.. _hw_references: Homework References =================== It is important that you know how to properly cite references. IN order to teach you how to do that we have taken the almost 300 references from the class and will ask you to provide **PROPER** academic references for them. All references will be managed with jabref. You will have to do about 10 references. Students should build teams of 2 students to correct each others contribution if possible. You will only get points for the references that are absolute correct. It does not matter if a colleague has helped you correcting your references. What is important is that you know how to cite correctly. .. warning:: This homework is typically underestimated by students and often done in sloppy fashion. I have had classes where 50% of the class got 0 points in this assignment. Thus it is not just sufficient to put in the reference as MISC if it is a url, but you have to actually look up the URL, if its a paper, you may even have to locate which journal or conference, which location the conference took place what date the conference took place and so forth. Please note that many bibentries including some form IEEE and other sources could be wrong or are incomplete. For example are there other locations where you can find the PDF of a paper? This assignment counts as much as a paper. How will you know which citation you need to do?: You will be assigned a number in class and you simply have to do all the references that are in the list and do the once with your assignment number specified in a1 - a5 and b1-b5 as defined in https://piazza.com/class/irqfvh1ctrg2vt?cid=260 What if i get a reference to "--------"? Just pick randomly another number that is not associated with a ------ Can I use endnote for this? No. What is an article? An article is published in a journal. What is inProceedings? That is an article published in a conference proceedings What is inBook? That is a chapter or pages in a book How do I cite urls? Often you can find a proper article and use that in addition to the url. Hence, you may have to introduce two references. If you just cite the URL, watch out for how published it, what is the author, when was it published, what is the proper url, and when was it accessed. What if my link no longer works? Can you find it in the internet archive? Is there a query you could find from the url and identify an alternate location? Where do I upload it: Go to gitlab and go into the bib folder, upload your references as class.bib How do I create labels: use class000 where 000 is the number of the 0 padded number of your reference in the list bellow. Example, assume you have to do reference 11, than your label for that is class011. Add the owner={HID, Firstname Lastname} field in jabref Where Firstname Lastname is your fisrname and lastname :: 1 * ---------------------------- 2 * http://www.gartner.com/technology/home.jsp and many web links 3 * Meeker/Wu May 29 2013 Internet Trends D11 Conference http://www.slideshare.net/kleinerperkins/kpcb-internet-trends-2013 4 * http://cs.metrostate.edu/~sbd/slides/Sun.pdf 5 * Taming The Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics, Bill Franks Wiley ISBN: 978-1-118-20878-6* Bill Ruh http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 6 * http://www.genome.gov/sequencingcosts/ 7 * CSTI General Assembly 2012, Washington, D.C., USA Technical Activities Coordinating Committee (TACC) Meeting, Data Management, Cloud Computing and the Long Tail of Science October 2012 Dennis Gannon* http://www.microsoft.com/en-us/news/features/2012/mar12/03-05CloudComputingJobs.aspx 8 * http://www.mckinsey.com/mgi/publications/big_data/index.asp 9 * Tom Davenport http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 10 * http://research.microsoft.com/en-us/people/barga/sc09_cloudcomp_tutorial.pdf 11 * http://research.microsoft.com/pubs/78813/AJ18_EN.pdf 12 * http://www.google.com/green/pdfs/google-green-computing.pdf 13 * http://www.wired.com/wired/issue/16-07 14 * http://research.microsoft.com/en-us/collaboration/fourthparadigm/ 15 * Jeff Hammerbacher http://berkeleydatascience.files.wordpress.com/2012/01/20120117berkeley1.pdf 16 * http://grids.ucs.indiana.edu/ptliupages/publications/Where%20does%20all%20the%20data%20come%20from%20v7.pdf 17 * http://www.interactions.org/cms/?pid=1032811 18 * http://www.quantumdiaries.org/2012/09/07/why-particle-detectors-need-a-trigger/atlasmgg/ 19 * http://www.sciencedirect.com/science/article/pii/S037026931200857X 20 * http://www.slideshare.net/xamat/building-largescale-realworld-recommender-systems-recsys2012-tutorial 21 * http://www.ifi.uzh.ch/ce/teaching/spring2012/16-Recommender-Systems_Slides.pdf 22 * http://en.wikipedia.org/wiki/PageRank 23 * http://pages.cs.wisc.edu/~beechung/icml11-tutorial/ 24 * https://sites.google.com/site/opensourceiotcloud/ 25 * http://datascience101.wordpress.com/2013/04/13/new-york-times-data-science-articles/ 26 * http://blog.coursera.org/post/49750392396/on-the-topic-of-boredom 27 * http://x-informatics.appspot.com/course 28 * http://iucloudsummerschool.appspot.com/preview 29 * https://www.youtube.com/watch?v=M3jcSCA9_hM 30 * ---------------------------- 31 * http://www.microsoft.com/en-us/news/features/2012/mar12/03-05CloudComputingJobs.aspx 32 * http://www.mckinsey.com/mgi/publications/big_data/index.asp 33 * Tom Davenport http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 34 * Anjul Bhambhri http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 35 * Jeff Hammerbacher http://berkeleydatascience.files.wordpress.com/2012/01/20120117berkeley1.pdf 36 * http://www.economist.com/node/15579717 37 * http://cs.metrostate.edu/~sbd/slides/Sun.pdf 38 * http://jess3.com/geosocial-universe-2/ 39 * Bill Ruhhttp://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 40 * http://www.hsph.harvard.edu/ncb2011/files/ncb2011-z03-rodriguez.pptx 41 * Hugh Williams http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 42 * ---------------------------- 43 * http://www.economist.com/node/15579717 44 * Geoffrey Fox and Dennis Gannon Using Clouds for Technical Computing To be published in Proceedings of HPC 2012 Conference at Cetraro, Italy June 28 2012 45 * http://grids.ucs.indiana.edu/ptliupages/publications/Clouds_Technical_Computing_FoxGannonv2.pdf 46 * http://grids.ucs.indiana.edu/ptliupages/publications/Where%20does%20all%20the%20data%20come%20from%20v7.pdf 47 * http://www.genome.gov/sequencingcosts/ 48 * http://www.quantumdiaries.org/2012/09/07/why-particle-detectors-need-a-trigger/atlasmgg 49 * http://salsahpc.indiana.edu/dlib/articles/00001935/ 50 * http://en.wikipedia.org/wiki/Simple_linear_regression 51 * http://www.ebi.ac.uk/Information/Brochures/ 52 * http://www.wired.com/wired/issue/16-07 53 * http://research.microsoft.com/en-us/collaboration/fourthparadigm/ 54 * CSTI General Assembly 2012, Washington, D.C., USA Technical Activities Coordinating Committee (TACC) Meeting, Data Management, Cloud Computing and the Long Tail of Science October 2012 Dennis Gannon https://sites.google.com/site/opensourceiotcloud/ 55 * ---------------------------- 56 * CSTI General Assembly 2012, Washington, D.C., USA Technical Activities Coordinating Committee (TACC) Meeting, Data Management, Cloud Computing and the Long Tail of Science October 2012 Dennis Gannon 57 * Dan Reed Roger Barga Dennis Gannon Rich Wolskihttp://research.microsoft.com/en-us/people/barga/sc09_cloudcomp_tutorial.pdf 58 * http://www.datacenterknowledge.com/archives/2011/05/10/uptime-institute-the-average-pue-is-1-8/ 59 * http://loosebolts.wordpress.com/2008/12/02/our-vision-for-generation-4-modular-data-centers-one-way-of-getting-it-just-right/ 60 * http://www.mediafire.com/file/zzqna34282frr2f/koomeydatacenterelectuse2011finalversion.pdf 61 * Bina Ramamurthy http://www.cse.buffalo.edu/~bina/cse487/fall2011/ 62 * Jeff Hammerbacher http://berkeleydatascience.files.wordpress.com/2012/01/20120117berkeley1.pdf 63 * Jeff Hammerbacher http://berkeleydatascience.files.wordpress.com/2012/01/20120119berkeley.pdf 64 * Anjul Bhambhri http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 65 * http://cs.metrostate.edu/~sbd/slides/Sun.pdf 66 * Hugh Williams http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 67 * Tom Davenport http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 68 * http://www.mckinsey.com/mgi/publications/big_data/index.asp 69 * http://cra.org/ccc/docs/nitrdsymposium/pdfs/keyes.pdf 70 * ---------------------------- 71 * https://wiki.nci.nih.gov/display/CIP/CIP+Survey+of+Biomedical+Imaging+Archives 72 * http://grids.ucs.indiana.edu/ptliupages/publications/Where%20does%20all%20the%20data%20come%20from%20v7.pdf 73 * http://www.ieee-icsc.org/ICSC2010/Tony%20Hey%20-%2020100923.pdf 74 * http://quantifiedself.com/larry-smarr/ 75 * http://www.ebi.ac.uk/Information/Brochures/ 76 * http://www.kpcb.com/internet-trends 77 * http://www.slideshare.net/drsteventucker/wearable-health-fitness-trackers-and-the-quantified-self 78 * http://www.siam.org/meetings/sdm13/sun.pdf 79 * http://en.wikipedia.org/wiki/Calico_%28company%29 80 * http://www.slideshare.net/GSW_Worldwide/2015-health-trends 81 * http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Industrial-Internet-Changing-Competitive-Landscape-Industries.pdf 82 * http://www.slideshare.net/schappy/how-realtime-analysis-turns-big-medical-data-into-precision-medicine 83 * http://medcitynews.com/2013/03/the-body-in-bytes-medical-images-as-a-source-of-healthcare-big-data-infographic/ 84 * http://healthinformatics.wikispaces.com/file/view/cloud_computing.ppt 85 * http://www.mckinsey.com/~/media/McKinsey/dotcom/Insights/Health%20care/The%20big-data%20revolution%20in%20US%20health%20care/The%20big-data%20revolution%20in%20US%20health%20care%20Accelerating%20value%20and%20innovation.ashx 86 * https://partner.microsoft.com/download/global/40193764 87 * http://ec.europa.eu/information_society/activities/health/docs/policy/taskforce/redesigning_health-eu-for2020-ehtf-report2012.pdf 88 * http://www.kpcb.com/internet-trends 89 * http://www.liveathos.com/apparel/app 90 * http://debategraph.org/Poster.aspx?aID=77 91 * http://www.oerc.ox.ac.uk/downloads/presentations-from-events/microsoftworkshop/gannon 92 * http://www.delsall.org 93 * http://salsahpc.indiana.edu/millionseq/mina/16SrRNA_index.html 94 * http://www.geatbx.com/docu/fcnindex-01.html 95 * https://wiki.nci.nih.gov/display/CIP/CIP+Survey+of+Biomedical+Imaging+Archives 96 * http://grids.ucs.indiana.edu/ptliupages/publications/Where%20does%20all%20the%20data%20come%20from%20v7.pdf 97 * http://www.ieee-icsc.org/ICSC2010/Tony%20Hey%20-%2020100923.pdf 98 * http://quantifiedself.com/larry-smarr/ 99 * http://www.ebi.ac.uk/Information/Brochures/ 100 * http://www.kpcb.com/internet-trends 101 * http://www.slideshare.net/drsteventucker/wearable-health-fitness-trackers-and-the-quantified-self 102 * http://www.siam.org/meetings/sdm13/sun.pdf 103 * http://en.wikipedia.org/wiki/Calico_%28company%29 104 * http://www.slideshare.net/GSW_Worldwide/2015-health-trends 105 * http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Industrial-Internet-Changing-Competitive-Landscape-Industries.pdf 106 * http://www.slideshare.net/schappy/how-realtime-analysis-turns-big-medical-data-into-precision-medicine 107 * http://medcitynews.com/2013/03/the-body-in-bytes-medical-images-as-a-source-of-healthcare-big-data-infographic/ 108 * http://healthinformatics.wikispaces.com/file/view/cloud_computing.ppt 109 * http://www.mckinsey.com/~/media/McKinsey/dotcom/Insights/Health%20care/The%20big-data%20revolution%20in%20US%20health%20care/The%20big-data%20revolution%20in%20US%20health%20care%20Accelerating%20value%20and%20innovation.ashx 