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Web Services Classification based on Wide & Bi-LSTM Model
2019
IEEE Access
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To solve this problem, a Web service classification method based on Wide & Bi-LSTM model is proposed in this paper. ...
INDEX TERMS Wide learning model, Bi-LSTM model, linear regression, web service classification. ...
CONCLUSION AND FUTURE WORK This paper presents a Web service classification method based on Wide&Bi-LSTM model. ...
doi:10.1109/access.2019.2907546
fatcat:xhtys2rymbg55ao67jzyvtr4gm
Deepbot: A Deep Neural Network based approach for Detecting Twitter Bots
2020
IOP Conference Series: Materials Science and Engineering
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For this challenge, the Deepbot is designed which adopts the Bi-LSTM model to analyze tweets and a Web interface is provided for public access which is developed using Web service. ...
Although various techniques have been proposed, this task is still challenging if we want to judge whether the tweets are posted by a bot or not merely based on the textual information. ...
In this paper, we propose a Bi-LSTM based Web application which can quickly detect bots based on only one piece of tweet. ...
doi:10.1088/1757-899x/719/1/012063
fatcat:bh4j2hkeenef5dpuhatddoyteq
ServeNet: A Deep Neural Network for Web Services Classification
[article]
2020
arXiv
pre-print
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Automated service classification plays a crucial role in service discovery, selection, and composition. Machine learning has been widely used for service classification in recent years. ...
and the length limitation, and then predict service classification on 50 service categories. ...
Two search approaches are widely used in service discovery [5] [6] . The first one is the keyword-based method. ...
arXiv:1806.05437v3
fatcat:o6vgiw4izve4fc7afyn36w7r4y
Real-time Leakage Current Classification of 15kV and 25kV distribution insulators based on Bidirectional Long Short-Term Memory Networks with Deep Learning Machine
2022
IEEE Access
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This paper presents an online monitoring system to classify the leakage/discharge current of the insulator in coastal sites using Bidirectional Long short-term memory (Bi-LSTM) models on a web-based service ...
Moreover, a web-based service is developed for maintenance staff to interact with all current and predicted status of insulators. ...
mechanism on a web-based service. ...
doi:10.1109/access.2022.3140479
fatcat:ut7aefcbo5eu7ef2m5pi22ecdi
Smart Contract Classification with a Bi-LSTM Based Approach
2020
IEEE Access
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Inspired by this, we proposed a smart contract classification approach based on Bi-LSTM model and Gaussian LDA, which can use a variety of information as inputs of the model, including source code, comments ...
INDEX TERMS Smart contract classification, Bi-LSTM, attention mechanism, Gaussian LDA, account information. ...
The other one considers Mashup requirements as application scenario to find best services. Besides, Cao et al. [9] used Bi-LSTM to learn the feature representations of Web services. ...
doi:10.1109/access.2020.2977362
fatcat:lylgzbigs5bfpiksnay5e3ksve
Identifying Emotion Labels from Psychiatric Social Texts Using a Bi-directional LSTM-CNN Model
2020
IEEE Access
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This study proposes a deep learning framework combining word embeddings, bi-directional long short-term memory (Bi-LSTM), and convolutional neural networks (CNN) to identify emotion labels from psychiatric ...
The Bi-LSTM is a powerful mechanism for extracting features from sequential data in which a sentence consists of multiple words in a particular sequence. ...
Healthcare-oriented web-based services draw many textbased queries related to depression. ...
doi:10.1109/access.2020.2985228
fatcat:nqqqxgssufcn3c6xaswqm4wzcm
GENETIC ALGORITHM - OPTIMIZED GATED RECURRENT UNIT (GRU) NETWORK FOR SEMANTIC WEB SERVICES CLASSIFICATION
2022
Malaysian Journal of Computer Science
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The novelty of the proposed model lies in implementing the GRU model for semantic web service classification. ...
The state-of-the-art of GRU (Gated Recurrent Unit) one of the RNN model, provides a proficient classification process. ...
The improved version of the LSTM model called the Bi_LSTM model is applied for web service classification [20] , that is initially developed by Google for deep and wide prediction of data to perform classification ...
doi:10.22452/mjcs.vol35no1.5
fatcat:nl6giqy6svgxjhailudclk62dm
Detection of Sentiment Analysis in Social Media using Deep Learning
2020
International journal of recent technology and engineering
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Furthermore, the prediction model trained using the activation function, Tanh, and when the amount of Bi-LSTM network layers is 2, the accuracy and F1-measure have a good better performance for sentiment ...
classification. ...
