NDLI: Confabulation based sentence completion for machine reading

Content Provider	IEEE Xplore Digital Library
Author	Qinru Qiu Qing Wu Burns, D.J. Moore, M.J. Pino, R.E. Bishop, M. Linderman, R.W.
Copyright Year	2011
Description	Author affiliation: Air Force Research Laboratory, Information Directorate, RITC, 525 Brooks Road, Rome, NY 13441, USA (Qing Wu; Burns, D.J.; Pino, R.E.; Bishop, M.; Linderman, R.W.) \|\| ITT Advanced Engineering & Sciences, 775 Daedalian Drive, Rome, NY 13441, USA (Moore, M.J.) \|\| Dept. of Electrical & Computer Engineering, State University of New York at Binghamton, Binghamton, NY 13850, USA (Qinru Qiu)
Abstract	Sentence completion and prediction refers to the capability of filling missing words in any incomplete sentences. It is one of the keys to reading comprehension, thus making sentence completion an indispensible component of machine reading. Cogent confabulation is a bio-inspired computational model that mimics the human information processing. The building of confabulation knowledge base uses an unsupervised machine learning algorithm that extracts the relations between objects at the symbolic level. In this work, we propose performance improved training and recall algorithms that apply the cogent confabulation model to solve the sentence completion problem. Our training algorithm adopts a two-level hash table, which significantly improves the training speed, so that a large knowledge base can be built at relatively low computation cost. The proposed recall function fills missing words based on the sentence context. Experimental results show that our software can complete trained sentences with 100% accuracy. It also gives semantically correct answers to more than two thirds of the testing sentences that have not been trained before.
Starting Page	1
Ending Page	8
File Size	366852
Page Count	8
File Format	PDF
ISBN	9781424498901
e-ISBN	9781424498918
DOI	10.1109/CCMB.2011.5952109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-11
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Shape Computational modeling Knowledge based systems Neurons Merging Machine reading Cogent confabulation Complexity theory Hash table Sentence completion Unsupervised learning
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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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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