Grant: Engage Grants Program
Université de Moncton
$25,000.00
Deep learning and collaborative filtering for project based team recommendation
FY 2018-19
Summary
Time management and timesheets software has been around in various industries for decades. Many industries*have adopted automated time tracking systems today. It is obvious that timesheets are important to any*business. However, important challenging problems remain. Among them: late and missing timesheets,*illegible and inaccurate timesheets, and manual entry errors. Additionally, timesheets are more about measuring*inputs than with improving the quality of output. To tackle these challenges and unleash the full potential of*creative talents for higher quality output, we want to develop an innovative way toward the use of timesheets*data for better teams building and project collaboration using Artificial Intelligence (AI). Our industrial partner*Dovico has been developing time management software for 25 years; they have seen the evolution of*timesheets over the years and see today a huge opportunity to develop a more intelligent system based on the*use of machine learning techniques.*The objective of this project is to build a machine-learning algorithm that can learn from available data on how*to assign team members to projects based on their work behavior and team members' interaction.
Program
Engage Grants Program
Recipient
Location
New Brunswick, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
530741-2018
Name nom
Akhloufi, Moulay
Department département
Siège social
Organization id
73
Institution établissement
Université de Moncton
Province en
New Brunswick
Province fr
Nouveau-Brunswick
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
25000
Program id
EGP
Program name en
Engage Grants Program
Program name fr
Programme de subventions d'engagement partenariat
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1551
Committee name en
Atlantic Internal Decision Committee
Committee name fr
Comité de décision interne pour l'Atlantique
Area of application code
801
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer software
Area of application fr
Logiciel
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Partie
1
Nb partie
1
Application title
Deep learning and collaborative filtering for project based team recommendation
Keyword
NSERC
Application summary
Time management and timesheets software has been around in various industries for decades. Many industries*have adopted automated time tracking systems today. It is obvious that timesheets are important to any*business. However, important challenging problems remain. Among them: late and missing timesheets,*illegible and inaccurate timesheets, and manual entry errors. Additionally, timesheets are more about measuring*inputs than with improving the quality of output. To tackle these challenges and unleash the full potential of*creative talents for higher quality output, we want to develop an innovative way toward the use of timesheets*data for better teams building and project collaboration using Artificial Intelligence (AI). Our industrial partner*Dovico has been developing time management software for 25 years; they have seen the evolution of*timesheets over the years and see today a huge opportunity to develop a more intelligent system based on the*use of machine learning techniques.*The objective of this project is to build a machine-learning algorithm that can learn from available data on how*to assign team members to projects based on their work behavior and team members' interaction.
