Artificial Intelligence, Based Training and Placement Management

ABSTRACT

The Training and Placement cell in colleges is responsible for conducting all job interviews and skill development procedures for candidates. These procedures are carried out either manually or using some form of database software, which can be slow and inefficient. We, therefore, have taken a step forward to build an Artificial Intelligence-based solution to this problem. We propose a system where the admin and student can carry out all the training and placement related operations within an Artificial Intelligence-based environment.

This allows users to communicate with the AI-controlled system.

Keywords: Artificial Intelligence, Natural Language Processing, Chatbot, Artificial Intelligence Markup Language.

INTRODUCTION

The role of the Training and Placement Cell is to guide students in choosing the right career path and in developing necessary knowledge, skills, and aptitudes to meet manpower requirements of various industries. The cell assists students in defining and realizing their career goals, both short-term and long-term, through individual counseling and group sessions.

Moreover, it maintains and regularly updates student and company databases, and establishes strategic links for campus recruitments. It also gathers information about job fairs and all relevant recruitment advertisements. The cell liaises with companies to understand their recruitment procedures and expectations, and aids them in recruiting suitable candidates.

Organizing pre-placement training, workshops, and seminars for students is also within the cell’s responsibilities. Furthermore, it arranges periodic meetings with Human Resources Departments of companies and Training and Placement Officers to promote recruitment. It assists students in securing industrial training at the end of the fourth and sixth semesters, and provides resources and activities to facilitate the career planning process. The cell acts as a link between students, alumni, and the employment community.

Lastly, it aids students in obtaining placements in reputable companies. Keeping industry requirements in mind, the training curriculum is designed to prepare students as entry-level Graduate Engineer Trainees. The training encompass key aspects of the field which will be further expounded upon in the course.

• Personality Development
• Communication Skills & Vocabulary
• Resume Preparation & Email Writing
• Group Discussion
• Interview Skills
• Aptitude Training & Practice Tests
• Foreign Languages, such as Japanese & German

In this application, we are using natural language processing to create a chatbot to navigate through all the modules of the system, carrying out tests and skill development activities to monitor student improvement and skills. This application also provides various recommendations based on user needs and keeps users notified about all the training and placement related news and information.

PROBLEM STATEMENT

While conducting interviews, the company may need a list of recommended candidates fit for the job criteria. It has to manually go through the records of all the students and depend on their resumes for judging their skills. The students, seeking or preparing for the job, need proper guidance to prepare themselves for the interview. To attain industry-level skill sets, they need to go through proper training and analysis, which are either slow or inefficient in traditional training and placement procedures.

Motivation

Our analysis points out the high number of papers related to various applications of chatbot in the field of management. There is no implementation of such technology in training and placement. Our motive is to create a fully automated solution to the training and placement process where both the student and the training and placement coordinator can utilize our platform to play their individual respective roles more efficiently. As a candidate seeking jobs, they must be notified with news about various job openings and campus drives. Due to the absence of a unified personal communication platform, the admin may not be able to reach each and every candidate. A 24×7 solution to the guidance and communication is provided in our proposed system.

LITERATURE REVIEW

This section explores literature review. For more details, see table 1
Chatbot for University Related FAQs(2017)
Articial Intelligence Markup Language (AIML) and Latent Semantic Analysis (LSA) are used for developing chatbots, which are used to dene general queries like how do you do?, how can I help you etc. This pattern can also be used to give random responses for same query. LSA is a Latent Semantic Analysis,which is utilized to discover likenesses between words as vector representation. So that the unanswered queries by AIML will be viewed as a reply by LSA. Most chatbots basically search for keywords, phrases, and examples that have been customized into their databases, yet some utilize more propelled strategies. So far no chatbot has possessed the capacity to totally trick people into trusting it as one of them through its information of regular dialect. In this paper the need for chatbot in education domain is highlighted and designed to provide visitor satisfaction.
AIML is Articial Intelligence Markup Language (AIML) and Latent Semantic Analysis (LSA) are used for developing chatbots, which are used to dene general queries like how do you do?, how can I help you etc. This pattern can also be used to give random responses for same query. LSA is a Latent Semantic Analysis,which is utilized to discover likenesses between words as vector representation. So that the unanswered queries by AIML will be viewed as a reply by LSA. Most chatbots basically search for keywords, phrases, and examples that have been customized into their databases, yet some utilize more propelled strategies. So far no chatbot has possessed the capacity to totally trick people into trusting it as one of them through its information of regular dialect . In this paper the need for chatbot in education domain is highlighted and designed to provide visitor satisfaction.Uses the Artificial Intelligence Markup Language (AIML) to simulate human FAQs releted to University
Developing a Chatbot For College Student Programme Advertisement(2018)
Academic advisement has been widely regarded as an essential student support service in higher education. Student advisement typical refers to services supporting course selection, general mentorship, and career planning. Giving college students timely and relevant advice is known to positively influence student retention, progression, and graduation. Academic advisement provides many institutional benefits, including increased student loyalty and prospective student recruitment.
A Noval Approach For Medical Assistance Using Trained Chatbot(2017)
The proposed idea is to create a system with artificial intelligence that can meet the requirements. The AI can predict the diseases based on the symptoms and give the list of available treatments. The System can also give the composition of the medicines and their prescribed uses. It helps them to take the correct treatment. Hence the people can have an idea about their health and can have the right protection
 
Home Automation using IoT and a Chatbot using Natural Language Processing
Home automation—controlling fans, lights, and other electrical appliances in a house using the Internet of Things—is widely preferred in recent days. In this paper, we propose a web application by which fans, lights, and other electrical appliances can be controlled over the Internet. The important features of this web application are as follows: firstly, we have a chatbot algorithm allowing the user to text instructions for controlling the electrical appliances at home. The messages sent via the chatbot are processed using Natural Language Processing techniques. Secondly, any device connected to the house’s local area network can control the devices and appliances in the house. Thirdly, the web application used to enable home automation also includes a security feature, enabling only certain users to access the application. Finally, it sends an email alert when an intruder is detected using motion sensors.

