by
Mohamed Sharaf
on Feb 16, 2023 | Categories:
data exploration, Databases, Recommendations, Visualization
In this blog, we discuss the potential benefits of augmenting automated view recommendation solutions with query refinement techniques towards achieving insightful data exploration. Particularly, effective data exploration has been fueled by many approaches that rely on either view recommendation…
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by
Senjuti Basu Roy
on Oct 26, 2022 | Categories:
Recommendations
Given a large number of users’ preferences (numerical or ordinal scores, ranked order) over a large number of objects, returning top-k results entails selecting a small list/set containing exactly k objects that are most “appropriate “. In this article, I will investigate two alternatives for…
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by
Mohamed Mokbel
on Oct 6, 2016 | Categories:
Databases, Recommendations, Spatial, Systems
Self-driving cars, ride-sharing service (e.g., Uber and Lyft), and Pokemon Go are just three examples of recent disruptive applications that gained huge market share and publicity. It is expected that each self-driving car will generate 2 PB of data per year, with 10 Million of such cars by 2020.…
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by
Kostas Stefanidis, Eirini Ntoutsi, Haridimos Kondylakis
on Mar 10, 2015 | Categories:
Recommendations
With the growing complexity of the Web, users often find themselves overwhelmed by the mass of choices available. For example, shopping for DVDs or clothes online becomes more and more difficult, as the variety of offers increases rapidly and gets unmanageable. To facilitate users in their…
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