Text categorization
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Deep Pyramid Convolutional Neural Networks for Text Categorization Open
This paper proposes a low-complexity word-level deep convolutional neural network (CNN) architecture for text categorization that can efficiently represent long-range associations in text. In the literature, several deep and complex neural…
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Effective Use of Word Order for Text Categorization with Convolutional Neural Networks Open
Convolutional neural network (CNN) is a neural network that can make use of the internal structure of data such as the 2D structure of image data. This paper studies CNN on text categorization to exploit the 1D structure (namely, word orde…
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Sentiment analysis using product review data Open
Sentiment analysis or opinion mining is one of the major tasks of NLP (Natural Language Processing). Sentiment analysis has gain much attention in recent years. In this paper, we aim to tackle the problem of sentiment polarity categorizati…
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Toward Optimal Feature Selection in Naive Bayes for Text Categorization Open
Automated feature selection is important for text categorization to reduce\nthe feature size and to speed up the learning process of classifiers. In this\npaper, we present a novel and efficient feature selection framework based on\nthe In…
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Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding Open
This paper presents a new semi-supervised framework with convolutional neural networks (CNNs) for text categorization. Unlike the previous approaches that rely on word embeddings, our method learns embeddings of small text regions from unl…
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Performances of K-Means Clustering Algorithm with Different Distance Metrics Open
Clustering is the process of grouping the data based on their similar properties. Meanwhile, it is the categorization of a set of data into similar groups (clusters), and the elements in each cluster share similarities, where... | Find, re…
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Sentiment analysis and classification of Indian farmers’ protest using twitter data Open
Protests are an integral part of democracy and an important source for citizens to convey their demands and/or dissatisfaction to the government. As citizens become more aware of their rights, there has been an increasing number of protest…
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Semantic Clustering and Convolutional Neural Network for Short Text Categorization Open
Peng Wang, Jiaming Xu, Bo Xu, Chenglin Liu, Heng Zhang, Fangyuan Wang, Hongwei Hao. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Proc…
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A Bayesian Classification Approach Using Class-Specific Features for Text Categorization Open
In this paper, we present a Bayesian classification approach for automatic text categorization using class-specific features. Unlike conventional text categorization approaches, our proposed method selects a specific feature subset for eac…
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Medical Text Classification using Convolutional Neural Networks Open
We present an approach to automatically classify clinical text at a sentence level. We are using deep convolutional neural networks to represent complex features. We train the network on a dataset providing a broad categorization of health…
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Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding. Open
This paper presents a new semi-supervised framework with convolutional neural networks (CNNs) for text categorization. Unlike the previous approaches that rely on word embeddings, our method learns embeddings of small text regions from unl…
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Seeing the wood for the trees: How machine learning can help firms in identifying relevant electronic word-of-mouth in social media Open
The increasing volume of firm-related conversations on social media has made it considerably more difficult for marketers to track and analyse electronic word-of-mouth (eWOM) about brands, products or services. Firms often use sentiment an…
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Feature Selection Using Particle Swarm Optimization in Text Categorization Open
Feature selection is the main step in classification systems, a procedure that selects a subset from original features. Feature selection is one of major challenges in text categorization. The high dimensionality of feature space increases…
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Text Categorization as a Graph Classification Problem Open
François Rousseau, Emmanouil Kiagias, Michalis Vazirgiannis. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long …
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Disconnected Recurrent Neural Networks for Text Categorization Open
Recurrent neural network (RNN) has achieved remarkable performance in text categorization. RNN can model the entire sequence and capture long-term dependencies, but it does not do well in extracting key patterns. In contrast, convolutional…
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Neural Discourse Structure for Text Categorization Open
We show that discourse structure, as defined by Rhetorical Structure Theory and provided by an existing discourse parser, benefits text categorization. Our approach uses a recursive neural network and a newly proposed attention mechanism t…
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HFT-CNN: Learning Hierarchical Category Structure for Multi-label Short Text Categorization Open
We focus on the multi-label categorization task for short texts and explore the use of a hierarchical structure (HS) of categories. In contrast to the existing work using non-hierarchical flat model, the method leverages the hierarchical r…
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Text categorization Performance examination Using Machine Learning Algorithms Open
Automated text categorization has been measured as a crucial technique for run and practice a huge quantity of papers in digital appearances that were extensive & constantly growing. In common, text categorization acts a significant respon…
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Arabic Text Categorization Using Support vector machine, Naïve Bayes and Neural Network Open
Text classification is a very important area in information retrieval. Text classification techniques used to classify documents into a set of predefined categories. There are several techniques and methods used to classify data and in fac…
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The Lao Text Classification Method Based on KNN Open
Text categorization is a common application scenario in the NLP field, and has many applications in public opinion monitoring and news classification. At present, there are few classifications for Lao text, but classification-oriented meth…
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IGICA: A Hybrid Feature Selection Approach in Text Categorization Open
Feature selection problem is one of the most important issues in machine learning and statistical pattern recognition.This problem is important in many applications such as text categorization because there are many redundant and irrelevan…
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A Sentiment Polarity Categorization Technique for Online Product Reviews Open
Sentiment analysis is also known as opinion mining which shows the people’s opinions and emotions about certain products or services. The main problem in sentiment analysis is the sentiment polarity categorization that determines whether a…
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A Novel Neural Network-Based Method for Medical Text Classification Open
Medical text categorization is a specific area of text categorization. Classification for medical texts is considered a special case of text classification. Medical text includes medical records and medical literature, both of which are im…
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Machine Learning Models of Text Categorization by Author Gender Using Topic-independent Features Open
In the present article, we address the problem of automatic text classification according to the author's gender. We used a preexisting corpus of Russian-language texts RusPersonality labeled with information on their authors (gender, age,…
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Sentiment Analysis: It’s Complicated! Open
Sentiment analysis is used as a proxy to measure human emotion, where the objective is to categorize text according to some predefined notion of sentiment.Sentiment analysis datasets are typically constructed with gold-standard sentiment l…
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Medical Concept Embedding with Multiple Ontological Representations Open
Learning representations of medical concepts from the Electronic Health Records (EHR) has been shown effective for predictive analytics in healthcare. Incorporation of medical ontologies has also been explored to further enhance the accura…
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Long-tail Vocabulary Dictionary Extraction from the Web Open
A dictionary --- a set of instances belonging to the same conceptual class --- is central to information extraction and is a useful primitive for many applications, including query log analysis and document categorization. Considerable wor…
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These are not the Stereotypes You are Looking For: Bias and Fairness in Authorial Gender Attribution Open
Stylometric and text categorization results show that author gender can be discerned in texts with relatively high accuracy. However, it is difficult to explain what gives rise to these results and there are many possible confounding facto…
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LSA & LDA topic modeling classification: comparison study on e-books Open
With the rapid growth of information technology, the amount of unstructured text data in digital libraries is rapidly increased and has become a big challenge in analyzing, organizing and how to classify text automatically in E-research re…
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A Study on Term Weighting for Text Categorization: A Novel Supervised Variant of tf.idf Open
Within text categorization and other data mining tasks, the use of suitable methods for term weighting can bring a substantial boost in effectiveness. Several term weighting methods have been presented throughout literature, based on assum…