NDLI: A ranking-based approach for hierarchical classification

Content Provider	IEEE Xplore Digital Library
Author	Naik, A. Rangwala, H.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA (Naik, A.; Rangwala, H.)
Abstract	With the growth of information organized in hierarchical databases, it is essential to develop automated approaches for classifying data instances (e.g., documents, proteins and images) into hierarchies. Several classification approaches have been developed that exploit the hierarchical structure prevalent within these underlying databases. One commonly used approach is to train local one-versus-rest classifiers for each of the nodes within the hierarchy and then make a prediction using a combination of these several trained classifiers. In this paper, we develop a hierarchical classification approach that utilizes a rank-based loss function to differentiate between the examples from different nodes across the hierarchies. The intuition behind our approach is that it allows for the training examples to have an ordering based on their class membership within the hierarchy. We also add regularization constraints that force the learned weight vectors associated with the parent and children nodes within the hierarchy to be similar to each other. To further improve the model performance, we extend our formulation to include a hierarchy based cost-sensitive loss during training. To ensure the scalability of our approach to datasets with large number of classes, instances and feature space, we implemented a distributed map-reduce based algorithm for training the different per-node classifiers. Our empirical results on a diverse set of image and text hierarchical databases shows an improved performance with the use of rank-based models in comparison to other baseline approaches.
Sponsorship	IEEE Comput. Intell. Soc.
Starting Page	1
Ending Page	10
File Size	679675
Page Count	10
File Format	PDF
ISBN	9781467382724
DOI	10.1109/DSAA.2015.7344898
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-19
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Support vector machines Databases Computational modeling Fasteners Mathematical model Optimization
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
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