Demystifying big data analytics for business intelligence through the lens of marketing mix

S Fan, RYK Lau, JL Zhao - Big Data Research, 2015 - Elsevier
Big data analytics have been embraced as a disruptive technology that will reshape
business intelligence, which is a domain that relies on data analytics to gain business …

Recommender systems—beyond matrix completion

D Jannach, P Resnick, A Tuzhilin… - Communications of the …, 2016 - dl.acm.org
Recommender systems â•fl beyond matrix completion Page 1 94 COMMUNICATIONS OF THE
ACM | NOVEMBER 2016 | VOL. 59 | NO. 11 review articles THE USE OF recommender systems …

Heterogeneous information network embedding for recommendation

C Shi, B Hu, WX Zhao, SY Philip - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Due to the flexibility in modelling data heterogeneity, heterogeneous information network
(HIN) has been adopted to characterize complex and heterogeneous auxiliary data in …

Measuring the business value of recommender systems

D Jannach, M Jugovac - ACM Transactions on Management Information …, 2019 - dl.acm.org
Recommender Systems are nowadays successfully used by all major web sites—from e-
commerce to social media—to filter content and make suggestions in a personalized way …

[CITAZIONE][C] Recommender Systems: An Introduction

D Jannach - 2010 - books.google.com
In this age of information overload, people use a variety of strategies to make choices about
what to buy, how to spend their leisure time, and even whom to date. Recommender …

Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer

A Gogleva, D Polychronopoulos, M Pfeifer… - Nature …, 2022 - nature.com
Resistance to EGFR inhibitors (EGFRi) presents a major obstacle in treating non-small cell
lung cancer (NSCLC). One of the most exciting new ways to find potential resistance …

When does retargeting work? Information specificity in online advertising

A Lambrecht, C Tucker - Journal of Marketing research, 2013 - journals.sagepub.com
Firms can now offer personalized recommendations to consumers who return to their
website, using consumers' previous browsing history on that website. In addition, online …

How should I explain? A comparison of different explanation types for recommender systems

F Gedikli, D Jannach, M Ge - International Journal of Human-Computer …, 2014 - Elsevier
Recommender systems help users locate possible items of interest more quickly by filtering
and ranking them in a personalized way. Some of these systems provide the end user not …

What recommenders recommend: an analysis of recommendation biases and possible countermeasures

D Jannach, L Lerche, I Kamehkhosh… - User Modeling and User …, 2015 - Springer
Most real-world recommender systems are deployed in a commercial context or designed to
represent a value-adding service, eg, on shop** or Social Web platforms, and typical …

Recommendation quality, transparency, and website quality for trust-building in recommendation agents

M Nilashi, D Jannach, O bin Ibrahim… - Electronic Commerce …, 2016 - Elsevier
Trust is a main success factor for automated recommendation agents on e-commerce sites.
Various aspects can contribute to the development of trust toward such an agent, including …