All Outputs (10)

DeepClean: a robust deep learning approach for autonomous vehicle camera data privacy (2022)
Thesis
Adeboye, O. DeepClean: a robust deep learning approach for autonomous vehicle camera data privacy. (Thesis). University of Salford

Autonomous Vehicles (AVs) generate several forms of tracking data, such as geolocation, distance, and camera data. The utility of these data, especially camera data for computer vision projects, has contributed to the advancement of high-performance... Read More about DeepClean: a robust deep learning approach for autonomous vehicle camera data privacy.

A framework for dynamic heterogeneous information networks change discovery based on knowledge engineering and data mining methods (2021)
Thesis
Umer, S. A framework for dynamic heterogeneous information networks change discovery based on knowledge engineering and data mining methods. (Thesis). University of Salford

Information Networks are collections of data structures that are used to model interactions in social and living phenomena. They can be either homogeneous or heterogeneous and static or dynamic depending upon the type and nature of relations between... Read More about A framework for dynamic heterogeneous information networks change discovery based on knowledge engineering and data mining methods.

Towards forecasting and prediction of faults in electricity distribution network : a novel data mining & machine learning approach (2020)
Thesis
Silva, H. Towards forecasting and prediction of faults in electricity distribution network : a novel data mining & machine learning approach. (Thesis). University of Salford

The electricity supply system includes a large-scale power generation installation and a convoluted network of electrical circuits that work together to efficiently and reliably supply electricity to consumers. Faults in the electricity distribution... Read More about Towards forecasting and prediction of faults in electricity distribution network : a novel data mining & machine learning approach.

Analyzing frequent patterns in data streams using a dynamic compact stream pattern algorithm (2019)
Thesis
Oyewale, A. (in press). Analyzing frequent patterns in data streams using a dynamic compact stream pattern algorithm. (Thesis). University of Salford

As a result of modern technology and the advancement in communication, a large amount of data streams are continually generated from various online applications, devices and sources. Mining frequent patterns from these streams of data is now an impor... Read More about Analyzing frequent patterns in data streams using a dynamic compact stream pattern algorithm.

Natural Language Processing and Information Systems : 24th International Conference on applications of natural language to information systems, NLDB 2019, Salford, UK, June 26–28, 2019, proceedings (2019)
Book
24th International Conference on applications of natural language to information systems, NLDB 2019, Salford, UK, June 26–28, 2019, proceedings. Switzerland: Springer Nature Switzerland. https://doi.org/10.1007/978-3-030-23281-8

This book constitutes the refereed proceedings of the 24th International Conference on Applications of Natural Language to Information Systems, NLDB 2019, held in Salford, UK, in June 2019. The 21 full papers and 16 short papers were carefully re... Read More about Natural Language Processing and Information Systems : 24th International Conference on applications of natural language to information systems, NLDB 2019, Salford, UK, June 26–28, 2019, proceedings.

Optimisation techniques for finding connected components in large graphs using GraphX (2018)
Thesis
Turifi, M. (in press). Optimisation techniques for finding connected components in large graphs using GraphX. (Thesis). The University of Salford

The problem of finding connected components in undirected graphs has been well studied. It is an essential pre-processing step to many graph computations, and a fundamental task in graph analytics applications, such as social network analysis, web gr... Read More about Optimisation techniques for finding connected components in large graphs using GraphX.

Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings (2016)
Book
(2016). E. Metais, F. Meziane, M. Saraee, V. Sugumaran, S. Vadera, E. Métais, …S. Vadera (Eds.), Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings. Springer. https://doi.org/10.1007/978-3-319-41754-7

This volume of the lecture notes in computer science (LNCS) contains the papers presented at the 21st International Conference on application of Natural Language to Information Systems, held at MediacityUK, University of Salford on the 22-24 June 201... Read More about Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings.

Natural language processing and information systems : 18th international conference on applications of natural language to information systems, NLDB 2013, Salford, UK, June 2013; Proceedings (2013)
Book
(2013). E. Métais, F. Meziane, M. Saraee, & S. Vadera (Eds.), Natural language processing and information systems : 18th international conference on applications of natural language to information systems, NLDB 2013, Salford, UK, June 2013; Proceedings. Springer

This book constitutes the refereed proceedings of the 18th International Conference on Applications of Natural Language to Information Systems, held in Salford, UK, in June 2013. The 21 long papers, 15 short papers and 17 poster papers presented... Read More about Natural language processing and information systems : 18th international conference on applications of natural language to information systems, NLDB 2013, Salford, UK, June 2013; Proceedings.

Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques
Thesis
Shaukat, S. (in press). Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques. (Dissertation). University of Salford

Application of machine learning in the field of malware analysis is not a new concept, there have been lots of researches done on the classification of malware in android and windows environments. However, when it comes to malware analysis in the int... Read More about Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques.

Classifying advanced malware into families based on instruction link analysis
Thesis
Tabatabaei, S. (in press). Classifying advanced malware into families based on instruction link analysis. (Dissertation). University of Salford

With the ever-increasing growth of network resources, a great number of organizations are extremely dependent on the internet for operational activities as such, exposing their sensitive and confidential information to intrusion or invasion by sabote... Read More about Classifying advanced malware into families based on instruction link analysis.