NDLI: Natural language processing based interpretation of skewed graphs

Content Provider	IEEE Xplore Digital Library
Author	Mahmood, A. Qazi, K. Bajwa, I.S. Naeem, M.A.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci., Auckland Univ. of Technol., Auckland, New Zealand (Naeem, M.A.) \|\| Dept. of Comput. Sci. & IT, Islamia Univ. Bahawalpur, Bahawalpur, Pakistan (Mahmood, A.; Qazi, K.; Bajwa, I.S.)
Abstract	Different graphical tools such as pie charts, line charts, bar charts, scatter diagram, histogram etc. are used for data representation in statistics. Textual information along with these graphical tools plays vital role in the analysis of quantitative data. Multimodal documents use skewed graphics as a significant tool for the representation of visual information. It is frequently experiential that the communicative objectives of the skewed graphics are not confined by credentials accompanying text. To distinguish the symbolized information using skewed graphics is assertive job for greenhorn readers. An approach to mechanize the progression of graph classification and information withdrawal is offered in this paper. This study spotlights on the skewed graphics that are vital type of area charts used for probability distribution and testing of hypothesis process. To begin with, we have classified the area charts into diverse classes and then designed structural design for graph image classification and information extraction from every class of area chart. The extorted information is represented in the structure of natural language abstract using pattern based approach.
Starting Page	2700
Ending Page	2704
File Size	608138
Page Count	5
File Format	PDF
ISBN	9781479930784
e-ISBN	9781479930807
DOI	10.1109/ICACCI.2014.6968323
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-24
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Graphics Image recognition Text recognition Area graph classification and recognition Natural languages Optical character recognition Skewed graphics Feature extraction Natural language processing Optical character recognition software Data mining Text detection and withdrawal
Content Type	Text
Resource Type	Article

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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
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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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