Design And Implementation Of A Distributed Recruitment Management System

2.9.1.8    Recruiterbox
Recruiterbox is an online recruiting software that covers everything from resume management to interview scheduling. It lets you easily collect resumes from email applications; just forward your emails to Recruiterbox, and it will automatically create candidate profiles using the information in the email. You can also upload resumes from your computer in bulk. The software detects duplicate candidates, allows you to search keywords in any application and accepts all file formats. Recruiterbox's applicant-tracking system also lets you create custom stages, so the software matches your desired hiring process. You can also assign different people to those stages, so that all relevant team members can contribute to the hiring process when necessary. It also tracks candidates' progress and auto-archives applicants who aren't relevant to your search.
2.9.1.9    The Applicant Manager
The Applicant Manager (TAM) does everything from tracking applicants to hosting your business's own branded Careers page. The cloud-based software system allows you to access applicants' data from anywhere, at any time, and lets you create custom workflows and pre- screening forms. It merges duplicate applications, automatically screens out unqualified candidates, and ranks and sorts applicants based on your settings. TAM also integrates with your calendars to make scheduling and keeping track of interviews easier, and it integrates with your social networks for faster sharing. Additionally, the software automatically posts your job listings to both free and paid job boards.
2.9.1.10    The Resumator
The Resumator offers both free and paid job-board integration, with automatic syndication options and pay-per-post/pay-per-click advertising options. Need to make a change to the posting? The software cuts out the work of editing every post on every job board separately; just edit one posting, and the software automatically updates the rest. It tracks analytics on social referrals and employee referrals so that you can see what networks and employees help you find the most qualified candidates. The Resumator also lets you create a customizable, branded careers page that applicants can access from any device easily integrates with LinkedIn. You can also create custom questionnaires and assessments, and if you use Google or Microsoft Exchange, the software syncs with your existing calendars for easier interview scheduling.
2.9.2    Existing Projects
This section describes projects written by individuals describing various data mining techniques utilized in their research
2.9.2.1    Application of Association Rule Mining To Learning Management Systems
A method for carrying out exams without traditional face-face interaction between candidates
and examiners is provided in (Garcia et al, 2010). The e-learning system described aims at supporting strategic decision concerning the evaluation of learners’ activities and can be used in adapting and customizing resource delivery (Zaiane et al, 2001); discovering and comparison with expected behavioural patterns specified by the instructor that describes an ideal learning path (Donnellan, 2003); giving an indication of how to best organize the educational web space and be able to make suggestions to learners who share similar characteristics (Bae, 2000); generating personalized activities to different groups of learners (Tseng, 2004); supporting the evaluation and validation of learning site designs (Machado, 2003); identifying interaction sequences indicative of problems and patterns that are markers of success (Maisonneuve, 2006).
It proposed a predictive association rule model aimed at the design of a global intelligent information system while integrating all decision support systems, process automation, all types of communication requirements and their interactions. Some of the main drawbacks of this model are that the used algorithms have too many parameters for somebody non expert in data mining and the obtained rules are far too many, most of them non-interesting and with low comprehensibility also due to the nature of the domain data size was usually small about (10-100) depending on the course (Hamalainen et al, 2006). Subsequently, we present another application of association rule mining to recruitment.
2.9.2.2    Information Retrieval Using Fuzzy Logic
The reviewed work was an Information retrieval system implementing fuzzy logic model and this was compared with the apriori algorithm implemented in the R.M.S. Fuzzy logic is a way of interfacing inherently analog processes that move through a continuous range of values, to a digital computer, that likes to see things as well-defined discrete numeric values. Simply put, fuzzy logic is the logic of approximate reasoning. A fuzzy engine is any automated
machine whether hardware or software  that employs the concept of fuzzy logic in its implementation pattern of decision making. The fuzzy engine is made up of three constituent parts or modules namely: the fuzzification module, the Fuzzy Rule Base/Evaluation Module, the defuzzification module. In the fuzzy rule base, fuzzified inputs, μ(x=A1), μ(x=A2), μ(y=B1), and μ(y=B2), are applied to the antecedents of the fuzzy rules. The fuzzy operator (AND or OR) is used to obtain a single number that represents the result of the antecedent evaluation. This number (the truth value) is then applied to the consequent membership function. To evaluate the disjunction of the rule antecedents, we apply the OR fuzzy operation. Typically, fuzzy expert systems make use of the classical fuzzy operation, union to represent disjunction: μ (A𝖴B(x)) = max [μ (A(x)), μ (B(x))] similarly, in order to evaluate the conjunction of the rule antecedents, we apply the AND fuzzy operation intersection: μ (A∩B(x)) = min [μ (A(x)), μ (B(x))]. Now the result of the antecedent evaluation can be applied to the membership function of the consequent.