Papers by Javubar Sathick
SN Computer Science
Usage of online learning platforms increases day by day and henceforth, there emerges the need fo... more Usage of online learning platforms increases day by day and henceforth, there emerges the need for automated grading systems to assess the learner's performance. Evaluating these answers demands for a well-grounded reference answer which aids a strong foundation for better grading. Since reference answers impacts the exactness of grading answers of learners, its correctness remains a great concern. A framework that addresses the reference answer exactness in Automated Short Answer Grading (ASAG) systems was developed. This framework includes material content acquisition, clustering collective content, expert answer as key components which was later fed to a zero-shot classifier for a strong reference answer generation. Then, the computed reference answers along with student answers and questions from Mohler dataset were fed to an ensemble of transformers to produce relevant grades. The aforementioned models' RMSE and correlation values were compared against the past values of the dataset. Based on the observations made, this model outperforms the previous approaches.
Survey on Crime Analysis and Prediction Using Data Mining and Machine Learning Techniques
Lecture Notes in Electrical Engineering, 2020
Crime is an unlawful event which affects the harmony of humanity. Whoever got victimized in a cri... more Crime is an unlawful event which affects the harmony of humanity. Whoever got victimized in a crime, it affects them both physically and mentally. Hence, they are haunted by the memories throughout their life. Due to the limitations, traditional data collection and analysis methods are not very effective now. Yesteryears, the researches were concentrating on demographic features of the population. Nowadays, the dynamic characteristics of individual or specific group could easily be extracted from the search engines, social media, e-commerce platforms, mobile applications, IOT devices, surveillance cameras, sensors and geographical information systems. The recent technological advancements are helpful in integration of data from various sources, classification of information into granular level, identification of crime sequences and designing a framework. Particularly, the artificial intelligence methodology called deep learning imitates the functions of human brain and able to acquire knowledge from unstructured data. It makes revolutionary changes in crime forecasting, predictive policing and legal strategy formulations. The following survey explores the possibilities of scrutinizing the data from huge repositories, analyzing various socioeconomic factors associated to the crime incidents, identifying the outliers, categorizing the patterns and designing effective computational models to predict crimes by using data mining and machine learning techniques.
Personalized and Optimal Ranking System for Recommendation in Heterogeneous Social Media Environment
Malnutrition Detection using Convolutional Neural Network
2021 Seventh International conference on Bio Signals, Images, and Instrumentation (ICBSII), 2021
Malnutrition is directly or indirectly responsible for the deaths of children younger than 5 year... more Malnutrition is directly or indirectly responsible for the deaths of children younger than 5 years in many countries. Identification of malnourished children will help to prevent the risk of death and can reduce physical and health issues by taking necessary measures or treatment. The proposed system uses a Convolutional Neural Network (CNN), a Deep Learning algorithm that takes input, analyzes the images, and differentiates one from the other. The architecture we used here is AlexNet for the training process and Transfer Learning. The system takes the image of a child as the input and classifies the image into a malnourished or normal child by comparing the image with the trained model. The objective of the system is to detect malnutrition in children that can help people and healthcare providers to reduce the effects caused by malnutrition by automation implementation instead of a manual process.
International Journal of Web-Based Learning and Teaching Technologies, 2021
Non-Factoid Question Answering (QA) is the next generation of textual QA systems, which gives pas... more Non-Factoid Question Answering (QA) is the next generation of textual QA systems, which gives passage level summaries for a natural language query, posted by the user. The main issue lies in the appropriateness of the generated summary. This paper proposes a framework for non-factoid QA system, which has three main components: (i) A deep neural network classifier, which produces sentence vector considering word correlation and context. (ii) Zero shot classifier that uses a multi-channel Convolutional Neural Network (CNN), to extract knowledge from multiple sources in the knowledge accumulator. This output acts as a knowledge enhancer that strengthens the passage level summary. (iii) Summary generator that uses Maximal Marginal Relevance (MMR) algorithm, which computes similarity among the query related answer and the sentences from zero shot classifier. This model is applied on the datasets WikiPassageQA and ANTIQUE. The experimental analysis shows that this model gives comparativel...
An Effective E-Learning Mechanism to Meet the Learning Demand of Industry 4.0
Industry 4.0 Interoperability, Analytics, Security, and Case Studies, 2021
Mining social web data is a challenging task and finding user interest for personalized and non-p... more Mining social web data is a challenging task and finding user interest for personalized and non-personalized recommendation systems is another important task. Knowledge sharing among web users has become crucial in determining usage of web data and personalizing content in various social websites as per the user’s wish. This paper aims to design a framework for extracting knowledge from web sources for the end users to take a right decision at a crucial juncture. The web data is collected from various web sources and structured appropriately and stored as an ontology based data repository. The proposed framework implements an online recommender application for the learners online who pursue their graduation in an open and distance learning environment. This framework possesses three phases: data repository, knowledge engine, and online recommendation system. The data repository possesses common data which is attained by the process of acquiring data from various web sources. The kno...
Indian Journal of Science and Technology, Jan 16, 2015
Enormous evolution of web data creates a peculiar myth in the field of computer and information t... more Enormous evolution of web data creates a peculiar myth in the field of computer and information technology for extracting the meaningful content from the web. Many organizations and social networks use databases for storing information and the data will be fetched from the specified data store. Data can be retrieved or accessed by SQL queries whereas the query is in the form of natural lingual statement which has to be processed. So, the primary objective of this research article is to find the suitable way to convert natural language query to SQL and make the data apt for semantic extraction. This Research paper also aims to derive an automatic query translator for Natural Language based questions into their associated SQL queries and provides an user friendly interface between end user and the database for easy access of social web data from different web sources such as facebook, twitter and linkedIn etc.,. This paper is implemented using java as the front end, SQL server as the back end and R-tool is used to collect the data from social web sources. This research article provides an optimized SQL query generation for the Natural Language question provided by the end user.
Feature extraction from behavioral styles of children for prediction of severity of stuttering using historical stuttering data
International Journal of Speech Technology
The International Review of Research in Open and Distributed Learning, 2015
Mining social web data is a challenging task and finding user interest for personalized and non-p... more Mining social web data is a challenging task and finding user interest for personalized and non-personalized recommendation systems is another important task. Knowledge sharing among web users has become crucial in determining usage of web data and personalizing content in various social websites as per the user’s wish. This paper aims to design a framework for extracting knowledge from web sources for the end users to take a right decision at a crucial juncture. The web data is collected from various web sources and structured appropriately and stored as an ontology based data repository. The proposed framework implements an online recommender application for the learners online who pursue their graduation in an open and distance learning environment. This framework possesses three phases: data repository, knowledge engine, and online recommendation system. The data repository possesses common data which is attained by the process of acquiring data from various web sources. The kno...
Natural Language to SQL Generation for Semantic Knowledge Extraction in Social Web Sources
Indian Journal of Science and Technology, 2015
Extraction of Actionable Knowledge to Predict Students' Academic Performance Using Data Mining Technique-an Experimental Study
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Papers by Javubar Sathick