Text Classification
4,465 Followers
Recent papers in Text Classification
The textual analysis has become most important task due to the rapid increase of the number of texts that have been continuously generated in several forms such as posts and chats in social media, emails, articles, and news. The... more
Most research in text classification to date has used a bag of words representation in which each feature corresponds to a single word. This paper examines some alternative ways to represent text based on syntactic and semantic... more
2013 curriculum is a new curriculum in the Indonesian education system which has been enacted by the government to replace KTSP curriculum. The implementation of this curriculum in the last few years has sparked various opinions among... more
–Text classification is used to classify the document of similar types. Text classification can be also performed under supervision i.e. it is an supervised leaning technique Text classification is a process in which documents are sorted... more
With growing texts of electronic documents used in many applications, a fast and accurate text classification method is very important. Arabic text classification is one of the most challenging topics. This is probably caused by the fact... more
'El Diario de Juárez' is a local newspaper in a city of 1.5 million Spanish-speaking inhabitants that publishes texts of which citizens read them on both a website and an RSS (Really Simple Syndication) service. This research applies... more
In recent years, impressive attention has been given for mining the publically available huge amount of data to gain situational awareness, which may help in preventing or decrease the effect of some disaster by taking the correct... more
The majority of the state-of-the-art text categorization algorithms are supervised and therefore require prior training. Besides the rigor involved in developing training datasets and the requirement for repetition of training for... more
Text Classification is the process of accommodating different categories of text on the basis of the content. It is a fundamental task of Natural Language Processing (NLP) having varied applications like sentiment analysis, spam... more
The increasing use of methods in natural language processing (NLP) which are based on huge corpora require that the lexical, morpho-syntactic and syntactic homogeneity of texts be mastered. We have developed a methodology and associate... more
Text Mining is the automatic discovery of new, previously unknown information, by automatic analysis of various textual resources. Text mining starts by extracting facts and events from textual sources and then enables forming new... more
Unsolicited communications currently accounts for over sixty percent of all sent e-mail with projections reaching the mid-eighties. While much spam is innocuous, a portion is engineered by criminals to prey upon, or scam, unsuspecting... more
Several text mining techniques have been proposed to deal with the huge number of textual documents that are available and that have been published nowadays. Mainly classification techniques, which assign pre-defined labels to new... more
We present a system that gathers and analyzes online discussion as it relates to consumer products. Weblogs and online message boards provide forums that record the voice of the public. Woven into this discussion is a wide range of... more
Text classification is a very important research area in machine learning. Artificial Intelligence is reshaping text classification techniques to better acquire knowledge. In spite of the growth and spread of AI in text mining research... more
Generating accurate and timely internal and external audit reports may seem difficult for some auditors due to limited time or expertise in matching the correct clauses of the standard with the textual statement of findings. To overcome... more
Student obligations imply writing a large number of homework assignments and term papers. Usually, they are submitted in electronic form. Checking papers for plagiarism isn’t an easy task. Quantity prevents teachers and professors to... more
As most information (over 80%) is stored as text, text mining is believed to have a high commercial potential value. knowledge may be discovered from many sources of information; yet, unstructured texts remain the largest readily... more
Social media has opened new avenues and opportunities for financial banking institutions to improve the quality of their products and services and to understand and to adapt to their cus-tomers' needs. By directly analyzing the feedback... more
Монография посвящена актуальному направлению изучения проблем стилистики методами математической лингвистики. В книге анализируются роль и место стилеметрии в филологических исследованиях, обсуждаются ее познавательные принципы и задачи,... more
Arab users give their comments and opinions daily, and it increases dramatically with the online reviews of products or services from companies, reviews in Arabic, and its dialects. This text describes the user's condition or needs for... more
With the rise of weblogs and the increasing tendency of online publications to turn to message-board style reader feedback venues, informal political discourse is becoming an important feature of the intellectual landscape of the... more
The massive amount of semi-structured data contained within the text documents makes the process of classifying them manually a very difficult task. Automatic text classification is the process of classifying documents based on their... more
This paper describes two classification supervised machine learning techniques of text data (tweets) based on Naive Bayes classifier and logistic regression. For creating features, a bag-of-words method is used. The goal of the project is... more
In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine... more
— Text mining is drawing enormous attention in this era as there is a huge amount of text data getting generated and it is required very hardly to manage this data to grasp maximum benefit out of it. Text classification is an essential... more
The aim of sentiment analysis is to automatically extract the opinions from a certain text and decide its sentiment. In this paper, we introduce the first publicly-available Twitter dataset on Sunnah and Shia (SSTD), as part of a... more
The main goal of this dissertation is to put different text classification tasks in the same frame, by mapping the input data into the common vector space of linguistic attributes. Subsequently, several classification problems of great... more