The Resource TaskDo : A Daily Task Recommender System, by Nikhil Sai Santosh Gurram
TaskDo : A Daily Task Recommender System, by Nikhil Sai Santosh Gurram
Resource Information
The item TaskDo : A Daily Task Recommender System, by Nikhil Sai Santosh Gurram represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri-Kansas City Libraries.This item is available to borrow from all library branches.
Resource Information
The item TaskDo : A Daily Task Recommender System, by Nikhil Sai Santosh Gurram represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri-Kansas City Libraries.
This item is available to borrow from all library branches.
- Summary
- Time is a constant entity and an invaluable element for every living person on this planet. Even with all modern-day technologies being available, many individuals like working professionals, students, and house makers often find a lack of time and time management as problems for successful task accomplishment. Many people face challenges in allocating time for their day to day work and personal life activities. One of the key reasons for this failure in task accomplishment is inefficient planning strategies for day to day tasks. There are many task management and to-do-list applications which focus on registering, organizing, sharing, and visualizing tasks, but most of them do not advise on optimal task management and recommendations for better performance. This problem has driven us to contribute a task recommender system which suggests a specific type of tasks to users based on their history of tasks and various factors at that specific time. This system not only suggests a specific type of task for the user but also collects feedback from the user to make the recommender system learn on how to provide useful recommendations thus making the users time much productive. For this system, we have taken some factors into consideration such as Day of the week, Time of the day, Type of the task, Weather, Location and Task completion success percentage. We have designed a rank score algorithm by drilling down to relevant data and by calculating Phi -Correlation on Task completion success percentage. This algorithm is used to provide recommendations for users for optimal task performance
- Language
- eng
- Extent
- 1 online resource (27 pages)
- Note
-
- "A thesis in Computer Science."
- Advisor: Mohammad Amin Kuhail
- Vita
- Contents
-
- Introduction
- Background and related work
- TaskDo - A daily task recommender system
- Evaluation
- Conclusion and future work
- Label
- TaskDo : A Daily Task Recommender System
- Title
- TaskDo
- Title remainder
- A Daily Task Recommender System
- Statement of responsibility
- by Nikhil Sai Santosh Gurram
- Language
- eng
- Summary
- Time is a constant entity and an invaluable element for every living person on this planet. Even with all modern-day technologies being available, many individuals like working professionals, students, and house makers often find a lack of time and time management as problems for successful task accomplishment. Many people face challenges in allocating time for their day to day work and personal life activities. One of the key reasons for this failure in task accomplishment is inefficient planning strategies for day to day tasks. There are many task management and to-do-list applications which focus on registering, organizing, sharing, and visualizing tasks, but most of them do not advise on optimal task management and recommendations for better performance. This problem has driven us to contribute a task recommender system which suggests a specific type of tasks to users based on their history of tasks and various factors at that specific time. This system not only suggests a specific type of task for the user but also collects feedback from the user to make the recommender system learn on how to provide useful recommendations thus making the users time much productive. For this system, we have taken some factors into consideration such as Day of the week, Time of the day, Type of the task, Weather, Location and Task completion success percentage. We have designed a rank score algorithm by drilling down to relevant data and by calculating Phi -Correlation on Task completion success percentage. This algorithm is used to provide recommendations for users for optimal task performance
- Cataloging source
- UMK
- http://library.link/vocab/creatorName
- Gurram, Nikhil Sai Santosh
- Degree
- M.S.
- Dissertation note
- (School of Computing and Engineering).
- Dissertation year
- 2019.
- Granting institution
- University of Missouri-Kansas City,
- Illustrations
- illustrations
- Index
- no index present
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- theses
- http://library.link/vocab/relatedWorkOrContributorName
- Kuhail, Mohammad Amin
- http://library.link/vocab/subjectName
- Recommender systems (Information filtering)
- Label
- TaskDo : A Daily Task Recommender System, by Nikhil Sai Santosh Gurram
- Note
-
- "A thesis in Computer Science."
- Advisor: Mohammad Amin Kuhail
- Vita
- Antecedent source
- not applicable
- Bibliography note
- Includes bibliographical references (pages 25-26)
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- black and white
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- Background and related work -- TaskDo - A daily task recommender system -- Evaluation -- Conclusion and future work
- Control code
- 1156322138
- Dimensions
- unknown
- Extent
- 1 online resource (27 pages)
- File format
- one file format
- Form of item
- online
- Level of compression
- mixed
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations.
- Quality assurance targets
- not applicable
- Specific material designation
- remote
- System control number
- (OCoLC)1156322138
- System details
-
- The full text of the thesis is available as an Adobe Acrobat .pdf file; Adobe Acrobat Reader required to view the file
- Mode of access: World Wide Web
- Label
- TaskDo : A Daily Task Recommender System, by Nikhil Sai Santosh Gurram
- Note
-
- "A thesis in Computer Science."
- Advisor: Mohammad Amin Kuhail
- Vita
- Antecedent source
- not applicable
- Bibliography note
- Includes bibliographical references (pages 25-26)
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- black and white
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- Background and related work -- TaskDo - A daily task recommender system -- Evaluation -- Conclusion and future work
- Control code
- 1156322138
- Dimensions
- unknown
- Extent
- 1 online resource (27 pages)
- File format
- one file format
- Form of item
- online
- Level of compression
- mixed
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations.
- Quality assurance targets
- not applicable
- Specific material designation
- remote
- System control number
- (OCoLC)1156322138
- System details
-
- The full text of the thesis is available as an Adobe Acrobat .pdf file; Adobe Acrobat Reader required to view the file
- Mode of access: World Wide Web
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.umkc.edu/portal/TaskDo--A-Daily-Task-Recommender-System-by/V99WgD9egrQ/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.umkc.edu/portal/TaskDo--A-Daily-Task-Recommender-System-by/V99WgD9egrQ/">TaskDo : A Daily Task Recommender System, by Nikhil Sai Santosh Gurram</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.umkc.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.umkc.edu/">University of Missouri-Kansas City Libraries</a></span></span></span></span></div>