110 * https://partner.microsoft.com/download/global/40193764 111 * http://ec.europa.eu/information_society/activities/health/docs/policy/taskforce/redesigning_health-eu-for2020-ehtf-report2012.pdf 112 * http://www.kpcb.com/internet-trends 113 * http://www.liveathos.com/apparel/app 114 * http://debategraph.org/Poster.aspx?aID=77 115 * http://www.oerc.ox.ac.uk/downloads/presentations-from-events/microsoftworkshop/gannon 116 * http://www.delsall.org 117 * http://salsahpc.indiana.edu/millionseq/mina/16SrRNA_index.html 118 * http://www.geatbx.com/docu/fcnindex-01.html 119 * ---------------------------- 120 * http://www.slideshare.net/BrandEmotivity/sports-analytics-innovation-summit-data-powered-storytelling 121 * http://www.sloansportsconference.com/ 122 * http://sabr.org/ 123 * http://en.wikipedia.org/wiki/Sabermetrics 124 * http://en.wikipedia.org/wiki/Baseball_statistics 125 * http://www.sportvision.com/baseball 126 * http://m.mlb.com/news/article/68514514/mlbam-introduces-new-way-to-analyze-every-play 127 * http://www.fangraphs.com/library/offense/offensive-statistics-list/ 128 * http://en.wikipedia.org/wiki/Component_ERA 129 * http://www.fangraphs.com/library/pitching/fip/ 130 * http://nomaas.org/2012/05/a-look-at-the-defense-the-yankees-d-stinks-edition/ 131 * http://en.wikipedia.org/wiki/Wins_Above_Replacement 132 * http://www.fangraphs.com/library/misc/war/ 133 * http://www.baseball-reference.com/about/war_explained.shtml 134 * http://www.baseball-reference.com/about/war_explained_comparison.shtml 135 * http://www.baseball-reference.com/about/war_explained_position.shtml 136 * http://www.baseball-reference.com/about/war_explained_pitch.shtml 137 * http://www.fangraphs.com/leaders.aspx?pos=all&stats=bat&lg=all&qual=y&type=8&season=2014&month=0&season1=1871&ind=0 138 * http://battingleadoff.com/2014/01/08/comparing-the-three-war-measures-part-ii/ 139 * http://battingleadoff.com/2014/01/08/comparing-the-three-war-measures-part-ii/ 140 * http://en.wikipedia.org/wiki/Coefficient_of_determination 141 * http://www.sloansportsconference.com/wp-content/uploads/2014/02/2014_SSAC_Data-driven-Method-for-In-game-Decision-Making.pdf 142 * https://courses.edx.org/courses/BUx/SABR101x/2T2014/courseware/10e616fc7649469ab4457ae18df92b20/ 143 * --------------------------- 144 * http://vincegennaro.mlblogs.com/ 145 * https://www.youtube.com/watch?v=H-kx-x_d0Mk 146 * http://www.sportvision.com/media/pitchfx-how-it-works 147 * http://www.baseballprospectus.com/article.php?articleid=13109 148 * http://baseball.physics.illinois.edu/FastPFXGuide.pdf 149 * http://baseball.physics.illinois.edu/FieldFX-TDR-GregR.pdf 150 * http://www.sportvision.com/baseball/fieldfx 151 * http://regressing.deadspin.com/mlb-announces-revolutionary-new-fielding-tracking-syste-1534200504 152 * http://grantland.com/the-triangle/mlb-advanced-media-play-tracking-bob-bowman-interview/ 153 * http://www.sportvision.com/baseball/hitfx 154 * https://www.youtube.com/watch?v=YkjtnuNmK74 155 * ---------------------------- 156 * http://www.sloansportsconference.com/?page_id=481&sort_cate=Research%20Paper 157 * http://www.slideshare.net/Tricon_Infotech/big-data-for-big-sports 158 * http://www.slideshare.net/BrandEmotivity/sports-analytics-innovation-summit-data-powered-storytelling 159 * http://www.liveathos.com/apparel/app 160 * http://www.slideshare.net/elew/sport-analytics-innovation 161 * http://www.wired.com/2013/02/catapault-smartball/ 162 * http://www.sloansportsconference.com/wp-content/uploads/2014/06/Automated_Playbook_Generation.pdf 163 * http://autoscout.adsc.illinois.edu/publications/football-trajectory-dataset/ 164 * http://www.sloansportsconference.com/wp-content/uploads/2012/02/Goldsberry_Sloan_Submission.pdf 165 * http://gamesetmap.com/ 