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- research-articleJuly 2024
A study into text sentiment analysis model based on deep learning
International Journal of Information and Communication Technology (IJICT), Volume 24, Issue 8Pages 64–75https://doi.org/10.1504/ijict.2024.139869Deep learning models for text sentiment analysis are employed to analyse the human emotions conveyed by natural language representation in text data. The BERT-ABiLSTM model, a large-scale pre-trained model, is utilised for text data by transforming text ...
- short-paperJanuary 2023
Explicit or Implicit? On Feature Engineering for ML-based Variability-intensive Systems
VaMoS '23: Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive SystemsPages 91–93https://doi.org/10.1145/3571788.3571804Software variability engineering benefits from Machine Learning (ML) to learn e.g., variability-aware performance models, explore variants of interest and minimize their energy impact. As the number of applications of combining variability with ML ...
- research-articleMay 2021
Encoding feature models using mainstream JSON technologies
ACMSE '21: Proceedings of the 2021 ACM Southeast ConferencePages 146–153https://doi.org/10.1145/3409334.3452048Feature modeling is a process for identifying the common and variable parts of a software product line and recording them in a tree-structured feature model. However, feature models can be difficult for mainstream developers to specify and maintain ...
- research-articleJanuary 2021
Research on prediction method on RUL of motor of CNC machine based on deep learning
International Journal of Computing Science and Mathematics (IJCSM), Volume 14, Issue 4Pages 338–346https://doi.org/10.1504/ijcsm.2021.120689To solve the problem of high fault frequency and sudden occurrence of the motor of computer numerical control (CNC) machine tool, the paper proposes a deep learning remaining useful life (RUL) prediction model based on DFS-LSTM. Through collecting the ...
- research-articleMay 2021
Feature Based Deep Retinex for Low-Light Image Enhancement
ICAIP '20: Proceedings of the 4th International Conference on Advances in Image ProcessingPages 66–71https://doi.org/10.1145/3441250.3441270Low-light image processing is a common issue in industry, media and other practical application fields. Enhancing image brightness or contrast directly may bring accompanying noise and color cast. The proposed method is a feature based deep F-Retinex-...
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- research-articleOctober 2020
Feature-oriented defect prediction
SPLC '20: Proceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume AArticle No.: 21, Pages 1–12https://doi.org/10.1145/3382025.3414960Software errors are a major nuisance in software development and can lead not only to reputation damages, but also to considerable financial losses for companies. Therefore, numerous techniques for predicting software defects, largely based on machine ...
- research-articleJuly 2020
Comparison of Different Dichotomous Classification Algorithms
Pattern Recognition and Image Analysis (SPPRIA), Volume 30, Issue 3Pages 303–314https://doi.org/10.1134/S105466182003030XAbstractExperimental investigations of various dichotomous classification algorithms are carried out. Dichotomous classification, or Error-Correcting Output Codes (ECOCs) classification, is based on the construction of a binary code matrix. The rows of ...
- research-articleJanuary 2020
Collaborative filtering recommendation algorithm based on deep neural network fusion
International Journal of Sensor Networks (IJSNET), Volume 34, Issue 2Pages 71–80https://doi.org/10.1504/ijsnet.2020.110460In order to accurately obtain potential features and improve the recommendation performance of the collaborative filtering algorithm, this paper puts forward a collaborative filtering recommendation algorithm based on deep neural network fusion (CF-DNNF)...
- short-paperSeptember 2019
Facilitating the Development of Software Product Lines in Small and Medium-Sized Enterprises
SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference - Volume BPages 230–237https://doi.org/10.1145/3307630.3342703Software Product Lines (SPLs) are Software Engineering methodologies that manage the development and evolution of families of product variants. They aim at handling the commonality and variability of these products. SPLs reduce the development cost, ...
- research-articleJuly 2019
Effective and Efficient Data Cleaning for Entity Matching
HILDA '19: Proceedings of the Workshop on Human-In-the-Loop Data AnalyticsArticle No.: 2, Pages 1–7https://doi.org/10.1145/3328519.3329127As a key data-integration step, entity matching (EM) identifies tuples referring to the same real-world entities in disparate data sources. In many cases, the EM quality can be improved by repairing incorrect values in the data; at the same time, it is ...
