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Aman Burman secures admission into four Ivy League institutions too

Social network technologies have gained widespread attention in many fields. However, the research on Tibetan Social Network (TSN) is limited to the sentiment analysis of micro-blogs, and few researchers focus on text classification and data mining in TSN. It cannot meet the social needs of the majority of Tibetans and the text information they really care about. In this paper, we investigate and compare different models that we adopted for the classification of Tibetan text. Machine learning models including Naive Bayesian (NB), Random Forest (RF), Support Vector Machine (SVM), fastText and t...

Accurate manual detection of brain tumor by a team of radiologists may be a long and tedious process, and further rely on their skills in the subject. Nowadays various medical imaging modalities are extensively used to minimize the above complexities and enable the patients to live a long and healthy life. This paper mainly focuses on the suspected patients of the brain tumor. A new method for feature extraction has been introduced and the framework for it has been briefed in the following steps. To begin with, a dual segmentation i.e. Fuzzy K-mean and Expectation-Maximization method has been ...

The focal point of this work is to automatically detect metaphor instances in short texts. It is the study of extricating the most optimal features for the task by using a deep learning architecture and carefully hand-crafted contextual features. The first feature set is created using a Convolutional Neural Network (CNN) architecture. Then, three other feature sets are manually hand-crafted using contextual justifications. Next, all of the feature sets are combined. Finally, the combined feature sets undergo the classification process using Support Vector Machine, Logistic Regression, Decision...

The efficient maintenance and classification of huge amounts of data is a big challenge for the websites which provide services for online businesses. Many of the websites provide multiple services for the customer. In the present work, we have compared various machine learning-based classification methods for the efficient distribution of data. To effectively categorize the data, the Enterprise Interface (El) layer is suggested between the application layer and the physical layer. Methods based on global and local clustering are proposed for the effective distribution of the data in the El la...