166 * http://www.trakus.com/technology.asp#tNetText 167 * ---------------------------- 168 * http://grids.ucs.indiana.edu/ptliupages/publications/Where%20does%20all%20the%20data%20come%20from%20v7.pdf 169 * http://www.interactions.org/cms/?pid=6002 170 * http://www.interactions.org/cms/?pid=1032811 171 * http://www.sciencedirect.com/science/article/pii/S037026931200857X 172 * http://biologos.org/blog/what-is-the-higgs-boson 173 * http://www.atlas.ch/pdf/ATLAS_fact_sheets.pdf 174 * http://www.nature.com/news/specials/lhc/interactive.html 175 * ---------------------------- 176 * https://www.enthought.com/products/canopy/ 177 * Python for Data Analysis: Agile Tools for Real World Data By Wes McKinney, Publisher: O'Reilly Media, Released: October 2012, Pages: 472. 178 * http://jwork.org/scavis/api/ 179 * https://en.wikipedia.org/wiki/DataMelt 180 * ---------------------------- 181 * http://indico.cern.ch/event/20453/session/6/contribution/15?materialId=slides 182 * http://www.atlas.ch/photos/events.html 183 * http://cms.web.cern.ch/ 184 * ---------------------------- 185 * https://en.wikipedia.org/wiki/Pseudorandom_number_generator 186 * https://en.wikipedia.org/wiki/Mersenne_Twister 187 * https://en.wikipedia.org/wiki/Mersenne_prime 188 * CMS-PAS-HIG-12-041 Updated results on the new boson discovered in the search for the standard model Higgs boson in the ZZ to 4 leptons channel in pp collisions at sqrt(s) = 7 and 8 TeV http://cds.cern.ch/record/1494488?ln=en 189 * https://en.wikipedia.org/wiki/Poisson_distribution 190 * https://en.wikipedia.org/wiki/Central_limit_theorem 191 * http://jwork.org/scavis/api/ 192 * https://en.wikipedia.org/wiki/DataMelt 193 * ---------------------------- 194 * http://www.slideshare.net/xamat/building-largescale-realworld-recommender-systems-recsys2012-tutorial 195 * http://www.ifi.uzh.ch/ce/teaching/spring2012/16-Recommender-Systems_Slides.pdf 196 * https://www.kaggle.com/ 197 * http://www.ics.uci.edu/~welling/teaching/CS77Bwinter12/CS77B_w12.html 198 * Jeff Hammerbacher https://berkeleydatascience.files.wordpress.com/2012/01/20120117berkeley1.pdf 199 * http://www.techworld.com/news/apps/netflix-foretells-house-of-cards-success-with-cassandra-big-data-engine-3437514/ 200 * https://en.wikipedia.org/wiki/A/B_testing 201 * http://www.infoq.com/presentations/Netflix-Architecture 202 * ---------------------------- 203 * http://pages.cs.wisc.edu/~beechung/icml11-tutorial/ 204 * ---------------------------- 205 * https://en.wikipedia.org/wiki/Kmeans 206 * http://grids.ucs.indiana.edu/ptliupages/publications/DACIDR_camera_ready_v0.3.pdf 207 * http://salsahpc.indiana.edu/millionseq/ 208 * http://salsafungiphy.blogspot.com/ 209 * https://en.wikipedia.org/wiki/Heuristic 210 * ---------------------------- 211 * Solving Problems in Concurrent Processors-Volume 1, with M. Johnson, G. Lyzenga, S. Otto, J. Salmon, D. Walker, Prentice Hall, March 1988. 212 * Parallel Computing Works!, with P. Messina, R. Williams, Morgan Kaufman (1994). http://www.netlib.org/utk/lsi/pcwLSI/text/ 213 * The Sourcebook of Parallel Computing book edited by Jack Dongarra, Ian Foster, Geoffrey Fox, William Gropp, Ken Kennedy, Linda Torczon, and Andy White, Morgan Kaufmann, November 2002. 214 * Geoffrey Fox Computational Sciences and Parallelism to appear in Enclyclopedia on Parallel Computing edited by David Padua and published by Springer. http://grids.ucs.indiana.edu/ptliupages/publications/SpringerEncyclopedia_Fox.pdf 215 * ---------------------------- 216 * http://www.slideshare.net/woorung/trend-and-future-of-cloud-computing 217 * http://www.slideshare.net/JensNimis/cloud-computing-tutorial-jens-nimis 218 * https://setandbma.wordpress.com/2012/08/10/hype-cycle-2012-emerging-technologies/ 219 * http://insights.dice.com/2013/01/23/big-data-hype-is-imploding-gartner-analyst-2/ 220 * http://research.microsoft.com/pubs/78813/AJ18_EN.pdf 