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AMEY TILVE

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Papers by AMEY TILVE

This research focuses on Text Classification. Text classification is the task of automatically so... more This research focuses on Text Classification. Text classification is the task of automatically sorting a set of documents into categories from a predefined set. The domain of this research is the combination of information retrieval (IR) technology, Data mining and machine learning (ML) technology. This research will outline the fundamental traits of the technologies involved. This research uses three text classification algorithms (Naive Bayes, VSM for text classification and the new technique -Use of Stanford Tagger for text classification) to classify documents into different categories, which is trained on two different datasets (20 Newsgroups and New news dataset for five categories).In regards to the above classification strategies, Naïve Bayes is potentially good at serving as a text classification model due to its simplicity.

This research focuses on Text Classification. Text classification is the task of automatically so... more This research focuses on Text Classification. Text classification is the task of automatically sorting a set of documents into categories from a predefined set. The domain of this research is the combination of information retrieval (IR) technology, Data mining and machine learning (ML) technology. This research will outline the fundamental traits of the technologies involved. This research uses three text classification algorithms (Naive Bayes, VSM for text classification and the new technique-Use of Stanford Tagger for text classification) to classify documents into different categories, which is trained on two different datasets (20 Newsgroups and New news dataset for five categories).In regards to the above classification strategies, Naïve Bayes is potentially good at serving as a text classification model due to its simplicity.

This research focuses on Text Classification. Text classification is the task of automatically so... more This research focuses on Text Classification. Text classification is the task of automatically sorting a set of documents into categories from a predefined set. The domain of this research is the combination of information ret rieval (IR) technology, Data mining and machine learning (ML) technology. This research will outline the fundamental traits of the technologies involved. This research uses three text classification algorithms (Naive Bayes, VSM for text classificatio n and the new technique -Use of Stanford Tagger for text classific ation) to classify documents into different categories, which is trained on two different datasets (20 Newsgroups and New news dataset for five categories).In regards to the above classifica tion strategies, Naïve Bayes is potentially good at serving as a tex classification model due to its simplicity.

Lecture notes in networks and systems, 2023

International Journal of Information Technology, 2021

A large amount of textual data is generated online with rapid growth and technological advancemen... more A large amount of textual data is generated online with rapid growth and technological advancement. Deriving interesting patterns like opinions, summaries and facts from the text data is a challenging task. Currently, there is no dataset for subjectivity/objectivity classification data in Indian National Security domain. A News dataset has been created for purpose of subjective/objective sentence classification. This paper defines the news corpus annotation guidelines and employs an inter-annotator agreement metric to assess the quality of the dataset. The proposed methodology also highlights different challenges and limitations of building a corpus in the National Security domain. The corpus can be utilized for research work in developing robust subjective/objective sentence classifier. Furthermore, text categorization experiments are conducted on corpus, demonstrates that neural network based classifier gives promising result.

International Journal of Computer Sciences and Engineering, 2018

Evolutionary Computing and Mobile Sustainable Networks, 2022

This research focuses on Text Classification. Text classification is the task of automatically so... more This research focuses on Text Classification. Text classification is the task of automatically sorting a set of documents into categories from a predefined set. The domain of this research is the combination of information retrieval (IR) technology, Data mining and machine learning (ML) technology. This research will outline the fundamental traits of the technologies involved. This research uses three text classification algorithms (Naive Bayes, VSM for text classification and the new technique-Use of Stanford Tagger for text classification) to classify documents into different categories, which is trained on two different datasets (20 Newsgroups and New news dataset for five categories).In regards to the above classification strategies, Naïve Bayes is potentially good at serving as a text classification model due to its simplicity.

This research focuses on Text Classification. Text classification is the task of automatically so... more This research focuses on Text Classification. Text classification is the task of automatically sorting a set of documents into categories from a predefined set. The domain of this research is the combination of information ret rieval (IR) technology, Data mining and machine learning (ML) technology. This research will outline the fundamental traits of the technologies involved. This research uses three text classification algorithms (Naive Bayes, VSM for text classificatio n and the new technique -Use of Stanford Tagger for text classific ation) to classify documents into different categories, which is trained on two different datasets (20 Newsgroups and New news dataset for five categories).In regards to the above classifica tion strategies, Naïve Bayes is potentially good at serving as a tex classification model due to its simplicity.