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ڶȫ֪ʶͼֻὫ20141017人

     ֪ʶͼףKnowledge Graphǵǰѧҵоȵ㡣֪ʶͼ׵ĹϢϢҪļֵΪȻԴרѧߵѧ塪йϢѧᣨCIPSǰѧֻ֮һλ齫ʮȫѧͬһصٰ죬񡢽ͨϸϢ鿴վеıעᲿ֡

    Ҫ

    ʱ䣺2014101614:00

    ٿʱ䣺20141017գһ죩

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ʮȫѧѧ(CCL-2014)20141018ա19人

     "ʮȫѧѧ"The Thirteenth China National Conferenceon Computational Linguistics,CCL201420141018ա19ڻʦѧСΪȻԴרѧߵ֯йϢѧᣨCIPS콢飬ȫѧ1991꿪ʼÿٰһΣ2013꿪ʼÿٰһΡCCLйڸԵļ㴦Ϊѧµѧͼɹṩ˹㷺Ľƽ̨

    Ҫ

    ʱ䣺201410178:00

    ٿʱ䣺2014101819գ죩

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CIPS-SIGHANĴԴʻ飨CLP-2014)20141020ա21人

     2014ĴԴʻ飨CLP-2014йϢѧᣨCIPS͹ʼѧЭĴרҵȤ飨SIGHAN֯׽ĴԴʻ飨CLP-201023ʼѧᣨCOLING-2010ͬڱٰ졣ڶĴԴʻ飨CLP201220121220-21йѧСCLP201420141020-21йʦѧС

     ĴԴʻ飨CLP-2014ּΪĴȫоԱṩһչʾоɹѧ˼롢̽о·ƶоչƽ̨CLP-2014ٰһ⾺ķִʡƴд顢ľ䷨Գȡйش˴ι⾺ϸϢμλ齫ʮȫѧͬһصٰ죬񡢽ͨϸϢ鿴վġConference venue

    Ҫ

    ʱ䣺201410198:00

    ٿʱ䣺2014102021գ죩

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ȫýᣨSMP-2014)2014111ա2ڱ

     ȫýᣨSMP2014111-2ڱѧٿйϢѧᣨCIPSý崦רί()ٰ졣ȫý崦ÿٰһΡSMPרעý崦ΪĿѧо빤̿Ϊý崦µѧо뼼չʾṩ˹㷺Ľƽ̨

    Ҫ

    ʱ䣺20141030 9:00-20:00

    ٿʱ䣺2014111-2գ죩

    οվ

ʮȫֻᣨCWMT-2014)2014114ա6ڰž

     ʮȫֻ(CWMT 2014)20141146ڰŴѧСֻ2005пԺԶŴѧٿһпԺҵѧпԺԶϾѧпԺŴѧѧԼѧɹٿ˾Ž졣й֯λ⣨20072008200920112013һοԴϵͳģ鿪2006ս֣20102012Щƶҹ뼼оͿ˻ԶӰ졣ˣCWMTѾΪҹȻԴľӰѧ

    CWMT 2014ּΪͬṩһƽ̨ǿͬеѧټ·רѧԻ۷Ӧüɹؼ֣Ϊٽйҵķչ𵽻ƶáбλר⽲߻ֻ̽ȵо۵㣬ר̳㼯רҽʾǰصͼỹ˹֪רѧص档⣬ڼ佫ѡѧģ䷢֤ͽרΪҵû߶ϵͳʾչʾ顣

    Ҫ

    ʱ䣺2014113 14:00-19:00

    ٿʱ䣺20141146գ죩

    οվ

ѧ֪ͨ

йϢѧԱչ֪ͨ

    ΪƽѧĸĸԻԱΪĹƣȫԱƶȣйЭڹ淶ȫѧ˻ԱǼǺŵ֪ͨҪ͹涨ϱľ˻ԱǼƶȡ

ԱǼǵļҪ:

