journal
MENU ▼
Read by QxMD icon Read
search

Big Data

journal
https://www.readbyqxmd.com/read/28816500/research-challenges-in-financial-data-modeling-and-analysis
#1
Lewis Alexander, Sanjiv R Das, Zachary Ives, H V Jagadish, Claire Monteleoni
Significant research challenges must be addressed in the cleaning, transformation, integration, modeling, and analytics of Big Data sources for finance. This article surveys the progress made so far in this direction and obstacles yet to be overcome. These are issues that are of interest to data-driven financial institutions in both corporate finance and consumer finance. These challenges are also of interest to the legal profession as well as to regulators. The discussion is relevant to technology firms that support the growing field of FinTech...
August 17, 2017: Big Data
https://www.readbyqxmd.com/read/28632445/critique-and-contribute-a-practice-based-framework-for-improving-critical-data-studies-and-data-science
#2
Gina Neff, Anissa Tanweer, Brittany Fiore-Gartland, Laura Osburn
What would data science look like if its key critics were engaged to help improve it, and how might critiques of data science improve with an approach that considers the day-to-day practices of data science? This article argues for scholars to bridge the conversations that seek to critique data science and those that seek to advance data science practice to identify and create the social and organizational arrangements necessary for a more ethical data science. We summarize four critiques that are commonly made in critical data studies: data are inherently interpretive, data are inextricable from context, data are mediated through the sociomaterial arrangements that produce them, and data serve as a medium for the negotiation and communication of values...
June 2017: Big Data
https://www.readbyqxmd.com/read/28632444/the-structural-consequences-of-big-data-driven-education
#3
Elana Zeide
Educators and commenters who evaluate big data-driven learning environments focus on specific questions: whether automated education platforms improve learning outcomes, invade student privacy, and promote equality. This article puts aside separate unresolved-and perhaps unresolvable-issues regarding the concrete effects of specific technologies. It instead examines how big data-driven tools alter the structure of schools' pedagogical decision-making, and, in doing so, change fundamental aspects of America's education enterprise...
June 2017: Big Data
https://www.readbyqxmd.com/read/28632443/diversity-in-big-data-a-review
#4
Marina Drosou, H V Jagadish, Evaggelia Pitoura, Julia Stoyanovich
Big data technology offers unprecedented opportunities to society as a whole and also to its individual members. At the same time, this technology poses significant risks to those it overlooks. In this article, we give an overview of recent technical work on diversity, particularly in selection tasks, discuss connections between diversity and fairness, and identify promising directions for future work that will position diversity as an important component of a data-responsible society. We argue that diversity should come to the forefront of our discourse, for reasons that are both ethical-to mitigate the risks of exclusion-and utilitarian, to enable more powerful, accurate, and engaging data analysis and use...
June 2017: Big Data
https://www.readbyqxmd.com/read/28632442/social-and-technical-trade-offs-in-data-science
#5
Solon Barocas, Danah Boyd, Sorelle Friedler, Hanna Wallach
No abstract text is available yet for this article.
June 2017: Big Data
https://www.readbyqxmd.com/read/28632441/research-dilemmas-with-behavioral-big-data
#6
Galit Shmueli
Behavioral big data (BBD) refers to very large and rich multidimensional data sets on human and social behaviors, actions, and interactions, which have become available to companies, governments, and researchers. A growing number of researchers in social science and management fields acquire and analyze BBD for the purpose of extracting knowledge and scientific discoveries. However, the relationships between the researcher, data, subjects, and research questions differ in the BBD context compared to traditional behavioral data...
June 2017: Big Data
https://www.readbyqxmd.com/read/28632440/call-for-papers-special-issue-on-profit-driven-analytics
#7
Bart Baesens, Wouter Verbeke, Cristián Bravo
No abstract text is available yet for this article.
June 2017: Big Data
https://www.readbyqxmd.com/read/28632439/call-for-papers-special-issue-on-computational-propaganda-and-political-big-data
#8
Philip N Howard, Gillian Bolsover
No abstract text is available yet for this article.
June 2017: Big Data
https://www.readbyqxmd.com/read/28632438/fair-prediction-with-disparate-impact-a-study-of-bias-in-recidivism-prediction-instruments
#9
Alexandra Chouldechova
Recidivism prediction instruments (RPIs) provide decision-makers with an assessment of the likelihood that a criminal defendant will reoffend at a future point in time. Although such instruments are gaining increasing popularity across the country, their use is attracting tremendous controversy. Much of the controversy concerns potential discriminatory bias in the risk assessments that are produced. This article discusses several fairness criteria that have recently been applied to assess the fairness of RPIs...
June 2017: Big Data
https://www.readbyqxmd.com/read/28632437/conscientious-classification-a-data-scientist-s-guide-to-discrimination-aware-classification
#10
Brian d'Alessandro, Cathy O'Neil, Tom LaGatta
Recent research has helped to cultivate growing awareness that machine-learning systems fueled by big data can create or exacerbate troubling disparities in society. Much of this research comes from outside of the practicing data science community, leaving its members with little concrete guidance to proactively address these concerns. This article introduces issues of discrimination to the data science community on its own terms. In it, we tour the familiar data-mining process while providing a taxonomy of common practices that have the potential to produce unintended discrimination...
