All Outputs (8)

Predicting road traffic accident severity using decision trees and time-series calendar heatmaps (2019)
Presentation / Conference
Silva, H., & Saraee, M. (2019, November). Predicting road traffic accident severity using decision trees and time-series calendar heatmaps. Presented at The 6th IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (2019 IEEE CSUDET), Penang, Malaysia

The European Commission estimates that around 135,000 people are seriously injured on Europe's roads each year. The road traffic injuries are a significant but neglected global general public health problem, needing rigorous attempts for effectiv... Read More about Predicting road traffic accident severity using decision trees and time-series calendar heatmaps.

Predictive modelling in mental health : a data science approach (2019)
Presentation / Conference
Saraee, M., Silva, H., & Saraee, M. (2019, November). Predictive modelling in mental health : a data science approach. Presented at 2019 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (IEEE CSUDET), Penang, Malaysia

In national and local level, understanding of factors associated with public health issues like mental health is paramount important. This framework evaluation aims to use the decision Tree technique to improve the degree of understanding of the ment... Read More about Predictive modelling in mental health : a data science 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.

Features in extractive supervised single-document summarization : case of Persian news (2019)
Journal Article
Rezaei, H., Moeinzadeh, S., Shahgholian, A., & Saraee, M. (2019). Features in extractive supervised single-document summarization : case of Persian news

Text summarization has been one of the most challenging areas of research in NLP. Much effort has been made to overcome this challenge by using either the abstractive or extractive methods. Extractive methods are more popular, due to their simplicity... Read More about Features in extractive supervised single-document summarization : case of Persian news.

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.

Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering (2019)
Presentation / Conference
Silva, H., & Saraee, M. (2019, June). Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering. Presented at 3RD IEEE Industrial and Commercial Power System Europe (I&CPS), Genoa, Italy

In-depth understanding of a fault cause in electricity distribution network has always been of paramount importance to Distributed Network Operators (DNO) for a reliable power supply. Faults in the network have direct effect on its stability, availab... Read More about Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering.

Analyzing data streams using a dynamic compact stream pattern algorithm (2019)
Journal Article
Oyewale, A., Hughes, C., & Saraee, M. (2019). Analyzing data streams using a dynamic compact stream pattern algorithm

A growing number of applications that generate massive streams of data need intelligent data processing and online analysis. Data & Knowledge Engineering (DKE) has been known to stimulate the exchange of ideas and interaction between these two rela... Read More about Analyzing data streams using a dynamic compact stream pattern algorithm.

Diabetics’ self-management systems : drawbacks and potential enhancements (2019)
Presentation / Conference
Darwish, F., Silva, H., & Saraee, M. (2019, March). Diabetics’ self-management systems : drawbacks and potential enhancements. Presented at 2nd International Conference on Geoinformatics and Data Analysis (ICGDA), Prague, Czech Republic

Diabetes is a pandemic that is growing globally, and by the year 2030 it is expected to effect three people every 10 minutes. In the UK, it is estimated that by 2025, 5 million people will have diabetes. Diabetes is currently costing the British Nati... Read More about Diabetics’ self-management systems : drawbacks and potential enhancements.