Novel hybrid approaches for big data recommendations

2019 ◽  
pp. 71-109
Author(s):  
Abdul Kader Saiod ◽  
Darelle van Greunen
Keyword(s):  
Big Data ◽  
Hybrid Approaches

scholarly journals Recommendation Systems in the Big Data Era

2020 ◽  
Vol 8 (12s3) ◽  
pp. 80-85
Keyword(s):  
Social Media ◽  
Big Data ◽  
Recommendation System ◽  
Recommendation Systems ◽  
Rapid Progression ◽  
Specific Product ◽  
Hybrid Approaches ◽  
Social Media Platforms ◽  
Use Of Social Media ◽  
The Way

Rapid progression in technology and increasing use of social media platforms like Facebook, Instagram and Twitter has altered the way of articulating people’s judgment, observation and sentiments about specific product, services, and more. This leads to the production and accumulation of massive amount of data. Recommendation systems are getting impetus when it comes to find insights from this data to make decisions that can be represented in various statistical and graphical forms. They have proven useful in predicting or recommending products ranging from food, movies, restaurants etc. This paper presents an overview about recommendation systems and a review of generation of recommendation methods based on categories like contentbased, collaborative, and hybrid approaches. The paper will enlist the limitations which the present recommendation system faces and the possible improvements required in their capabilities to fit into a wider range of application areas.

Find Out About 'Big Data' to Track Outcomes

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  
Big Data

Find Out About 'Big Data' to Track Outcomes

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

“Big Data in Psychology: Methods and Applications”

2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  
Big Data

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org

When the Sample Is the Population: Big Data

PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  
Big Data

Little sensors, big data

2015 ◽  
Author(s):  
Kirsten Weir
Keyword(s):  
Big Data
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