June 2017: Big Data
https://www.readbyqxmd.com/read/28586238/toward-accountable-discrimination-aware-data-mining-the-importance-of-keeping-the-human-in-the-loop-and-under-the-looking-glass
#11
Bettina Berendt, Sören Preibusch
"Big Data" and data-mined inferences are affecting more and more of our lives, and concerns about their possible discriminatory effects are growing. Methods for discrimination-aware data mining and fairness-aware data mining aim at keeping decision processes supported by information technology free from unjust grounds. However, these formal approaches alone are not sufficient to solve the problem. In the present article, we describe reasons why discrimination with data can and typically does arise through the combined effects of human and machine-based reasoning, and argue that this requires a deeper understanding of the human side of decision-making with data mining...
June 2017: Big Data
https://www.readbyqxmd.com/read/28328254/a-perspective-on-natural-language-understanding-capability-an-interview-with-sam-bowman
#12
Vasant Dhar, Sam Bowman
No abstract text is available yet for this article.
March 2017: Big Data
https://www.readbyqxmd.com/read/28328253/a-comprehensive-index-for-predicting-risk-of-anemia-from-patients-diagnoses
#13
Matthew G Tuck, Farrokh Alemi, John F Shortle, Sanj Avramovic, Charles Hesdorffer
This article demonstrates how time-dependent, interacting, and repeating risk factors can be used to create more accurate predictive medicine. In particular, we show how emergence of anemia can be predicted from medical history within electronic health records. We used the Veterans Affairs Informatics and Computing Infrastructure database to examine a retrospective cohort of 9,738,838 veterans over an 11-year period. Using International Clinical Diagnoses Version 9 codes organized into 25 major diagnostic categories, we measured progression of disease by examining changes in risk over time, interactions in risk of combination of diseases, and elevated risk associated with repeated hospitalization for the same diagnostic category...
March 2017: Big Data
https://www.readbyqxmd.com/read/28328252/liberal-entity-extraction-rapid-construction-of-fine-grained-entity-typing-systems
#14
Lifu Huang, Jonathan May, Xiaoman Pan, Heng Ji, Xiang Ren, Jiawei Han, Lin Zhao, James A Hendler
The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases...
March 2017: Big Data
https://www.readbyqxmd.com/read/28328251/predicting-presidential-election-outcomes-from-what-people-watch
#15
Arash Barfar, Balaji Padmanabhan
In a recent article by Barfar and Padmanabhan (2015), we demonstrated how television viewership data could predict presidential election outcomes in the United States. In this article, we examine predictive models using a snapshot of Nielsen's national data on television viewership. The study is conducted with high-dimensional low sample size (HDLSS) data, whereby we conduct a comparative analysis with and without feature reduction on the data from the 2012 elections. We find that simple "single-show models" often provided more insights and predictive accuracies than models from feature reduction...
March 2017: Big Data
https://www.readbyqxmd.com/read/28287837/scientific-training-in-the-era-of-big-data-a-new-pedagogy-for-graduate-education
#16
Jay Aikat, Thomas M Carsey, Karamarie Fecho, Kevin Jeffay, Ashok Krishnamurthy, Peter J Mucha, Arcot Rajasekar, Stanley C Ahalt
The era of "big data" has radically altered the way scientific research is conducted and new knowledge is discovered. Indeed, the scientific method is rapidly being complemented and even replaced in some fields by data-driven approaches to knowledge discovery. This paradigm shift is sometimes referred to as the "fourth paradigm" of data-intensive and data-enabled scientific discovery. Interdisciplinary research with a hard emphasis on translational outcomes is becoming the norm in all large-scale scientific endeavors...
March 2017: Big Data
https://www.readbyqxmd.com/read/28282239/the-role-of-teamwork-in-the-analysis-of-big-data-a-study-of-visual-analytics-and-box-office-prediction
#17
Verica Buchanan, Yafeng Lu, Nathan McNeese, Michael Steptoe, Ross Maciejewski, Nancy Cooke
Historically, domains such as business intelligence would require a single analyst to engage with data, develop a model, answer operational questions, and predict future behaviors. However, as the problems and domains become more complex, organizations are employing teams of analysts to explore and model data to generate knowledge. Furthermore, given the rapid increase in data collection, organizations are struggling to develop practices for intelligence analysis in the era of big data. Currently, a variety of machine learning and data mining techniques are available to model data and to generate insights and predictions, and developments in the field of visual analytics have focused on how to effectively link data mining algorithms with interactive visuals to enable analysts to explore, understand, and interact with data and data models...
March 2017: Big Data
https://www.readbyqxmd.com/read/28234016/call-for-papers-special-issue-on-profit-driven-analytics
#18
Bart Baesens, Wouter Verbeke, Cristián Bravo
No abstract text is available yet for this article.
March 2017: Big Data
https://www.readbyqxmd.com/read/28207289/call-for-papers-special-issue-on-computational-propaganda-and-political-big-data
#19
Philip N Howard, Gillian Bolsover
No abstract text is available yet for this article.
March 2017: Big Data
https://www.readbyqxmd.com/read/27992267/doomed-direct-online-optimization-of-modeling-errors-in-dynamics
#20
Nathan Ratliff, Franziska Meier, Daniel Kappler, Stefan Schaal
It has long been hoped that model-based control will improve tracking performance while maintaining or increasing compliance. This hope hinges on having or being able to estimate an accurate inverse dynamics model. As a result, substantial effort has gone into modeling and estimating dynamics (error) models. Most recent research has focused on learning the true inverse dynamics using data points mapping observed accelerations to the torques used to generate them. Unfortunately, if the initial tracking error is bad, such learning processes may train substantially off-distribution to predict well on actual observed acceleration rather than the desired accelerations...
December 2016: Big Data
journal
journal
48893
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"