Bi-LSTM
Xu et al. (2019)
Binary
Hotel reviews
on travel
service Web
site, Ctrip
Bi-LSTM
Table - - II: The positive and negative lexical data and sources in our study Sentiment
dictionary ...
doi:10.35940/ijrte.a1927.059120
fatcat:eaw5doex6zcn5pbpqplqyl4chu
High-quality Train Data Generation for Deep Learning-based Web Page Classification Models
2021
IEEE Access
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Our experimental results with movies and cellphones data sets show that the average F 1 -score of the deep learning models (FNN, CNN, Bi-LSTM, and SeqGAN) trained with our proposed algorithm shows up to ...
The current deep learning models detecting relevant web pages show low accuracy because of the poor quality of the training data. ...
classification models (FNN, CNN, and Bi-LSTM) as shown in Table 5 . ...
doi:10.1109/access.2021.3086586
fatcat:4stqiqfnx5go5a5iimini4ds4i
Web Information Extraction methods using Web Content Mining (WCM) for Webapplications
2022
International Journal of Computing and Digital Systems
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Classification methods are used in Artificial Neural Networks (ANN), it would train the input data from the large network and segregate them based on the algorithms used by the user. ...
The technique Long Short-Term Memory (LSTM) is used to hold the status in intermediate memory then all generated data in web applications send this status to RNN for further classifications. ...
services discovery TF-IDF, LDA, WE-LDA, Deep mining of hidden information Wide & Bi-LSTM model Collaborative Filtering (CF) Sentiment-aware deep recommender system 8 Review based analysis Matrix factorization ...
doi:10.12785/ijcds/110149
fatcat:cpkcklt2rzh6dhwpd45yktybge
Multimodal Classification of Onion Services for Proactive Cyber Threat Intelligence Using Explainable Deep Learning
2022
IEEE Access
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In this paper, we propose a novel multimodal classification approach based on explainable deep learning that classifies onion services based on the image and text content of each site. ...
on the content, as well as provide an interpretation of the classification outcome. ...
The pipeline approach shown in Fig. 1 is widely adopted in building a dark web classification model. ...
doi:10.1109/access.2022.3176965
fatcat:dn4l6w5pqnbnzigsuzd46lf6oq
Unlocking the Power of Deep PICO Extraction: Step-wise Medical NER Identification
[article]
2020
arXiv
pre-print
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However, in most circumstances, there will be more than one evidences in an extracted sentence even it has been categorized to a certain class. ...
In table 2, we compare the PICO classification results of different models based on Bi-LSTM architecture. ...
However, the scores of the Bi-LSTM model are much higher than the CNN model's, so here we only show the result of the Bi-LSTM model as in Table 2 . ...
arXiv:2005.06601v1
fatcat:pllt66lorbhmngley7hwg2z6tm
Dominant Lexicon Based Bi-LSTM for Emotion Prediction on a Text
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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As a result the proposed model Selective Lexicon Based BI-LSTM (SL + BI-LSTM) outperforms all the models with high accuracy. ...
User-generated content and opinionative data has become a massive source of information on World Wide Web in the past few decades. ...
This final vector is given as an input to neural network models CNN [24] , LSTM [25] , BI-LSTM and Selective Lexicon based BI-LSTM to predict the emotion. ...
doi:10.35940/ijitee.k1256.09811s19
fatcat:klvw37y6ijgppkxfrojhxxapli
Deepfake tweets classification using stacked Bi-LSTM and words embedding
2021
PeerJ Computer Science
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Besides, the performance of deep learning models is analyzed including long short-term memory network, gated recurrent unit, bi-direction LSTM, and convolutional neural network+LSTM. ...
For this purpose, a stacked bi-directional long short-term memory (SBi-LSTM) network is proposed to classify the sentiment of deep fake tweets. ...
Bi-LSTM Bidirectional LSTM is an extension to the traditional LSTM. Bi-LSTM improves the performance of the model on sequence classification problems. ...
doi:10.7717/peerj-cs.745
pmid:34805502
pmcid:PMC8576542
fatcat:pcwuornoere7ricq7ilorh2ewu
Deep Learning-Based Autoscaling Using Bidirectional Long Short-Term Memory for Kubernetes
2021
Applied Sciences
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Furthermore, as compared to the LSTM model, the Bi-LSTM model performs better in terms of resource provision accuracy and elastic speedup. ...
Through experiments with two different realistic workloads, the Bi-LSTM model achieves better accuracy not only than the Long Short-Term Memory model but also than the state-of-the-art statistical auto-regression ...
The Bi-LSTM prediction model explained in Section 5 is compared with the forward LSTM and ARIMA prediction models. The configuration of each compared model differs based on different datasets. ...
doi:10.3390/app11093835
doaj:49c18189a30942c6bcafa77966cabdde
fatcat:qkf4lwpfh5ez7c25q5r42tidvq
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