A survey of temporal data mining
By Srivatsan Laxman, P. Shanti Sastry. 2006
375 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/86068dfacf4aafebce3eb552f2b09320d5252df3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Yingcai Wu
- Neil T. Spring
- Teh Ying Wah
- Ben Shneiderman
- Indrė Žliobaitė
- Catherine Plaisant
- Huamin Qu
- Kenyon Crowley
In Information Systems
- Diane Joyce Cook
- Neil T. Spring
- Parisa Rashidi
- Teh Ying Wah
- Ben Shneiderman
- Indrė Žliobaitė
- Catherine Plaisant
- Saeed Reza Aghabozorgi
In Signal Processing
- Diane Joyce Cook
- Indrė Žliobaitė
- Yingcai Wu
- Neil T. Spring
- Parisa Rashidi
- Teh Ying Wah
- Ben Shneiderman
- Catherine Plaisant
Citations in the corpus
- Visual Analysis of Topic Competition on Social Media (2013, background): “Time is often represented by the horizontal axis [21, 29], or spirals to highlight the periodical patterns [44].”
- EventAction (2019, background): “One popular research topic in temporal data mining is discovering frequently occurring sequential patterns, which can generate novel insights and drive decision making [36].”
- Time-series clustering - A decade review (2015, background): “There are some surveys and reviews that focus on comparative aspects of time-series clustering experiments [6,13–17] but none of them tend to be as comprehensive as we are in this review.”
- Learning under Concept Drift: an Overview (2010, background): “Temporal data mining [96] incorporates time dimension into data mining process.”
- Keeping the Resident in the Loop: Adapting the Smart Home to the User (2009, background): “[13] do model some temporal information by incorporating”