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Bits 'n Pieces on Big Data
Innovative information and insight into Big Data (if you like the content, please donate to Bitcoin #1MhtqfDaAsy4TpYwjS2Kq2DMKrecupbx8c)
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"Data Science: Where are We Going?" - Dr. DJ Patil (Strata + Hadoop 2015) - YouTube

Data Science, where are we going? What impact can we expect? With a special introduction from President Barack Obama. Watch more from Strata + Hadoop San Jos...
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This is the most interesting presentation but many more material in this year's Strata: http://strataconf.com/big-data-conference-ca-2015/public/content/home

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RecSys 2014 (Silicon Valley) - RecSys

RecSys 2014 (Silicon Valley) - RecSys | Bits 'n Pieces on Big Data | Scoop.it
Foster City, Silicon Valley, USA, 6th-10th October 2014

 

The ACM Recommender System conference (RecSys) is the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems.

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Also, of interest is the First Workshop on Recommendation Systems for Television and online Video (RecSysTV) that is happening in conjunction with this conference: http://boxfish.com/recsys

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Web Science 2014 Data Challenge

Web Science 2014 Data Challenge | Bits 'n Pieces on Big Data | Scoop.it

The web has generated huge amounts of data at massive
scale, but making sense of these datasets and representing them in a
compact and easily-interpretable way remains very difficult. The goal
of this challenge is to encourage innovative visualizations of web
data.  To enable this visualization, the following several large-scale, easy-to-use, publicly-available datasets are prepared:

1. Web traffic data, including more than 200 million HTTP requests
from browsers to servers;
2. Twitter data, including a sample of more than 22 million tweets;
3. Social bookmarking data, consisting of about 430,000 bookmarked pages;
4. Co-authorship of academic papers, consisting of about 21.5 million papers
and 10.8 million authors

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Rules:
1. For fairness, the visualization must be primarily based on the data
that we provide. Other datasets may be used to augment ours, but these
datasets must be publicly-available and described in detail in the
documentation (see #4 below).

2. The visualization must be a static image, and must be submitted as
a PDF. In addition to the main PDF, please submit a PNG version at a
resolution of about 640x480, for display on web pages, social media
sites, mobile devices, etc. This PNG version need not contain the full
visualization, but should be an appropriate representation (e.g. a
subset of the full PDF).

3. Please include a separate PDF file containing a description of the
visualization, including: (1) name(s), affiliation(s), and contact
information of the creator(s), (2) the purpose of the visualization,
(3) which dataset(s) were used, (4) a brief description of how the
visualizations was created, and (5) any other information you would
like to share with the judges.

4. By submitting your visualization, you agree to allow us to display
your visualization at the conference and on the Web Science website
and social media channels. (We will give proper attribution, of
course.) You also certify that you are the copyright holder of the
visualization and are authorized to give us this permission.

5. Entries are due by 11:59PM Hawaii time on April 15, 2014. Please
e-mail your entry to David Crandall. (If you do not receive a
confirmation email within 24 hours, your entry has not been received
and should be re-sent.)

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DIMACS Workshop 2014

DIMACS Workshop  2014 | Bits 'n Pieces on Big Data | Scoop.it
DIMACS Workshop on Building Communities for Transforming Social Media Research Through New Approaches for Collecting, Analyzing, and Exploring Social Media DataApril 10 - 11, 2014 
DIMACS Center, CoRE Building, Rutgers University
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Many interesting papers. For example: Matthew J. Salganik, "Wiki Surveys: Open and Quantifiable Social Data Collection."

Presented under the auspices of the DIMACS Special Focus on Information Sharing and Dynamic Data Analysis.

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Schedule: All sessions: Strata 2014 - O'Reilly Conferences, February 11 - 13, 2014, Santa Clara, CA

Schedule: All sessions: Strata 2014 - O'Reilly Conferences, February 11 - 13, 2014, Santa Clara, CA | Bits 'n Pieces on Big Data | Scoop.it
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ACM Web Science Conference 2014 (WebSci14)

ACM Web Science Conference 2014 (WebSci14) | Bits 'n Pieces on Big Data | Scoop.it
ACM Web Science 2014 (WebSci14) Conference. Hosted by Center for Complex Networks and Systems Research, School of Informatics and Computing at Indiana University, Bloomington, USA, 23-26 June 2014.
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From HadoopDB to Hadapt: A Case Study of Transitioning a VLDB paper...

VLDB 2013 Early Career Research Contribution Award Presentation Abstract: Four years ago at VLDB 2009, a paper was published about a research prototype.

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Daniel Abadi's Hadapt slides from VLDB.

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The 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining | Program

The 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining | Program | Bits 'n Pieces on Big Data | Scoop.it
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SIGIR Conference 2013 Full papers

SIGIR Conference 2013 Full papers | Bits 'n Pieces on Big Data | Scoop.it
SIGIR Conference 2013,special interest group on information retrieval,search technologies, dermot garland
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onur savas's comment, July 30, 2013 11:19 PM
Slides from the paper "Entity Linking and Retrieval"" http://ejmeij.github.io/entity-linking-and-retrieval-tutorial/
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Tutorial: Machine Learning on Big Data (SIGMOD 2013)

Tutorial: Machine Learning on Big Data (SIGMOD 2013) | Bits 'n Pieces on Big Data | Scoop.it
Below the fold, there is an embedded version of our slides. You can also download them in PowerPoint or PDF file. If you have any questions or comments, please feel free to leave a comment below.
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Great tutorial at SIGMOD 2013. Slides can be seen without downloading.

