JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2016, Vol. 51 ›› Issue (9): 11-17.doi: 10.6040/j.issn.1671-9352.1.2015.C05

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Information retrieval: the final direction of human language technology research in DARPA

CAO Rong, HUANG Jin-zhu, YI Mian-zhu   

  1. Language Engineering Department, PLA University of Foreign Language, Luoyang 471003, Henan, China
  • Received:2015-11-14 Online:2016-09-20 Published:2016-09-23

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Abstract: In order to procure the relevant research and application of human language technology in American defense field, the design ideas, progress and goal of DARPA since its coming into being is combed comprehensively and systematically. The focus of DARPA covered speech recognition, machine translation, information retrieval, language resource construction, language technology evaluation and system integration, etc. Judged from the distribution of research fields, expected goals and application ideas, the ultimate goal of DARPA human language technology research is highly-efficient, highly-adapted, highly-intelligent IR technology, which is applied to expand the scope of military operations, downsize operators and lift operation speed. Meanwhile, DARPAs innovation and military requirement-driven practice are worth learning.

Key words: human language technology, national defense technology, information retrieval, DARPA

CLC Number: 

  • TP391.1
[1] 黄晓庆, 周宇煜, 张为民, 等. 达帕的启示[M]. 北京: 科学出版社, 2012: 3.
[2] 刘纪平. 多重演化神经网络在语音识别中的应用[D].武汉:武汉大学,2011: 2. LIU Jiping. Multiple evolutionary neural networks in speech recognition [D].Wuhan: Wuhan University, 2011: 2.
[3] STANLEY F C, BRIAN K, LIDIA M, et al. Advances in speech transcription at IBM under the DARPA EARS program[J]. Transactions on Audio, Speech, and Language Processing, 2006, 14:1596-1608.
[4] TIMIT.TIMIT [EB/OL].(2003-05-10)[2014-12-23]. https://catalog.ldc.upenn.edu.docs.LDC93SI/readme.txt.
[5] MANI I, HOUSE D, KLEIN G, et al. The TIPSTER SUMMAC text summarization evaluation: final report [J].Conference on European Chapter of the Association for Computational Linguistics, 1999, 4(1):82-83.
[6] DARPA.Memex(Domain-Specific Search)[EB/OL].(2014-02-09)[2015-06-07]. http://www.darpa.mil/NewsEvents/Releases/2014/02/09.aspx.
[7] 孙斌. 信息提取技术概述(上)[J]. 术语标准化与信息技术, 2002(3): 28-32. SUN Bin. A Summarization of information extraction(1)[J]. Terminology Standardization & Information Technology, 2002(3): 28-32.
[8] 陆铭. WEB2.0网络热点发现与个性化检索研究[D]. 合肥:中国科学技术大学, 2012. LU Ming. Research on network hotspot detection in Web 2.0 and personalized information retrieval[D]. Hefei:University of Science and Technology of China, 2012.
[9] 赵丹群. 浅析TREC平台的评测项目机制[J]. 情报理论与实践, 2014,37(10): 121-124,144. ZHAO Danqun. An elementary analysis of tracks structure of TREC platform [J]. Information Studies:Theory & Application, 2014, 37(10): 121-124+144.
[10] DUC. Introduction [EB/OL].(2010-11-17)[2014-12-23]. http://duc.nist.gov/.
[11] 刘德喜. 基于基本要素的多文档自动文摘研究[D]. 武汉:武汉大学, 2007. LIU Dexi. Multi-document summarization based on basic element[D]. Wuhan: Wuhan University, 2007.
[12] DARPA.DARPA initiates overarching language translation research publishes broad agency announcement for broad operational language translation(BOLT)program [EB/OL].(2011-04-19)[2014-12-23].http://www.darpa.mil/NewsEvents/Releases/2011/2011/04/19-DARPA-initiates-overarching-language-translation-research-Publishes-Broad-Agency-Announcement-for-Broad-Operational-Language-Translation-program.aspx.
[13] DARPA.Broad Operational language translation(BOLT)[EB/OL].(2011-04-19)[2014-12-23]. http://www.darpa.mil/Our-Work/I2O/Programs/Broad-Operational-Language-Translation-%28BO-LT%29.aspx.
[14] DARPA. DARPA-BAA-12-47: deep exploration and filtering of text(DEFT)[EB/OL].(2012-06-07)[2014-12-23]. https://www.fbo.gov/index?s=opportunity&mode=form&tab=core&id=1fc65bccd0-aa08abdff35bffc1ce8867&-cview=0.
[15] DARPA. Deep exploration and filtering of text(DEFT)[EB/OL].(2012-06-07)[2014-12-23]. http://www.darpa.mil/Our-Work/I2O/Programs/Deep-Exploration-and-Filtering-of-Text-(DEFT).aspx.
[16] DARPA. Can automated deep natural-language analysis unlock the power of inference? [EB/OL].(2012-05-03)[2014-12-23]. http://www.darpa.mil/NewsEvents/Releases/2012/05/03a.aspx.
[17] DORR B. Deep exploration and filtering of text(DEFT)[EB/OL].(2012-03-18)[2014-12-23]. https://www.fbo.gov/utils/view?id=9645b2e015a72-8609daff66561339622 DARPA-BAA-12-47-(DEFT).pdf.
[18] BOYAN O. Low resource lnguages for emergent Incidents[EB/OL].(2014-11-15)[2015-06-14]. https://www.fbo.gov/utils/view?id=d1339e87c15cb9e20-c97676d1e717752 DARPA-BAA-15-04-LORELEI.pdf.
[19] 贾珍珍,曾华锋,刘戟锋. 美国颠覆性军事技术的预研模式、管理与文化——以美国国防高级研究计划局(DARPA)为例[J]. 自然辩证法研究,2016(1):41-45. JIA Zhenzhen, ZENG Huafeng, LIU Jifeng. The pre-study mode, management and culture of disruptive military technologies: with the defense advanced research projects agency as a case[J]. Studies in Dialectics of Nature, 2016(1): 41-45.
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