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A Study of Scoring English Tests Using an Automatic Scoring Model Incorporating Semantics
AbstractThe automatic essay scoring (AES) model enables automatic analysis and scoring of texts, which is an essential element in education. This...
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The ultimate recommendation system: proposed Pranik System
In today's fast-paced world, recommendation systems have become indispensable tools, aiding users in making personalized decisions amidst an...
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Incorporating Word Embedding and Hybrid Model Random Forest Softmax Regression for Predicting News Categories
Online media reshaped the news industry leading to information richness, timely dissemination, and immense diversity. In addition, recent...
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Classification of Offensive Tweet in Marathi Language Using Machine Learning Models
Offensive language identification is essential to make social media a safe and clean place to share one’s view. In this work, a model is proposed to...
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Low-time-complexity document clustering using memristive dot product engine
Document clustering has been commonly accepted in the field of data analysis. Nevertheless, the challenging issues for the clustering are the massive...
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An empirical study of automated privacy requirements classification in issue reports
The recent advent of data protection laws and regulations has emerged to protect privacy and personal information of individuals. As the cases of...
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A term extraction algorithm based on machine learning and comprehensive feature strategy
Manual term extraction is similar to literal meaning: A translator browses text, classifies words, and prepares for translation. Terminology, as a...
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Research on Automatic Summary Method for Futures Research Reports Based on TextRank
Futures research reports, authored by futures analysts, delve into various aspects such as futures contracts, the macro-environment, industry trends,...
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Leveraging contextual features to enhanced machine learning models in detecting COVID-19 fake news
The proliferation of fake news on online social networks, particularly Twitter, has become a major issue in recent years. False and potentially...
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Deep bidirectional LSTM for disease classification supporting hospital admission based on pre-diagnosis: a case study in Vietnam
Overcrowding in hospitals in Vietnam has caused many disadvantages in receiving and treating patients. Especially at the stage of receiving and...
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Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models
Sentiment analysis holds significant value for e-commerce companies, enabling them to gain insights from customer sentiment. By evaluating customer...
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Query-Document Topic Mismatch Detection
Query-document topic match is one of the central signals for ranked information retrieval. Returning documents which are too broad or insufficient or...
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The Problems and Methods of Automatic Text Document Classification
AbstractThis paper gives a review of the main problems and methods of automatic text classification. It focuses on problems such as the choice of...
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PSLDA: a novel supervised pseudo document-based topic model for short texts
Various kinds of online social media applications such as Twitter and Weibo, have brought a huge volume of short texts. However, mining semantic...
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Feature selection based on term frequency deviation rate for text classification
Feature selection is a technique to select a subset of the most relevant features for modeling training. In this paper, a new concept of TDR is...
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A hybrid approach of Poisson distribution LDA with deep Siamese Bi-LSTM and GRU model for semantic similarity prediction for text data
Prediction of semantic similarity between text data is an open and challenging research issue in the NLP-Natural Language-processing field....
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Enhancing stock market prediction using three-phase classifier and EM-EPO optimization with news feeds and historical data
Stock price forecasting is a crucial area of research that demands a thorough comprehension of market dynamics and sophisticated analytical methods....
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Emoji Based Sentiment Classification Using Machine Learning Approach
Online media platforms like Facebook, Twitter, and Instagram continue to influence our world. People today are more closely connected than ever...
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COVID-19 Literature Mining and Retrieval Using Text Mining Approaches
In light of the recent COVID-19 epidemic, users are facing growing difficulties in navigating the vast expanse of Internet content to locate relevant...
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Comparing Bag of Words and TF-IDF with different models for hate speech detection from live tweets
Social media platforms such as Twitter have revolutionized online communication and interactions but often contain components of disdain for its...
