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Information Filtering and Automatic Keyword Identification by Artificial Neural Networks

Zvi Boger, Tsvi Kuflik, Bracha Shapira, Peretz Shoval
2000 European Conference on Information Systems  
In this study we employ an artificial neural-network (ANN) as an alternative method for both filtering and term selection, and compare its effectiveness to "traditional" methods.  ...  Information filtering (IF) systems usually filter data items by correlating a vector of terms (keywords) that represent the user profile with similar vectors of terms that represent the data items (e.g  ...  Brief Introduction to Artificial Neural Networks Modeling ANN modeling is done by learning from known examples. A network of simple mathematical "neurons" is connected by weights.  ... 
dblp:conf/ecis/BogerKSS00 fatcat:tllwtk2brzdidipfez5m4vdto4

Chinese User Service Intention Classification Based on Hybrid Neural Network

Shengbin Jia, Yang Xiang
2019 Journal of Physics, Conference Series  
Therefore, a hybrid neural network classification model based on BiLSTM and CNN is proposed to recognize users service intentions.  ...  The model can fuse the temporal semantics and spatial semantics of the user descriptions.  ...  This work was supported in part by the National Natural Science Foundation of China under Grant 71571136, in part by the National Basic Research Program of China under Grant 2014CB340404, and in part by  ... 
doi:10.1088/1742-6596/1229/1/012054 fatcat:ouwphoquzncivkyeitqxcheptu

Active Monitoring of Adverse Drug Reactions with Neural Network Technology

Chang-Chun Gao, Tao Wu, Jing-Sheng Lin, Jia-Ling Zha
2017 Chinese Medical Journal  
Active Monitoring of Adverse Drug Reactions with Neural Network Technology  ...  the era of artificial neural network research.  ...  Experts need to check, track, and confirm the ADRs filtered by machine. After the artificial processing, a conclusion of ADRs can be drawn 4.  ... 
doi:10.4103/0366-6999.207468 pmid:28584215 pmcid:PMC5463482 fatcat:ojql5mlnavhi3i6cuktqhfmxdy

A Study of Various Speech Features and Classifiers used in Speaker Identification

Priyatosh Mishra, Pankaj Kumar Mishra
2016 International Journal of Engineering Research and  
Keywords-Linear Predictive Cepstral Coefficients (LPCC), Mel Frequency Cepstral Coefficients (MFCC), Gaussian Mixture Model ( GMM), Vector Quantization (VQ), Hidden Markov Model ( HMM), Artificial Neural  ...  Network (ANN) I.  ...  Artificial Neural Networks An Artificial Neural Network is mathematical model that tries to simulate the structure and functions of biological neural networks.  ... 
doi:10.17577/ijertv5is020637 fatcat:eu4gvuqqsbalxlbqxhngo5itae

Ayurvedic Plant Identification using Image Processing and Artificial Intelligence

Amey Sunil Deshmukh, Pushppavisha Mani Mudhaliar, Dr. Surabhi Thorat
2021 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
In this paper, a new technique to deployment problem is proposed based on the artificial bee colony (ABC) algorithm which is enhanced for the deployment of sensor networks to gain better performance by  ...  Wireless networks provide small sensing, machine and wireless networking nodes.  ...  Published : 10 Dec 2021 Keywords: ANN(Artificial Neural Network), KNN(k-nearest neighbors), PNN(Probablistic Neural Network),SVM(Support Vector Machine  ... 
doi:10.32628/cseit217655 fatcat:ho3coezsdjchpi3222ikrugljm

Automatic Code Summarization: A Systematic Literature Review [article]

Yuxiang Zhu, Minxue Pan
2019 arXiv   pre-print
By reading and analyzing relevant articles, we aim at obtaining a comprehensive understanding of the current status of automatic code summarization.  ...  By fully elaborating current approaches in the field, our work sheds light on future research directions of program comprehension and comment generation.  ...  The difference of timeframe is significant in the field of automatic code summarization, since the first application of artificial neural network to automatic code summarization was published by Iyer  ... 
arXiv:1909.04352v2 fatcat:xdxfdihcdfhbfnnilc2ofif4le

Segmentation of User Task Behavior by using Artificial Neural Network

Ruchika Tripathi, Pankaj Richhariya
2016 International Journal of Computer Applications  
Proposed work classifies the user query by combining query clustering boundary spread method with the neural network.  ...  Proposed scheme reduces execution time as well because of using trained neural network.  ...  assigning identification numbers to those keywords.  ... 
doi:10.5120/ijca2016912394 fatcat:5zmf24nyijfvdkjqg67bh2bg5y

Document Clustering using Learning from Examples

G. ThavasiRaja, R. Malmathanraj, M. Arun
2012 International Journal of Computer Applications  
Information filtering (IF) systems usually filter data items by correlating a set of terms representing the user's interest with similar sets of terms representing the data items.  ...  A new framework is described to classify large scale documents and retrieve the documents related to the user's query based on the application of trained artificial neural network (ANN) model.  ...  Information filtering (IF) is a research area that provides tools for filtering out irrelevant information.  ... 
doi:10.5120/4872-7299 fatcat:gsnr5anizrfy5ggulf3ugsrw7q

