Dharani M

Bio: Dharani M is an academic researcher from Velagapudi Ramakrishna Siddhartha Engineering College. The author has contributed to research in topics: Password & Iris recognition. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Interactive Transport Enquiry with AI Chatbot

Abstract: Public transportation is used efficiently by millions of people all over the world. People tend to travel to different places and at certain times they may feel completely lost in a new place. Our chatbot comes to rescue at this time. A Chatbot is often described as one of the most promising tools for communication between humans and machines using artificial intelligence. It is a software application that is used to conduct an online chat conversation via text by using natural language processing (NLP) and deep learning techniques. It provides direct contact with a live human agent in the form of GUI. This AI chatbot confirms the current location and the final destination of the user by asking a few questions. It examines the user’s query and extracts the appropriate entries from the database. The deep learning techniques that are used in this chatbot are responsible for understanding the user intents accurately to avoid any misconceptions. Once the user’s intention has been recognized, the chatbot provides the most relevant response for the user’s query request. Then the user gets all the information about the bus names along with their numbers so that the person can travel safely to the desired location. Our chatbot is implemented in python's Keras library and used Tkinter for GUI.

IRIS-Based Human Identity Recognition with Deep Learning Methods

Abstract: Abstract: One of the most important computer system modules is the one in charge of user security. It has been demonstrated that simple logins and passwords cannot provide high efficiency and are simple for hackers to crack. The popular substitute is identity identification using bio-metrics. Iris as a biometric characteristic has attracted increased attention in recent years. It was brought on by the high efficiency and precision this quantifiable aspect ensured. Throughout the literature, the effects of this curiosity can be seen. Several authors have put forth a variety of various approaches. This paper describe methods for an irisbased algorithm for recognizing human identity. Artificial neural networks (ANN) and a CNN-based transfer learning model (Mobile-net) were employed in the classification process. Once the output has been categorized, the iris component is segmented using a process called segmentation. Tests that have been run have demonstrated that the suggested procedure can produce results that are adequate.

Virtual Assistant for Prediction of Fake Job Profile Using Machine Learning

Abstract: To avoid fraudulent post for job in the internet, an android application using machine learning based classification techniques is proposed in the paper. Different classifiers are used for checking fraudulent post in the web and the results of those classifiers are compared for identifying the best fake job scam detection model. It helps in detecting fake job posts from an enormous number of posts. It is an android application that is used to conduct an online conversation via text and speech by using natural language processing (NLP) and predicts the fake job offers using machine learning techniques. The data we used contains real and fake job post. We cleaned and pre-processed our data. After we implemented the classifiers, we trained and evaluated them for prediction of fake job offers.

A Chatbot to promote Students Mental Health through Emotion Recognition

Abstract: The objective of this paper is to develop a chatbot for students to promote their mental health through emotion recognition technique. Nowadays, students are facing a lot of mental health issues due to various reasons like pandemic lockdowns, peer pressure, social media bullying, academic stress, loneliness, sexual harassment, etc. Because of which students are unable to progress well in their life, both emotionally and academically. Due to the battle of life, the students are also unable to receive proper guidance from experienced and knowledgeable humans to solve their personal issues. Therefore, developing a human friendly chatbot that can help students get the right guidance for their issues at the right time is a much needed one. These kind of chatbots can play a vital role in reducing the number of suicides in the country due to depression and stress. The chatbot named Maxx helps students solve or prevent any mental health issue in their day-to-day life. Maxx converses with the student, understands his/her present emotional state/mental health issue (if any), identifies the cause of that emotion/mental health issue and provides the right guidance based on the reason identified. Maxx uses technologies like DialogFlow for Natural Language Processing (NLP), Flutter for app development and Google Cloud Platform (GCP) for data storage and security.

Building a Chatbot System to Analyze Opinions of English Comments

Abstract: Chatbot research has advanced significantly over the years. Enterprises have been investigating how to improve these tools’ performance, adoption, and implementation to communicate with customers or internal teams through social media. Besides, businesses also want to pay attention to quality reviews from customers via social networks about products available in the market. From there, please select a new method to improve the service quality of their products and then send it to publishing agencies to publish based on the needs and evaluation of society. Although there have been numerous recent studies, not all of them address the issue of opinion evaluation on the chatbot system. The primary goal of this paper’s research is to evaluate human comments in English via the chatbot system. The system’s documents are preprocessed and opinion-matched to provide opinion judgments based on English comments. Based on practical needs and social conditions, this methodology aims to evolve chatbot content based on user inter-actions, allowing for a cyclic and human-supervised process with the following steps to evaluate comments in English. First, we preprocess the input data by collecting social media comments, and then our system parses those comments according to the rating views for each topic covered. Finally, our system will give a rating and comment result for each comment entered into the system. Experiments show that our method can improve accuracy better than the referenced methods by 78.53%.

Text Mining Approaches Oriented on Customer Care Efficiency

Abstract: In the proposed work is performed a text classification for a chatbot application used by a company working in assistance services of automatic warehouses. industries. Specifically, text mining technique is adopted for the classification of questions and answers. Business Process Modeling Notation (BPMN) models describe the passage from “AS-IS” to “TO BE” in the context of the analyzed industry, by focusing the attention mainly on customer and technical support services where chatbot is adopted. A two-step process model is used to connect technological improvements and relationship marketing in chatbot assistance: the first step provides the hierarchical clustering able to classify questions and answers through Latent Dirichlet Allocation -LDA- algorithm, and the second one executes the Tag Cloud representing the visual representation of more frequent words contained in the experimental dataset. Tag cloud is used to show the critical issues that customers find in the usage of the proposed service. By considering an initial dataset, 24 hierarchical clusters are found representing the preliminary combination of the couple’s question-answer. The proposed approach is suitable to automatically construct a combination of chatbot questions and appropriate answers in intelligent systems.

Chatbot using NLP

Abstract: A chatbot is a application which is mainly used to provide text-based or text-to-speech online chat conversations in place of live human chat operators. The chatbot aims to establish connection between and a machine and a human. The machine incorporates data so that it can recognize the sentences and come to a conclusion in response to an inquiry. The response principle is the matching of the user's input phrase. The current technological effort involves establishing a chatbot-based system for college inquiries that uses Natural Language Processing to send natural language to a server. In this project, we're creating a chatbot that can answer users' questions about the college. The user will be able to ask the chatbot different questions about the college, including inquiries about the infrastructure and courses. The user will able to ask various questions to the chatbot about the college, the questions may be concerned with the infrastructure and courses.