TY - GEN
T1 - TiVEx
T2 - 20th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2023
AU - Helal, Heba
AU - Sharaf, Mohamed A.
AU - Masud, Mohammad M.
AU - Chrysanthis, Panos K.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - To facilitate fast-visual data analysis, there is a need for recommending top-k views with "interesting"insights automatically. However, working with high-dimensional time series data makes the process of view recommendations difficult. The primary obstacle lies in finding an automatic way to generate views with less processing time (efficiency) while still closely aligning with the ground truth (effectiveness). In this paper, we propose TiVEx (Time Series Visual Exploration), a technique to address this challenge. TiVEx aims to achieve a balance between efficiency and effectiveness in generating view recommendations. Through extensive experiments, we demonstrate significant cost savings achieved by TiVEx, indicating its efficiency. Furthermore, our analysis delves into the exploration of striking the right balance between efficiency and effectiveness.
AB - To facilitate fast-visual data analysis, there is a need for recommending top-k views with "interesting"insights automatically. However, working with high-dimensional time series data makes the process of view recommendations difficult. The primary obstacle lies in finding an automatic way to generate views with less processing time (efficiency) while still closely aligning with the ground truth (effectiveness). In this paper, we propose TiVEx (Time Series Visual Exploration), a technique to address this challenge. TiVEx aims to achieve a balance between efficiency and effectiveness in generating view recommendations. Through extensive experiments, we demonstrate significant cost savings achieved by TiVEx, indicating its efficiency. Furthermore, our analysis delves into the exploration of striking the right balance between efficiency and effectiveness.
KW - Optimization
KW - Recommendation
KW - Time series data
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=85190133748&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85190133748&partnerID=8YFLogxK
U2 - 10.1109/AICCSA59173.2023.10479252
DO - 10.1109/AICCSA59173.2023.10479252
M3 - Conference contribution
AN - SCOPUS:85190133748
T3 - Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
BT - 2023 20th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2023 - Proceedings
PB - IEEE Computer Society
Y2 - 4 December 2023 through 7 December 2023
ER -