Social media has provided the great opportunity for millions of internet users to express their opinions online. The online reviews have a huge potential to gain rich insight into an individual’s behavior towards an ...
详细信息
Social media has provided the great opportunity for millions of internet users to express their opinions online. The online reviews have a huge potential to gain rich insight into an individual’s behavior towards an entity. Sentiment analysis (SA) is a widely accepted Natural Language Processing (NLP) technique that helps in analyzing these reviews. Feature extraction (FE) plays a key role in enhancing the performance of a sentiment classification model. Historically, the most popular techniques employed for FE have been Term Frequency-Inverse Document Frequency (TF-IDF), Word2Vec and GloVe. But these approaches are non-contextual and also domain-specific. The recent research studies have utilized state-of-the-art (SOTA) context-aware Bidirectional Encoder Representations from Transformers (BERT) embeddings for building SA models. However, BERT employs cross-encoder architecture in which it can produce word embeddings only. Sentence embeddings can be derived by averaging word embeddings. But this method is computationally expensive and does not yield optimal sentence embeddings (SEs). To address the shortcomings in the existing FE methods, this paper introduces a novel technique to extract domain-insensitive high-quality SEs directly via Sentence Transformer (ST) and proposes a general-purpose unified framework for SA. In the proposed framework, first we generate semantically rich SEs employing ST and then integrate these embeddings into three different machine learning algorithms including logistic regression, random forest and support vector machine. The proposed method is evaluated on balanced and imbalanced datasets across seven diverse domains on the basis of F1-score, precision, recall, accuracy and AUC values. It has outperformed the existing FE approaches and several SOTA studies. Also, the significant improvement in F1 scores, ranging from 4% to 7% above the SOTA BERT embeddings in case of imbalanced datasets, highlights the efficiency of the proposed metho
The idea of fog computing enables the delivery of computational services and resources closer to the endpoints and users, at the network’s edge. Due to the large number of devices, determining the best resource alloc...
详细信息
An information system stores outside data in the backend database to process them efficiently and protects sensitive data from illegitimate flow or unauthorised users. However, most information systems are made in suc...
详细信息
Software bug repositories stores a wealth of information related to the problems that occurred during the software development. Today’s software development is a modular approach, with multiple developers working in ...
详细信息
The prospective applications of facial expression-based emotion recognition have sparked a lot of interest in domains like camera technology, mental health analysis, and human-computer interaction. Using the ResNet152...
详细信息
The process of testing conventional programs is quite easy as compared to the programs using Deep Learning approach. The term Deep learning (DL) is used for a novel programming approach that is highly data centric and...
详细信息
Blockchain and the Internet of Things (IoT), two of the most emerging technologies, are already reconfiguring our digital future, as described by the drastic change in the current network architecture. The incorporati...
详细信息
An ultra-wideband (UWB) slotted compact Vivaldi antenna with a microstrip line feed was evaluated for microwave imaging (MI) applications. The recommended FR4 substrate-based Vivaldi antenna is 50×50×1.5 mm3...
详细信息
Closed-Circuit Television (CCTV) cameras in public places have become more prominent with the rising firearm-related criminal activities, such as robberies, open firing, threats at gunpoint, etc. Early detection of fi...
详细信息
This study applies single-valued neutrosophic sets, which extend the frameworks of fuzzy and intuitionistic fuzzy sets, to graph theory. We introduce a new category of graphs called Single-Valued Heptapartitioned Neut...
详细信息
暂无评论