NDLI: Personalization without user interruption: boosting activity recognition in new subjects using unlabeled data

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Personalization without user interruption: boosting activity recognition in new subjects using unlabeled data

Content Provider	ACM Digital Library
Author	Ghasemzadeh, Hassan Fallahzadeh, Ramin
Abstract	Activity recognition systems are widely used in monitoring physical and physiological conditions as well as observing the short/long term behavioral patterns for the purpose of improving the health and wellbeing of the users. The major obstacle in widespread use of these systems is the need for collecting labeled data to train the activity recognition model. While a personalized model outperforms a user-independent model, collecting labels from every single user is burdensome and in some cases impractical. In this paper, we propose an uninformed cross-subject transfer learning algorithm that leverages the cross-user similarities by constructing a network-based feature-level representation of the data in source and target users and perform a best effort community detection to extract the core observations in target data. Our algorithm uses a heuristic classifier-based mapping to assign activity labels to the core observations. Finally, the output of labeling is conditionally fused with the prediction of the source-model to develop a boosted and personalized activity recognition algorithm. Our analysis on real-world data demonstrates the superiority of our approach. Our algorithm achieves over 87% accuracy on average which is 7% higher than the state-of-the art approach.
Starting Page	293
Ending Page	302
Page Count	10
File Format	PDF
ISBN	9781450349659
DOI	10.1145/3055004.3055015
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-04-18
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Uninformed transfer learning Cross-subject boosting Activity recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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