5 citations · 13 across the 7 of their papers we have counts for
5 papers · 1 filter
Macro-optimization of email recommendation response rates harnessing individual activity levels and group affinity trends
Mohammed Korayem, Khalifeh Aljadda, Trey Grainger
Recommendation emails are among the best ways to re-engage with customers after they have left a website. While on-site recommendation systems focus on finding the most relevant it…
Application of Statistical Relational Learning to Hybrid Recommendation Systems
Shuo Yang, Mohammed Korayem, Khalifeh AlJadda +2
Recommendation systems usually involve exploiting the relations among known features and content that describe items (content-based filtering) or the overlap of similar users who i…
GELATO and SAGE: An Integrated Framework for MS Annotation
Khalifeh AlJadda, Rene Ranzinger, Melody Porterfield +6
Several algorithms and tools have been developed to (semi) automate the process of glycan identification by interpreting Mass Spectrometric data. However, each has limitations when…
Mining Massive Hierarchical Data Using a Scalable Probabilistic Graphical Model
Khalifeh AlJadda, Mohammed Korayem, Camilo Ortiz +7
Probabilistic Graphical Models (PGM) are very useful in the fields of machine learning and data mining. The crucial limitation of those models,however, is the scalability. The Baye…
PGMHD: A Scalable Probabilistic Graphical Model for Massive Hierarchical Data Problems
Khalifeh AlJadda, Mohammed Korayem, Camilo Ortiz +3
In the big data era, scalability has become a crucial requirement for any useful computational model. Probabilistic graphical models are very useful for mining and discovering data…