    1.Աдɺѧ䣺cips_m@iscas.ac.cn

    2.յԱϢȷϺѧȻ, ɻԱʸ֤

2014"йϢѧ"˻Աշѱ׼

    ˻Ա120Ԫ/    ѧԱ 60Ԫ/

Աѽɷѷʽ

    1 תˣ

       Убзк֧ йϢѧ ˺ţ0200004509014415619

    2 ʾֻ

       ַ8718"йϢѧ" տˣйϢѧ 100190

    3 ѧ֧˺תˣ

       йϢѧ ˺ţcips_pay@163.com

    4йϢѧ칫ҽɷ

       ַкйشĽ4Ժ7¥201 ϵ绰010-62562916

    ԱעᲢɷѺ󣬽ûԱǼǺźͻԱ֤ڲμѧĸѧʱƾԱ֤ܻŻݣڻйϢѧԱͨѶӰ棩

    Ϊѧ߼ѧᣬ2014ȻԱǼǵȫԱͲѧԱԽɷ˳ȵȵãΪֹ2014ȫ꡶Ϣѧֽʰ棩

ѧ̬

Դ¼ƻʮƻķ45Ԫ

    գͳ.°Դ¼ƻ۷ȥ꣬׹һΪBRAIN¼ƻĴĿĿּڻƻͼףѸƶȷƻʵ֡ΪǿƶĿʵʩ°Ϊüƻ1ԪǹоԺ(NIH)ҿѧ͹ȽоĿ֡

    ڣھ˳1Ļ̸һNIHټĹСԴ¼ƻһЩĿԸ˳ʵͼʽһʵĿ꣺Ϊ10Ľ̹45ԪԼĿǰԤ4

    http://scienceblog.blog.163.com/blog/static/189685007201451195033437

CIKM 201411³Ϻ

    CIKM 201411³ϺУ췽˹ȸJeff DeanѧϰԼ΢ĹԱȫִиܲQi Lu֪ʶͼĿYagoĴʼGerhard Weikum

    http://cikm2014.fudan.edu.cn/index.php/Index/info/id/6

ٶȻ߹ݽӡ֥鿪š

    91622ӡ֥鿪šؽĿ̨ӭ˽Ŀλ""սѡ֡ʴСȡλɰٶʴŶӿʴڹڻƵƵ˻٩ƾѸٵķӦ׼ȷĻش´Ĺأ40漰֣Ӱӣʷѧ͵ĿȫԣɫıӮֳھ̾ѡ

    http://finance.chinanews.com/it/2014/09-17/6598884.shtml

ľ䷨ϵͳ NiuParser 1.0.0 Beta

    ɶѧȻԴʵŶӾһŬƳɹʽľ䷨ϵͳ NiuParser֧ľӼߴԷдC++ɿκԴ롣оԶѡ

    http://www.niuparser.com/

ﺺϿ⣨BLCU Chinese CorpusBCCʽ

    100ֱ罻ѧƼ~ģ걬CCRL͹ίϿ⡣ȫļ㣬֧ģҺͳģʽҡȫԶִʲԱע

    http://bcc.blcu.edu.cn/

΢оԱFunaiɾͽ

    գ΢оԺоԱJunichi TsujiiΪȻԴ(NLP)ѧıھϵĿԹFunaiɾͽһձѧҪĽ֮һ֮ǰĵý߰Marvin MinksyںTakeo Kanadeڡ

    http://blogs.technet.com/b/inside_microsoft_research/archive/2014/09/16/microsoft-researcher-receives-prestigious-funai-achievement-award.aspx

DBpedia Version 2014 released

The most important improvements of the new release compared to DBpedia 3.9 are:
1. the new release is based on updated Wikipedia dumps dating from April / May 2014 (the 3.9 release was based on dumps from March / April 2013), leading to an overall increase of the number of things described in the English edition from 4.26 to 4.58 million things.
2. the DBpedia ontology is enlarged and the number of infobox to ontology mappings has risen, leading to richer and cleaner data.

