In the digital age, the recruitment industry has transformed with the rise of AI

NEW YORK, NY, UNITED STATES, January 25, 2024 /EINPresswire.com/ -- New York, — Expertini.Com, a global job site headquartered in London, is unveiling Resume Score™, an AI tool designed to streamline recruitment processes and foster unbiased candidate selection.

In response to the rapid evolution of the workforce ecosystem in the digital age, Expertini acknowledges the transformative impact of AI on the recruitment industry. The company has developed Resume Score™ with a dedicated research team, including members such as Dr. S. M. M. Habibi Ph.D., Ms. Najwa Hadi, Dr. Fareeda Quadeer, Mr. Zainulabidin Nadeem, Mr. Syed Anwar, Mr. Nikhil Patel, Mr. Colwyn Heck, Mr. Marvin Kuhn, and Australia coordinator Mr. Imam Yaser.

The Application Tracking System (ATS), introduced in the 1990s, has been a pivotal tool in streamlining hiring processes. Expertini's advanced ATS, utilizing Semantic Search and NLP, incorporates a matching algorithm rooted in Cosine Similarity†. This technology, categorized under Applied Science, objectively scores resumes based on a job description matching algorithm using Cosine similarity:

Sc (A,B):= cos(θ) = A * B / ||A|| ||B|| = n∑i=1 Ai * Bi /√ n∑i=1 (A2i) * √ n∑i=1 (B2i)

This mathematical formula, with values ranging from -1 to 1, quantitatively assesses resumes against job criteria, ensuring effective and accurate scoring.

Expertini emphasizes, "Although technology should not be deemed a replacement for the human mind, it is more appropriate to use it for enhancement, speed, and facilitating tools." It goes on to say, "Even as AI introduces efficiency to recruitment procedures, the invaluable human touch remains irreplaceable."

Expertini's objective approach minimizes unconscious bias in traditional hiring processes, facilitating a more diverse and inclusive workforce. These AI-driven tools can enrich the recruitment funnel, handling initial short-lists and thereby preserving valuable time for recruiters to identify the right talent. This automated approach not only saves time but also optimizes resources.

According to Expertini, the incorporation of AI into recruitment marks a transformative shift, evolving the industry from a labor-intensive, manual process to a data-driven, efficient, and strategic function. As organizations increasingly adopt AI technologies, they secure a competitive advantage in identifying, attracting, and retaining top talent through the utilization of AI, ML, and NLP. Harnessing Resume Scoring for decision-making empowers companies to construct agile and responsive teams equipped to navigate the intricacies of the modern business landscape.

AI tools play a crucial role in mitigating unconscious biases in the recruitment process. By focusing on objective criteria and analyzing candidate qualifications without prejudice, AI contributes to creating a more diverse and inclusive workforce, fostering innovation and productivity. Expertini asserts that the integration of AI in recruitment can empower ethical values ensuring fair resume scoring as computer AI and algorithms are mostly built to be unbiased and provide equal opportunities. This is a vital step towards removing ethnic bias.

Resume Score™ not only benefits recruiters but also empowers job seekers by providing insights into their resumes' strengths and weaknesses. This level of transparency enhances the application process, enabling candidates to strategically position themselves in alignment with market demands.

Expertini's global platform spans job listings across more than 100 countries, providing a user-friendly interface integrated with web services, APIs, and partner networks. Importantly, the platform is offered free of charge to employers, recruiters, and job seekers worldwide. Collaborating with influential channels like Google for Jobs and Zoho, Expertini extends its reach, enhancing job posting visibility.

The user-friendly interface allows employers to efficiently create and publish job listings. There are no hidden costs; Expertini is entirely free for all users. Employers can easily navigate the platform to post free job listings for their local regions. Multilingual and equipped with free tools such as Resume-Score, Job Score, and an ATS system, the platform streamlines the hiring process. Job seekers are also welcomed to register, analyze their Resumes/CVs, and assess their profiles before submitting applications to Employers/Recruiters—all without any charges. The built-in Resume Builder supports .pdf, .doc, and .docx Resume/CV formats for scoring.

The AI-driven Resume Score™ accelerates the hiring process by enabling AI to manage the initial workload for recruiters. Additionally, it offers valuable insights to candidates regarding their strengths before application submission, empowering them to recognize their strengths and motivating them to seek additional knowledge to address any skill gaps.

Notes and References:
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† Trigonometry seems to have originated in the Hellenistic world, with Hipparchus (c. 190 – c. 120 BC) considered its founder. It was later expounded by Al-Battani (ca. 858-929) in his astronomical work "The Perfection of the Almagest," who defined the trigonometric functions. Abu'l Wafa (940-997/998), in his work, systematically set the elements of trigonometry. Al-Biruni (973-1048) outlined in-depth in his "Mas'udic Canon." Additionally, al-Tusi's (1201-1274) "Treatise on the Complete Quadrilateral" provided extraordinary trigonometrical formulas for plane and spherical triangles. These works played a crucial role in computing mathematical calculations for today's modern science.

1. Encyclopaedia of the History of Science, Technology, and Medicine in Non-Western Cultures. (2008). Germany: Springer.

2. G. Richard, A. Rizk. Semantics of the concurrent logic programming language PARLOG. RR-0848, INRIA. 1988. ffinria-00075705f.

3. Bondielli, Alessandro, and Francesco Marcelloni. "A data-driven approach to automatic extraction of professional figure profiles from Résumés." Intelligent Data Engineering and Automated Learning–IDEAL 2019: 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I 20. Springer International Publishing, 2019.

4. Dehak, N., Dehak, R., Glass, J., Reynolds, D., Kenny, P. (2010). "Cosine Similarity Scoring without Score Normalization Techniques." MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA.

5. Singhal, Amit. "Modern Information Retrieval: A Brief Overview." Google Inc., 2001, and Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 24 (4): 35–43."

Ahsan Syed
Expertini
Info@Expertini.com
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