With advanced innovation in digital technology, demand for virtual assistants is arising which can assist a person
and at the same time, minimize the need for interaction with the human. Acknowledging the requirement, we
propose an interactive and intelligent student assistant, StuA, which can help new-comer in a college who are
hesitant in interacting with the seniors as they fear of being ragged. StuA is capable of answering all types of
queries of a new-comer related to academics, examinations, library, hostel and extra curriculum activities. The
model is designed using CLIPS which allows inferring using forward chaining. Nevertheless, a generalized
algorithm for backward chaining for CLIPS is also implemented. Validation of the proposed model is presented
in five steps which show that the model is complete and consistent with 99.16% accuracy of the knowledge
model. Moreover, the backward chaining algorithm is found to be 100% accurate.

/pdf/stua-an-intelligent-student-assistant-28aefqprul.pdf

StuA: An Intelligent Student Assistant

Cognition2Vocation: meta-learning via ConvNets and continuous transformers

  Abstract — Every job demands an employee with some specific qualities in addition to the basic educational qualification For example, an introvert person cannot be a good leader despite of a very good academic qualification Thinking and logical ability is required for a person to be a successful software engineer So, the aim of this paper is to present a novel approach for advising an ideal job to the job seeker while considering his personality trait and educational qualification both Very well-known theories of personality like MBTI indicator and OCEAN theory, are used for personality mining For education mining, score based system is used The score based system captures the information from attributes like most scoring subject, dream job etc After personality mining, the resultant values are coalesced with the information extracted from education mining And finally, the most suited jobs, in terms of personality and educational qualification are recommended to the job seekers The experiment is conducted on the students who have earned an engineering degree in the field of computer science, information technology and electronics Nevertheless, the same architecture can easily be extended to other educational degrees also To the best of the author's knowledge, this is a first e-job advisory system that recommends the job best suited as per one's personality using MBTI and OCEAN theory both

/pdf/personality-and-education-mining-based-job-advisory-system-4tke2pqp79.pdf

Personality and Education Mining based Job Advisory System

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Personality and Education Mining based Job Advisory System