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Artificial intelligence / Information extraction / Applied mathematics / Sequence labeling / Parsing / Learning / Machine learning / Conditional random field / Theoretical computer science


Scholarly Document Information Extraction using Extensible Features for Efficient Higher Order Semi-CRFs Nguyen Viet Cuong, Muthu Kumar Chandrasekaran, Min-Yen Kan, Wee Sun Lee∗ Department of Computer Science, National
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Document Date: 2015-04-23 05:59:28


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File Size: 514,55 KB

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City

Knoxville / /

Company

CRF / CRFs / /

Country

United States / /

Currency

USD / /

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Facility

International Research Centre / National University of Singapore / /

IndustryTerm

Web lookup / Web-based citation parsing / digital library services / computing / Web Technologies / learning solutions / notable systems / /

Organization

Wee Sun Lee∗ Department of Computer Science / National University of Singapore / IDM Programme Office / Singapore National Research Foundation / International Research Centre / /

Person

Viviane Moreira / Philip S. Cho / Muthu Kumar Chandrasekaran / Minh-Thang Luong / Alan Souza / Nguyen Viet Cuong / Sunita Sarawagi / Wen Hua / Hai Leong Chieu / Wee Sun Lee / Andreas Hotho / Liangcai Gao / C. Lee Giles / Kurt D. Bollacker / Frank Puppe / Florian Lemmerich / Xixi Qi / Min Yen Kan / Thuy Dung Nguyen / Peter Kluegl / Isaac G. Councill / Ying Liu / Min-Yen Kan / William W. Cohen / Dat T. Huynh / Xiaofan Lin / Huy Hoang Nhat Do / Carlos Heuser / Steve Lawrence / Martin Toepfer / Zhi Tang / Nan Ye / /

Position

author / vp / editor / Problem Author / 1SCRF 2SCRF 3SCRF author / Reference string parsing Generic section labeling Author / author / institution and publication venue / /

ProvinceOrState

Tennessee / /

Technology

Viterbi algorithm / Web Technologies / 2.2 Inference Algorithms Inference algorithms / optical character recognition / PDF / computed using the Viterbi algorithm / /

URL

http /

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