Abstract We analyze a large dataset of fully employed individuals gathered through incentive-compatible surveys to study who joins professional social network sites (SNS) such as LinkedIn. We test the conflicting…
Feature Engineering As the dataset contained rich information on each article (e.g., not only the full text but also a category label and topic tags), we could create multiple sets…
Ready to Buy a New Electric Car? Here’s What You Need to Know! Are you in the market for a new electric car? Awesome! EVs are rapidly becoming the most…
Electric Vehicles (EVs) vs. Gas-Powered Cars: Are EVs Worth the Investment? Electric vehicles are much better for the environment compared to gas-powered cars. However, many Americans are hesitant to buy…
Tagging is a popular way to organize stuff online (like videos and articles). People can add their own labels (tags) to things, which makes it easier to find them later.…
Point of Interest (POI) recommendation systems are systems designed to suggest interesting or relevant locations to users, especially in the context of location-based social networks (LBSNs). These systems have attracted…
Popularity bias in recommender systems is a problem where popular items are recommended more frequently, leading to less popular items being overlooked. This bias can be harmful for both users…
Imagine you're trying to crack a secret code hidden in a dataset. Maximum likelihood estimation (MLE) is like being a detective searching for the most likely suspect among a group…
Topic modeling is a technique in natural language processing (NLP) that aims to discover latent topics within a collection of documents. These topics are hidden patterns of co-occurring words that…
The Web's growing role in electronic and business transactions has pushed the advancement of recommender systems. A key reason for this progress is how easily the Web lets users share…
Navjeet Kaur