Topic Modeling: A Hands-On Adventure in Big Data

2015 ◽  
pp. 113-158
Keyword(s):  
Big Data ◽  
Topic Modeling ◽  
Hands On

Ocean Acidification

2019 ◽  
pp. 146-168
Keyword(s):  
Big Data ◽  
Ocean Acidification ◽  
Hands On ◽  
Monitoring Effort

Absorption of CO2 by the waters of the oceans is making them acid, which is then detrimental to much ocean life like corals. There are technological solutions to the problems of the oceans; action is possible. Nevertheless, whatever is done it must be watched very carefully. This monitoring effort will take big data taken from space and from the air, but it will also take a major hands-on effort by people right at the water's surface. This chapter's story, “The Captain's Tale,” looks at what might happen when an effort that is closely watched by a great number of people runs into problems.

Integrating Big Data Services Into an Undergraduate MIS Curriculum

2017 ◽  
Vol 7 (2) ◽  
pp. 58-73 ◽  
Author(s):  
Scott Jensen
Keyword(s):  
Big Data ◽  
Real World ◽  
Data Science ◽  
Graduate Programs ◽  
Advanced Degree ◽  
Data Services ◽  
Hands On ◽  
Data Problem

There is an insatiable demand in industry for data scientists, and graduate programs and certificates are gearing up to meet this demand. However, there is agreement in the industry that 80% of a data scientist's work consists of the transformation and profiling aspects of wrangling Big Data; work that may not require an advanced degree. In this paper, the authors present hands-on exercises to introduce Big Data to undergraduate MIS students using the CoNVO Framework and Big Data tools to scope a data problem and then wrangle the data to answer questions using a real-world dataset. This can provide undergraduates with a single course introduction to an important aspect of data science.

Topic modeling for analysis of big data tensor decompositions

2018 ◽  
Author(s):  
Thomas S. Henretty ◽  
Muthu Baskaran ◽  
James Ezick ◽  
Richard Lethin ◽  
M. Harper Langston
Keyword(s):  
Big Data ◽  
Topic Modeling ◽  
Tensor Decompositions

Theorizing Supply Chains with Qualitative Big Data and Topic Modeling

2020 ◽  
Vol 56 (2) ◽  
pp. 7-18 ◽  
Author(s):  
Pratima (Tima) Bansal ◽  
Jury Gualandris ◽  
Nahyun Kim
Keyword(s):  
Big Data ◽  
Supply Chains ◽  
Topic Modeling

Enhancing Self-Reflection with Wearable Sensors Workshop

2015 ◽  
Vol 7 (3) ◽  
pp. 93-101
Author(s):  
Genovefa Kefalidou ◽  
Vicky Shipp ◽  
James Pinchin ◽  
Alan Dix
Keyword(s):  
Big Data ◽  
Wearable Sensors ◽  
Future Trends ◽  
Self Reflection ◽  
Wide Range ◽  
Hands On ◽  
New Form ◽  
Control And Management ◽  
Fine Tune

On 23rd September 2014 the authors organised a workshop on self-reflection tools and wearable sensors as part of the ACM MobileHCI 2014 Conference in Toronto, Canada. The aim of the workshop was to bring together professionals from different backgrounds to discuss the current adoption of such methodological tools, their challenges and future trends. Examples of own individuals' work were presented where such methodologies had been employed. Hands-on activities enabled us to fine- tune our understanding of those methodologies and unpack new potentials regarding their advantages and limitations. The workshop argued that the potential synthesis of such methodologies in collecting data will contribute to a new form of ‘Big Data on-the-go' while introducing ethical, control and management challenges. The workshop revealed interesting opportunities arising from the synergies of sensors and reflection tools with a wide range of applications. Finally, the workshop offered opportunities for experimenting with sensors and reflection tools on site.

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