221 * http://static.googleusercontent.com/media/www.google.com/en//green/pdfs/google-green-computing.pdf 222 * ---------------------------- 223 * http://www.slideshare.net/JensNimis/cloud-computing-tutorial-jens-nimis 224 * http://research.microsoft.com/en-us/people/barga/sc09_cloudcomp_tutorial.pdf 225 * http://research.microsoft.com/en-us/um/redmond/events/cloudfutures2012/tuesday/Keynote_OpportunitiesAndChallenges_Yousef_Khalidi.pdf 226 * http://cloudonomic.blogspot.com/2009/02/cloud-taxonomy-and-ontology.html 227 * ---------------------------- 228 * http://www.slideshare.net/woorung/trend-and-future-of-cloud-computing 229 * http://www.eweek.com/c/a/Cloud-Computing/AWS-Innovation-Means-Cloud-Domination-307831 230 * CSTI General Assembly 2012, Washington, D.C., USA Technical Activities Coordinating Committee (TACC) Meeting, Data Management, Cloud Computing and the Long Tail of Science October 2012 Dennis Gannon. 231 * http://research.microsoft.com/en-us/um/redmond/events/cloudfutures2012/tuesday/Keynote_OpportunitiesAndChallenges_Yousef_Khalidi.pdf 232 * http://www.datacenterknowledge.com/archives/2011/05/10/uptime-institute-the-average-pue-is-1-8/ 233 * https://loosebolts.wordpress.com/2008/12/02/our-vision-for-generation-4-modular-data-centers-one-way-of-getting-it-just-right/ 234 * http://www.mediafire.com/file/zzqna34282frr2f/koomeydatacenterelectuse2011finalversion.pdf 235 * http://www.slideshare.net/JensNimis/cloud-computing-tutorial-jens-nimis 236 * http://www.slideshare.net/botchagalupe/introduction-to-clouds-cloud-camp-columbus 237 * http://www.venus-c.eu/Pages/Home.aspx 238 * Geoffrey Fox and Dennis Gannon Using Clouds for Technical Computing To be published in Proceedings of HPC 2012 Conference at Cetraro, Italy June 28 2012 http://grids.ucs.indiana.edu/ptliupages/publications/Clouds_Technical_Computing_FoxGannonv2.pdf 239 * https://berkeleydatascience.files.wordpress.com/2012/01/20120119berkeley.pdf 240 * Taming The Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics, Bill Franks Wiley ISBN: 978-1-118-20878-6 241 * Anjul Bhambhri, VP of Big Data, IBM http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 242 * Conquering Big Data with the Oracle Information Model, Helen Sun, Oracle 243 * Hugh Williams VP Experience, Search & Platforms, eBay http://businessinnovation.berkeley.edu/fisher-cio-leadership-program/ 244 * Dennis Gannon, Scientific Computing Environments, http://www.nitrd.gov/nitrdgroups/images/7/73/D_Gannon_2025_scientific_computing_environments.pdf 245 * http://research.microsoft.com/en-us/um/redmond/events/cloudfutures2012/tuesday/Keynote_OpportunitiesAndChallenges_Yousef_Khalidi.pdf 246 * http://www.datacenterknowledge.com/archives/2011/05/10/uptime-institute-the-average-pue-is-1-8/ 247 * 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http://blogs.teradata.com/data-points/announcing-teradata-aster-big-analytics-appliance/ 261 * http://wikibon.org/w/images/2/20/Cloud-BigData.png 262 * http://hortonworks.com/hadoop/yarn/ 263 * https://berkeleydatascience.files.wordpress.com/2012/01/20120119berkeley.pdf 264 * http://fisheritcenter.haas.berkeley.edu/Big_Data/index.html 265 * ---------------------------- 266 * http://saedsayad.com/data_mining_map.htm 267 * http://webcourse.cs.technion.ac.il/236621/Winter2011-2012/en/ho_Lectures.html 268 * The Web Graph: an Overview Jean-Loup Guillaume and Matthieu Latapy https://hal.archives-ouvertes.fr/file/index/docid/54458/filename/webgraph.pdf 269 * Constructing a reliable Web graph with information on browsing behavior, Yiqun Liu, Yufei Xue, Danqing Xu, Rongwei Cen, Min Zhang, Shaoping Ma, Liyun Ru http://www.sciencedirect.com/science/article/pii/S0167923612001844 270 * http://www.ifis.cs.tu-bs.de/teaching/ss-11/irws 271 * ---------------------------- 272 * 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