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.
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
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 * https://loosebolts.wordpress.com/2008/12/02/our-vision-for-generation-4-modular-data-centers-one-way-of-getting-it-just-right/
248 * http://www.mediafire.com/file/zzqna34282frr2f/koomeydatacenterelectuse2011finalversion.pdf
249 * http://searchcloudcomputing.techtarget.com/feature/Cloud-computing-experts-forecast-the-market-climate-in-2014
250 * http://www.slideshare.net/botchagalupe/introduction-to-clouds-cloud-camp-columbus
251 * http://www.slideshare.net/woorung/trend-and-future-of-cloud-computing
252 * http://www.venus-c.eu/Pages/Home.aspx
253 * http://www.kpcb.com/internet-trends
254 * ----------------------------
255 * http://bigdatawg.nist.gov/_uploadfiles/M0311_v2_2965963213.pdf
256 * https://dzone.com/articles/hadoop-t-etl
257 * http://venublog.com/2013/07/16/hadoop-summit-2013-hive-authorization/
258 * https://indico.cern.ch/event/214784/session/5/contribution/410
259 * http://asd.gsfc.nasa.gov/archive/hubble/a_pdf/news/facts/FS14.pdf
260 * 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 * http://www.ifis.cs.tu-bs.de/teaching/ss-11/irws
273 * https://en.wikipedia.org/wiki/PageRank
274 * http://webcourse.cs.technion.ac.il/236621/Winter2011-2012/en/ho_Lectures.html
275 * Meeker/Wu May 29 2013 Internet Trends D11 Conference http://www.slideshare.net/kleinerperkins/kpcb-internet-trends-2013
276 * ----------------------------
277 * https://www.gesoftware.com/minds-and-machines
278 * https://www.gesoftware.com/predix
279 * https://www.gesoftware.com/sites/default/files/the-industrial-internet/index.html
280 * https://developer.cisco.com/site/eiot/discover/overview/
281 * http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Industrial-Internet-Changing-Competitive-Landscape-Industries.pdf
282 * http://www.gesoftware.com/ge-predictivity-infographic
283 * http://www.getransportation.com/railconnect360/rail-landscape
284 * http://www.gesoftware.com/sites/default/files/GE-Software-Modernizing-Machine-to-Machine-Interactions.pdf