Context Matters: Why Aren’t You Leveraging Items’ Context to Boost Your Recommender Model?
Data sparsity is one of the biggest challenges in recommender systems. A promising solution to alleviate this problem is to rely on auxiliary sources...
Recent Posts
The Web Conference 2019 in San Francisco
In May 2019, Hady traveled to San Francisco for the Web Conference 2019 (previously the conference series was known as World Wide Web or...
Introduction to CSVPL
Here in Preferred.AI, much of our work involves processing and manipulating data. We regularly find ourselves wanting to explore a given dataset quickly and...
Consequential Associations
On 22 April 2019, Preferred.AI minted a new PhD. Trong Le passed the defense of his PhD dissertation, entitied “Modeling Sequential and Basket-Oriented Associations...
KL Diversion
In an attempt to build bridges, Preferred.AI crossed the bridge and conducted a data science meetup at Kuala Lumpur (KL), Malaysia on 16 March...
Aloha, AAAI-2019
In January 2019, four members of Preferred.AI travelled to the AAAI-19 conference held in Honolulu, Hawaii to present 2 papers and 1 tutorial. As...
The Best Web Scraper for You: A Guide to Understanding Crawlers
In this age where new content is generated on the Web every second, it is only natural that we find ways to harness them....
AI for Preference Learning: Sentiment, Comparison, and Recommendation
Artificial Intelligence or AI is pervading many aspects of our lives, influencing the array of options we encounter and changing the way we make...
Getting High on Climbing
To begin the year 2019 on a high note, Preferred.AI went on a group outing to Climb Central, an indoor rock climbing gym at...
Crash Course on Data Science Pipeline
Building on the success of the premiere of Preferred.AI-designed enrichment course on Web Data Extraction & Regression Analysis Using Java, we staged another run...
