2016 Impact factor 1.862
Special Topics

EPJ Data Science Highlight - Discovering temporal regularities in retail customers’ shopping behaviour

(image via Pixabay, CC0 Creative Commons)

Why do we buy certain items when we buy them? A new study published in EPJ Data Science analyzes personal retail data to extract a temporal purchasing profile, which is able to summarize whether and when a customer makes a purchase. Its results show that certain patterns and types of shoppers are detectable, which can be used both by customers to enable personalized services, and by the retail market chain for providing offers and discounts tailored to the individual shoppers personal temporal profile.

(Guest post by Riccardo Guidotti and Anna Monreale, originally published on the SpringerOpen blog)

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EPJ H Highlight - Once upon a time, an exoplanet was discovered

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Mayor and Queloz in front of the dome of the EULER 1.2 m-telescope at La Silla Observatory.

Personal recollections of an astrophysicist shed new light on the 1995 discovery on 51 Pegasi b

In recent history, a very important achievement was the discovery, in 1995, of 51 Pegasi b, the first extrasolar planet ever found around a normal star other than the Sun. In a paper published in EPJ H, Davide Cenadelli from the Aosta Valley Astronomical Observatory (Italy) interviews Michel Mayor from Geneva Observatory (Switzerland) about his personal recollections of discovering this exoplanet. They discuss how the development of better telescopes made the discovery possible. They also delve into how this discovery contributed to shaping a new community of scholars pursuing this new field of research. In closing, they reflect upon the cultural importance that the 51 Pegasi b discovery had in terms of changing our view of the cosmos.

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EPJ Data Science Highlight – The science behind what makes a bestselling book

Photo by Anastasia Zhenina on Unsplash

Books that are fiction, thrillers or mysteries, have high initial sales numbers and are released around Christmas are more likely to be bestsellers, according to a study published in EPJ Data Science

(This post was originally published on the SpringerOpen blog)

A team of researchers from Northeastern University, Boston, used a big data approach to investigate what makes a book successful. By evaluating data from the New York Times Bestseller Lists from 2008 to 2016, they developed a formula to predict if a book would be a bestseller.

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Managing Editors
Agnès Henri (EDP Sciences) and Sabine Lehr (Springer-Verlag)
Dear Sabine and Isabelle,
Thank you so much for all your help and excellent work you did on the EPJ ST volume "Nonlinear Dynamics of Deterministic and Stochastic Systems: Unraveling Complexity". This was a great experience and collaboration.

Alexander Neiman (on behalf of the guest editors), Ohio University, Athens, USA
Editor EPJ Special Topics 222/10, 2013

ISSN: 1951-6355 (Print Edition)
ISSN: 1951-6401 (Electronic Edition)

© EDP Sciences and Springer-Verlag