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Managing and Mining Sensor Data
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“For all three tasks data has been addressed both in an online and offline manner, with more alarm related tasks being naturally used in the context of online and continuous monitoring [1].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [1]
In the citing paper
“According to [1,19], most healthcare systems are dealing with the following issues: (1) data acquisition using the adequate sensor set; (2) transmission of data from subject to clinician; (3) integration of data with other descriptive data; and (4) data storage.”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [1]
In the citing paper
“Preprocessing in the healthcare domain involves (1) filter unusual data to remove artifacts and (2) remove high frequency noise [1,13].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [1]
In the citing paper
“The main challenges of the preprocessing phase in healthcare systems are addressed in [1] which includes data formatting, data normalization, and data synchronization.”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [1]
In the citing paper
“This means that in order to make sense of the data, appropriate data processing techniques are essential [1].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [1]
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Metadata
- Authors
- Aggarwal, C. C.
- Affiliations
- IBM (United States) (US)
- Corresponding author
- Charų C. Aggarwal
- ORCID
- Charų C. Aggarwal
- Venue
- Springer eBooks
- Publisher
- Springer US
- Published
- 2013
- OpenAlex
- W204230938
- Cited by
- 294
- References
- 0
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 9 · 2023: 13 · 2022: 12 · 2021: 21 · 2020: 25 · 2019: 28 · 2018: 42 · 2017: 30 · 2016: 24 · 2015: 34 · 2014: 34 · 2013: 8
- FWCI
- 21.52
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer eBooks (publishedVersion)
- Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Sensor Networks for Data Analysis
- Physical Sciences › Computer Science › Computer Networks and Communications › Energy Efficient Wireless Sensor Networks
- Physical Sciences › Computer Science › Information Systems › Advanced Database Systems and Queries
- Keywords
- sensor data management, sensor data mining, sensor networks, sensor data acquisition, low-cost sensors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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