Word Sense Disambiguation Based Sentiment Classification Using Linear Kernel Learning Scheme

Word Sense Disambiguation has been a trending topic of research in Natural Language Processing and Machine Learning.Mining core features and performing the text classification still exist as a challenging task.Here the features of the context such as neighboring words like adjective provide the evidence for classification using machine learning approach.This paper presented the text document classification that has wide applications in information retrieval,which uses movie review datasets.Here the document indexing based on controlled vocabulary,adjective,word sense disambiguation,generating hierarchical cate-gorization of web pages,spam detection,topic labeling,web search,document summarization,etc.Here the kernel support vector machine learning algorithm helps to classify the text and feature extract is performed by cuckoo search opti-mization.Positive review and negative review of movie dataset is presented to get the better classification accuracy.Experimental results focused with context mining,feature analysis and classification.By comparing with the previous work,proposed work designed to achieve the efficient results.Overall design is per-formed with MATLAB 2020a tool.

Classification of Foot Pressure Images Using Machine Learning Algorithm

Arthritis is an acute systemic disease of a joint accompanied by pain.In developed countries,it mainly causes disability among people over 50 years of age.Rheumatoid Arthritis is a type of arthritis that occurs commonly among elders.The incidence of arthritis is higher in females than in males.There is no permanent diagnosis method for arthritis,but if it was identified in the early stages based on the foot pressure,it can be diagnosed before attaining the critical stage of Rheumatoid Arthritis.The analysis and study of arthritis patients were done using design thinking methodology.Design thinking is a problem-solving methodology that is used tofind a solution for the identification of the early stage of arthritis.This process consists offive stages follows Empathy,Define,Ideate,Prototype,and Testing.To define the problem statement,the Empathy was done with the arthritis patients to know the difficulties faced by them.This paper proposes a measurement technique of early measurement of arthritis using a non-invasive technique.It helps us to detect arthritis using a foot pressure pad that was designed with piezoresistive material and the feature classification was done using Weka.