    http://blog.dbpedia.org/2014/09/09/dbpedia-version-2014-released/

2014 SIGKDD Test of Time Award

İ
A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise [KDD 1996]
Integrating Classification and Association Rule Mining [KDD 1998]
Maximizing the Spread of Influence through a Social Network [ KDD '03]

    http://www.kdd.org/blog/2014-sigkdd-test-time-award

ġѧԴ

ICML2014Ƶ
http://techtalks.tv/icml2014/
    International Conference on Machine Learning 2014ƵKeynoteTutorialTrack

word2vec 0.1C汾
https://code.google.com/p/word2vec/
    ҪĶһIJCBOWۼӸijƽ޸˻ģ

ѧϰDeep Learning on Hadoop
http://cdn.oreillystatic.com/en/assets/1/event/115/Introduction%20to%20Parallel%20Iterative%20Deep%20Learning%20on%20Hadoop%E2%80%99s%20Next%E2%80%8B-Generation%20YARN%20Framework%20Presentation%202.pdf
    ˵ĽʲôѧϰDLʲôӦʺDLDLЩԴʵ֣HadoopһDLӦá

226482ݼ6,482 Datasets Available Across 22 Federal Agencies In Data.json Files
http://kinlane.com/2014/08/25/6482-datasets-available-across-22-federal-agencies-in-datajson-files/
    226482ݼ

David MimnoдġԻѧϰѧߵһ㽨顷
http://mimno.infosci.cornell.edu/b/articles/ml-learn/
    David MimnoдġԻѧϰѧߵһ㽨顷ǿʵ۽ϡ

ӵд--ڱ
http://v.youku.com/v_show/id_XNzY1MTk2OTY0.html
    ڼ飺μݴѧУͳϵΡ廪ѧѧѧѧԺƸ,ѧԺԺʿ

Tutorial: Dependency Parsing: Past, Present, and Future
http://ir.hit.edu.cn/~lzh/
    COLING 2014ݴѧڣںʿTutorial "Dependency Parsing: Past, Present, and Future"

TutorialEntity Linking and Retrieval
http://ejmeij.github.io/entity-linking-and-retrieval-tutorial/
    Ϊʵӣʵ

ʿģRECURSIVE DEEP LEARNING FOR NATURAL LANGUAGE PROCESSING AND COMPUTER VISION
http://nlp.stanford.edu/~socherr/thesis.pdf
    Richard Socher

199IT2014.09.012014.09.07ϼ
http://dataunion.org/bbs/forum.php?mod=viewthread&tid=426&page=1&extra=#pid433
    Nielsen2014ȫ񱨸桢Acquity2014ȫго桢App Annie&IDC2014Q2ȫֻϷгȡ

Michael Jordan Redditʴ
http://www.reddit.com/r/MachineLearning/comments/2fxi6v/ama_michael_i_jordan/
    Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley.
    ڱʴУMichael JordanشѧϰĹ۵㣬ƼһЩѧϰѧϰ鼮ȵȡ

˹Դ
http://openair.allenai.org/
    Open AI ResourceռAIĺܶ๤ߺݣôҵ޺ۡĿǰڰ3000+Դ12࣬ϲã

KDD2014 "the recommender problem revisited"
http://www.kdd.org/kdd2014/tutorials/KDD%20-%20The%20Recommender%20Problem%20Revisited.pdf
    ƼϵͳһXavier Amatriain(135ҳ, 2014ѧϰļѧУ248ҳ), ڶ"Context Aware Recommendation" (64ҳ)

ѧϰοĿȫ
http://memkite.com/deep-learning-bibliography/
    ռѧϰµij2014֮󣩣˾ıעѧϰصϡ

Deep learning߰ CNTK
https://cntk.codeplex.com/
    ΢оԺƷC++ʵ֣CPU/GPU֧֣DNN/CNN/RNN/LSTMĿǰֻ֧windows

ѵ: Deep Learning Methods and Applications" (2014)
    http://research.microsoft.com/pubs/209355/DeepLearning-NowPublishing-Vol7-SIG-039.pdf
    ΢оԺᶰдѵ飬200ҳƪѧϰķӦ˱Ƚȫ


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