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KDD Workshop on Learning Emergencies from Social Information 2014

KDD Workshop on Learning Emergencies from Social Information 2014 | Bits 'n Pieces on Big Data | Scoop.it

Mobile phone data and the content generated by hundreds of millions of users on social media such as Twitter, or Facebook, present continuous data streams of human social activities, and offer an unprecedented opportunity to mine and understand the structure and dynamics of social and information behavior in various situations. In this workshop we will call attention to researching situations following large-scale emergencies, including natural disasters, terrorist attacks, and so on. These emergency events are now among the largest threats to national security. Over the last decade, natural disasters have affected more than 2.4 billions of people. There is an indisputably increasing need for new tools to strengthen disaster resilience at all levels of society. 

 How can we deal with data collected from heterogeneous and potentially biased sources? How can we properly understand social dynamics during emergencies? How can we turn such understanding into tools for decision makers? To better prepare for future emergencies, it is valuable to deeply understand the context within which the research can be applied. 
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Massive Data Flow: Understanding the Complex Dynamics of the Web

The Web is perhaps the most complex system that we know. Its massive scale, complex dynamism, open richness, and social character mean that it may be more profitable to study it using tools and concepts appropriate for understanding nervous systems, organisms, ecosystems and society, rather than approaches more traditionally employed to engineer technology. Simultaneously, the scientists trying to understand this wide array of complex natural systems may have much to gain by considering the emergingstudy of the Web.

 

Massive Data Flow: Understanding the Complex Dynamics of the Web
Workshop at the ACM Web Science Conference 2014 (http://www.websci14.org )
10:00 - 18:00, June 23rd, 2014
Indiana University, Bloomington

http://sacral.c.u-tokyo.ac.jp/event/MDF_WebSci/ ;


Via Complexity Digest
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1st International Workshop on Scalable Computing For Real-Time Big Data Applications (SCRAMBL'14)

1st International Workshop on Scalable Computing For Real-Time Big Data Applications (SCRAMBL'14) | Bits 'n Pieces on Big Data | Scoop.it

1st International Workshop on Scalable Computing For Real-Time Big Data Applications. This workshop aims at providing a venue for designers, practitioners, researchers, developers, and industrial/governmental partners to come together, present and discuss leading research results, use cases, innovative ideas, challenges, and opportunities that arise from real-time big data applications.

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The Future of the Statistical Sciences Workshop

The Future of the Statistical Sciences Workshop | Bits 'n Pieces on Big Data | Scoop.it
Workshop at a Glance: WHAT: Future of the Statistical Sciences Workshop WHEN: November 11-12, 2013 WHERE: Royal Statistical Society Offices, London, England About the Future of the Statistical Sciences Workshop The capstone event of the International...
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Collective Intelligence 2014

Collective Intelligence 2014 | Bits 'n Pieces on Big Data | Scoop.it

This interdisciplinary conference seeks to bring together researchers from a variety of fields relevant to understanding and designing collective intelligence of many types.

 

Topics of interest include but are not limited to:

human computation

social computing

crowdsourcing

wisdom of crowds (e.g., prediction markets)

group memory and extended cognition

collective decision making and problem-solving

participatory and deliberative democracy

animal collective behavior

organizational design

public policy design (e.g., regulatory reform)

ethics of collective intelligence (e.g., “digital sweatshops”)

computational models of group search and optimization

emergence and evolution of intelligence

new technologies for making groups smarter

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Strata in London 2013 - O'Reilly Conferences, November 11 - 13, 2013, London, England

Strata in London 2013 - O'Reilly Conferences, November 11 - 13, 2013, London, England | Bits 'n Pieces on Big Data | Scoop.it
The O'Reilly Strata Conference delivers the nuts-and-bolts foundation for building a data-driven business—the latest on the skills, tools, and technologies you need to make data work.
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There are some interesting talks...

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Program

Program | Bits 'n Pieces on Big Data | Scoop.it

In recent years, analysis of data from social media has provided a wealth of information about phenomena at societal scale, at least to the extent to which interactions, intentions and beliefs measured on-line reflect their real-world counterparts. Data from Twitter, Facebook, Google+, and Weblogs in general have been used to predict elections, opinions and attitudes, movie revenues, andoscillations in the stock market, to cite few examples. Similar data provided insights into the mechanisms driving the formation of groups of interests, topical communities, and the evolution of social networks. They also have been used to study polarization phenomena in politics, diffusion of information and the dynamics of collective attention.

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Frontiers in Massive Data Analysis (Prepublication from NIST Big Data Working Group)

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NIST pre-publication. The NIST Big Data working group is meeting on Sep 30, 2013 in their Gaithersburg campus: http://bigdatawg.nist.gov/home.php

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