- research-articleJune 2019
Comparison of video shot detection methods using higher order local descriptor
ICAICR '19: Proceedings of the Third International Conference on Advanced Informatics for Computing ResearchArticle No.: 13, Pages 1–5https://doi.org/10.1145/3339311.3339324Video Shot Detection plays a vital role in the analysis of the contents in Video. The algorithms and methodologies learnt from Video Shot Detection has a wide range of applications starting from Video Browsing, Content-based Video Retrieval and Storage, ...
- research-articleApril 2019Best Paper
Hearthstone AI: Oops to Well Played
ACMSE '19: Proceedings of the 2019 ACM Southeast ConferencePages 149–154https://doi.org/10.1145/3299815.3314461Online digital collectible card games have seen a massive rise in popularity recently, none more so than Hearthstone: Heroes of Warcraft. While the game is mainly player vs. player focused, a need for competent game playing AI has arisen as well. This ...
- research-articleFebruary 2019
A Survey of Feature Selection for Vulnerability Prediction Using Feature-based Machine Learning
ICMLC '19: Proceedings of the 2019 11th International Conference on Machine Learning and ComputingPages 36–42https://doi.org/10.1145/3318299.3318345This paper summarized the basic process of software vulnerability prediction using feature-based machine learning for the first time. In addition to sorting out the related types and basis of vulnerability features definition, the advantages and ...
- articleOctober 2018
On Some Transformations of Features in Machine Learning in Medicine
Pattern Recognition and Image Analysis (SPPRIA), Volume 28, Issue 4Pages 720–736https://doi.org/10.1134/S1054661818040302A new view is given to supervised classification problems by precedents on the basis of logical approaches and the possibility of their application in medicine. The basic logical and logical statistical models of classification (basic definitions, ...
- extended-abstractSeptember 2018
Variability extraction and modeling for product variants
SPLC '18: Proceedings of the 22nd International Systems and Software Product Line Conference - Volume 1Page 250https://doi.org/10.1145/3233027.3236396Fast changing hardware and software technologies in addition to larger and more specialized customer bases demand software tailored to meet very diverse requirements. Software development approaches that aim at capturing this diversity on a single ...
- research-articleSeptember 2018
Feature-based reuse in the ERP domain: an industrial case study
SPLC '18: Proceedings of the 22nd International Systems and Software Product Line Conference - Volume 1Pages 170–178https://doi.org/10.1145/3233027.3233051Enterprise Resource Planning (ERP) system vendors need to customize their products according to the domain-specific requirements of their customers. Systematic reuse of features and related ERP product customizations would improve software quality and ...
- research-articleMay 2018
What's inside my app?: understanding feature redundancy in mobile apps
ICPC '18: Proceedings of the 26th Conference on Program ComprehensionPages 266–276https://doi.org/10.1145/3196321.3196329As the number of mobile apps increases rapidly, many users may install dozens of, or even hundreds of, apps on a single smartphone. However, many apps on the same phone may contain similar or even the same feature, resulting in feature redundancy. For ...
- research-articleJanuary 2017
Performance analysis of GA-based iterative and non-iterative learning approaches for medical domain data sets
Intelligent Decision Technologies (INTDTEC), Volume 11, Issue 3Pages 321–334https://doi.org/10.3233/IDT-170298Research in disease diagnosis is a challenging task due to inconsistent, class imbalance, conflicting and high dimensionality nature of medical data sets. The excellent features of each such data set play an important role in improving performance ...
- articleSeptember 2016
FFSc: a novel measure for low-rate and high-rate DDoS attack detection using multivariate data analysis
Security and Communication Networks (SACN), Volume 9, Issue 13Pages 2032–2041https://doi.org/10.1002/sec.1460A Distributed Denial of Service DDoS attack is a major security threat for networks and Internet services. Attackers can generate attack traffic similar to normal network traffic using sophisticated attacking tools. In such a situation, many intrusion ...
- articleJuly 2016
Methods for discrete analysis of medical data on the basis of recognition theory and some of their applications
- Yu. I. Zhuravlev,
- G. I. Nazarenko,
- A. P. Vinogradov,
- A. A. Dokukin,
- N. N. Katerinochkina,
- E. B. Kleimenova,
- M. V. Konstantinova,
- V. V. Ryazanov,
- O. V. Sen'ko,
- A. M. Cherkashov
Pattern Recognition and Image Analysis (SPPRIA), Volume 26, Issue 3Pages 643–664https://doi.org/10.1134/S105466181603024XMethods for the analysis of medical data and the results of their application to the treatment of a number of socially important diseases in important medical areas (cardiology, neurology, surgery, and oncology) are considered. The precedent approach is ...