Programming Challenges of a Chatbot: Current and Future Prospective (2017)

A chatbot is an instant messaging service able to provide services using instant messaging frameworks. Its aim is to deliver conversational services to users in an efficient manner. A chatbot is a quick, less confusing web and mobile application. It’s easy to install without the need for installation packages, which are simple to manage and distribute. Chatbots differ from human accounts as they don’t have any online status or “last seen” timestamps, nor do they initiate conversations or calls with other accounts. The intent classification module identifies the intent of a user’s message. The entity recognition module extracts structured bits of information from the message. The candidate response generator processes all the domain-specific calculations for the user’s request, and the response selector scores all response candidates and selects a response that will best suit the user.

Table 1: Comparison Between Reference Papers
Sr.No.    Year    System    Advantages    Limitations
1    2017    Chatbot for University Related FAQs
It provides full information about frequently asked questions related to students’ queries.   It doesn’t provide navigation throughout various website operations.

2    2018    Developing a Chatbot for College Student Program Advisement
It provides information about student program advisement.    It’s not applicable for interactions with various other operations apart from student program advisement.

3    2017    A Novel Approach for Medical Assistance Using a Trained Chatbot
It provides assistance to patients through human-computer interaction.    It’s only applicable in medical assistance.

4    2017    Home Automation using IoT and a Chatbot using Natural Language Processing.
It provides full control over home automation through an AI-based chatbot.    Its functionality is limited to home automation operations.

 PROPOSED SYSTEM

The proposed system application is developed as a tool to implement an automated solution to training and placement management procedures, providing an artificial intelligence-based approach. We provide a system where human-computer interaction takes place, offering a smart solution to the existing system traditionally carried out with a manual approach. This system consists of various modules and additional features which generate more efficient and sophisticated outcomes. By adding various artificial intelligence-based system components, such as a chatbot for interaction with the system and navigating through the modules, and a recommendation system to provide efficient, recommended outcomes based on various conditions, we take into consideration the user’s motives and needs. The system architecture is fully described below in Fig. 1: System Architecture. Below are the objectives of the proposed system:

• This system provides a full solution to the manually done procedure of Training and Placement.
• A chatbot to provide full assistance and navigation through all the modules of the system.
• Improvises and monitors student skill set by taking various computer-based exams.
• Provides a recommended candidate’s list according to their skill set.
• Displays various news and relevant information.

Fig. 1: System Details of Admin and Student Carrying Out Training and Placement Procedure Through Proposed System (System Architecture)

REFERENCES

1. Ranoliya, Bhavika R., Raghuwanshi, Nidhi, and Singh, Sanjay. “Chatbot for university related FAQs.” Advances in Computing, Communications and Informatics (ICACCI), 2017, pp. 1525-1530.
2. Rahman, A.M., Al Mamun, Abdullah, and Islam, Alma. “Programming challenges of chatbot: Current and future prospective.” Humanitarian Technology Conference (R10-HTC), 2017 IEEE Region 10, pp. 75-78.
3. Albayrak, Naz, Ozdemir, Aydeniz, and Zeydan, Engin. “An overview of artificial intelligence based chatbots and an example chatbot application.” Signal Processing and Communications Applications Conference (SIU), 2018, pp. 1-4.
4. Hussain, Shafquat, and Athula, Ginige. “Extending a conventional chatbot knowledge base to external knowledge source and introducing user based sessions for diabetes education.” Advanced Information Networking and Applications Workshops (WAINA), 2018, pp. 698-703.
5. Baby, Cyril Joe, Khan, Faizan Ayyub, and Swathi, JN. “Home automation using IoT and a chatbot using natural language processing.” Power and Advanced Computing Technologies (i-PACT), 2017 Innovations, 2017, pp. 1-6.
6. Choi, Hanjong, Hamanaka, Takeshi, and Matsui, Kanae. “Design and implementation of interactive product manual system using chatbot and sensed data.” Consumer Electronics (GCCE), 2017 IEEE 6th Global Conference, 2017, pp. 1-7.
7. D’Silva, Godson Michael, Thakare, Sanket, More, Shradha, and Kuriakose, Jeril. “Real world smart Chatbot for customer care using a software as a service (SaaS) architecture.” I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2017 International Conference, 2017, pp. 658-664.
8. Yushendri, Jefri, Hanif, Alvian Rahman, Siswadi, AnnekeAnnassia Putri, Musa, Purnawarman, Kusuma, Tubagus Maulana, and Wibowo, Eri Prasetyo. “A speech intelligence conversation bot for interactive media information.” Informatics and Computing (ICIC), 2017 Second International Conference, 2017, pp. 1-6.
9. Setiaji, Bayu, and Wibowo, Ferry Wahyu. “Chatbot using a knowledge in database.” 7th International Conference on Intelligent Systems, Modelling and Simulation, 2017.

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