Development of an intelligent searcher

J.L.C. Medina, H.B. Gamboa
2005 2005 International Conference on Industrial Electronics and Control Applications  
This article presents a description of the design and development of an Intelligent Searcher (a System based on an Intelligent Agent ).  ...  In the second part, the implementation and general results are discussed. The analysis presented here covers the entire software development life cycle.  ...  Neural Networks An artificial neuronal network (ANN) is an attempt for simulating through computational procedures the behavior of part of the human brain .  ... 
doi:10.1109/icieca.2005.1644381 fatcat:tuecpbvmdfevpkkfugrtbdxq7u

A review of Deep learning Techniques for COVID-19 identification on Chest CT images [article]

Briskline Kiruba S, Petchiammal A, D. Murugan
2022 arXiv   pre-print
Automatic identification of COVID-19 is a challenge for health care officials.  ...  Relevant studies were collected by various databases such as Web of Science, Google Scholar, and PubMed.  ...  In this study, papers are selected by the keywords Artificial Intelligence, COVID-19, Convolutional Neural Network, CT-images, and Deep Learning.  ... 
arXiv:2208.00032v2 fatcat:lfv5p633evholjztvroykrayba

An Improved Automatic Image Annotation Approach using Convolutional Neural Network-Slantlet Transform

Myasar Mundher Adnan, Mohd Shafry Mohd Rahim, AR Khan, Tanzila Saba, Suliman Mohamed Fati, Saeed Ali Bahaj
2022 IEEE Access  
And they employed a deep learning convolutional neural network to build and improve image coding and annotation capabilities.  ...  The automatic feature extraction for automatic annotation was the emphasis of this paper.  ...  THE ARCHITECTURES OF THE CNN Convolutional neural networks (CNN) are artificial neural networks used to extract local features from data.  ... 
doi:10.1109/access.2022.3140861 fatcat:5ubshtj67fby7eawh2bbbwmjn4

Automatic Image Annotation via Combining Low-level Colour Feature with Features Learned from Convolutional Neural Networks

Yi Lin, Honggang Zhang
2018 NeuroQuantology  
In addition to using low-level colour features from original images, we extract features learned from convolutional neural networks (CNNs).  ...  Finally, when combining the two feature sets as inputs into the deep neural network-based AIA systems, we obtain the best performance in both cases.  ...  This paper The artificial neural network in such aspects as structure principle and function features is closer to the human brain.  ... 
doi:10.14704/nq.2018.16.6.1612 fatcat:f3hspon52bbefndeacycpoim6i

SPI: Automated Identification of Security Patches via Commits [article]

Yaqin Zhou, Jing Kai Siow, Chenyu Wang, Shangqing Liu, Yang Liu
2021 arXiv   pre-print
We devise a deep learning-based security patch identification system that consists of two neural networks: one commit-message neural network that utilizes pretrained word representations learned from our  ...  commits dataset; and one code-revision neural network that takes code before and after revision and learns the distinction on the statement level.  ...  Our work demonstrates that it is promising to apply deep neural networks to scale up patches identification via an automatic and evolutionary approach and improve the state of the art [77] in the industry  ... 
arXiv:2105.14565v2 fatcat:hlfmlekf5zcqtnsj5qugkza5du

A Study on Email Spam Filtering Techniques

V Christina, S Karpagavalli, G Suganya
2010 International Journal of Computer Applications  
Electronic mail is used daily by millions of people to communicate around the globe and is a mission-critical application for many businesses.  ...  The necessity of effective spam filters increases. In this paper, we presented our study on various problems associated with spam and spam filtering methods, techniques.  ...  Content based Spam Filtering Techniques -Neural Networks: The neural networks are quite famous to be well adapted for problems of classification.  ... 
doi:10.5120/1645-2213 fatcat:2szems4bhfaovlzodgjo6mqcw4

Applying the EFuNN Evolving Paradigm to the Recognition of Artefactual Beats in Continuous Seismocardiogram Recordings [chapter]

Mario Malcangi, Hao Quan, Emanuele Vaini, Prospero Lombardi, Marco Di Rienzo
2017 Communications in Computer and Information Science  
The SCG data collection and the work of MDR, EV and PL were supported by the Italian Space Agency through the ASI 2013-061-I.0 and ASI 2013-079-R.0 grants.  ...  Keywords: Seismocardiogram Á Evolving Fuzzy Neural Network Á Artfact identification Introduction The assessment of both the electrical and mechanical activity of the heart are essential for the full  ...  On this premise, we propose the use of the Evolving Fuzzy Neural Network (EFuNN) paradigm for the automatic artifact detection in the SCG signal.  ... 
doi:10.1007/978-3-319-65172-9_22 fatcat:rbk5shjicnfepgiagphcv3krua
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