or more of: resumes, Curriculum Vitale (CV), answers to questions, and/or answers to questionnaires.

24. The computer system of claim 14, wherein the first module is such that the external sources for information obtained about the candidate include one or more of: social media profiles, on-line information, on-line media articles and on-line publications.

25. The computer system of claim 14, wherein the third module is additionally configured for automatically sending the candidates of the first candidate pool one or more questions to which the received answers are analyzed.

26. The computer system of claim 14, wherein the third module is additionally configured for the analyzing the received answers to questions from candidates of the first candidate pool to determine a second candidate pool by performing a big data analysis comprising correlating data between data established by a search engine for the position with the answers and/or information obtained from the received answers from the candidates of the first candidate pool.

27. The computer system of claim 26, wherein the correlation includes a match and/or an approximate match of the data.

28. A computer usable non-transitory storage medium having a computer program embodied thereon for causing a suitably programmed system to select candidates for a position, by performing the following steps when such program is executed by the system, the steps comprising: maintaining a plurality of breathing profiles, each breathing profile associated with at least one candidate, and comprising information for each at least one candidate, the information obtained from the candidate and/or from external sources, the information in each of the breathing profiles in a computer searchable format; searching one or more of the breathing profiles of the plurality of breathing profiles, the searching comprising analyzing parameters for a position for which candidates are requested by an entity, with the information in one or more breathing profiles of the plurality of breathing profiles; selecting breathing profiles associated with candidates whose breathing profiles include information which correlates with the parameters for the position, the candidates associated with the selected breathing profiles forming a first candidate pool; and analyzing received answers to questions from candidates of the first candidate pool to determine a second candidate pool, the number of candidates in the second candidate pool being not more than equal to the number of candidates in the first candidate pool.

29. The computer usable non-transitory storage medium of claim 28, wherein the steps additionally comprise: causing the electronic transmission of a list of the candidates of the second candidate pool to the entity that requested candidates for the position.

30. The computer usable non-transitory storage medium of claim 28, wherein the number of candidates in the second candidate pool is less than the number of candidates in the first candidate pool.

31. The computer usable non-transitory storage medium of claim 28, wherein the correlation includes a match and/or an approximate match of the parameters with at least a portion of the information in the breathing profile being analyzed.