NDLI: Bilingual sentence matching using Kernel CCA

Content Provider	IEEE Xplore Digital Library
Author	Tripathi, A. Klami, A. Virpioja, S.
Copyright Year	2010
Description	Author affiliation: University of Helsinki, Department of Computer Science, P.O.Box 68, 00014 UH, Finland (Tripathi, A.) \|\| Aalto University School of Science and Technology, Department of Information and Computer Science, P.O.Box 15400, FI-00076, Finland (Klami, A.; Virpioja, S.)
Abstract	The problem of matching samples between two data sets is a fundamental task in unsupervised learning. In this paper we propose an algorithm based on statistical dependency between the data sets to solve the matching problem in a general case when samples in both data sets have different feature representations. As a concrete example, we consider the task of sentence-level alignment of parallel corpus based on monolingual data. Multilingual text collections with sentence-level alignment are required by statistical machine translation methods. We show how statistical dependencies between feature representations of partially aligned (e.g., paragraph-level alignment) corpora can be used to learn sentence-level alignment in a data-driven way. Our novel matching algorithm based on Kernel Canonical Correlation Analysis (KCCA) outperforms an earlier algorithm using linear CCA.
Starting Page	130
Ending Page	135
File Size	145737
Page Count	6
File Format	PDF
ISBN	9781424478750
ISSN	15512541
e-ISBN	9781424478774
e-ISBN	9781424478767
DOI	10.1109/MLSP.2010.5589249
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-29
Publisher Place	Finland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Accuracy Correlation Semantics Iterative methods Convergence Cost function
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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