Probabilistic Topic Models and User Behavior
Explore latent thematic structures in document collections and user behavior data. Learn how topic modeling algorithms can enhance predictions and understanding of collection organization.
Modeling User Fatigue for Sequential Recommendation - Session M3.6
Explore innovative approaches to modeling user fatigue in sequential recommendation systems, enhancing user experience and engagement in digital platforms.
Behavior-Contextualized Item Preference Modeling for Multi-Behavior Recommendation
Explore advanced techniques in multi-behavior recommendation systems, focusing on behavior-contextualized item preference modeling for improved personalization and accuracy.
Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation - Session M3.5
Explore critical insights into beyond-accuracy performance metrics in next basket recommendation systems, challenging current assumptions and methodologies.
Leveraging User Behavior Insights to Enhance Search Relevance
Unlock the power of user behavior insights to optimize search relevance. Learn to capture clickstream data, analyze user interactions, and continuously improve search strategies for better user experiences.
Predicting Impending Exposure to Malicious Content from User Behavior
Explore proactive cybersecurity through user behavior analysis, enabling real-time prediction and prevention of malicious content exposure during browsing sessions.
Social Engineering: Training the Human Firewall Against Phishing Attacks
Explore research on psychological factors behind phishing susceptibility and learn strategies to improve security education and measure risk in your organization.
Who's in Control: Human or Machine? - Behavioral Detection in Cybersecurity
Explore advanced behavioral detection methods for protecting critical web APIs against sophisticated attacks, focusing on user behavior analysis and biometric detection techniques.
Google Analytics - A Beginner's Guide
Learn to navigate Google Analytics, understand website traffic, and gain insights on audience, acquisition, and behavior to improve your online presence and marketing strategies.
A Day in the Life of an Enterprise Customer - Understanding Enterprise SaaS Expectations
Explore enterprise customer expectations for SaaS apps and gain insights into how they want to utilize your product, enhancing your understanding of their perspective.
Knowing Your App Buyers - Profiles and Purchasing Patterns
Explore app buyer profiles, purchasing patterns, and regional trends to gain practical insights for optimizing your app's monetization strategy.
Improving App Engagement and Retention - Playtime 2016
Discover tools and strategies to analyze user behavior, improve app engagement, and boost retention. Learn from successful developers and implement best practices for your Android app.
Grow Your Business with Player Analytics for Mobile Games
Discover how Player Analytics provides game developers with crucial insights into player behavior, spending patterns, and churn prediction to optimize gameplay and boost business growth.
Driving Buyer Behavior with IAP and Subscriptions - KPI Guide for Google Play Apps and Games
Explore key monetization metrics for Google Play apps, including buyer conversion, revenue per user, and subscriber engagement, to optimize in-app purchases and subscriptions.
How to Build an Adaptive, Performant Web App
Discover responsive design principles and data-driven strategies to create adaptive web apps that enhance user engagement through personalized experiences, testing, and feedback.
Treatment Effect Estimation for User Interest Exploration on Recommender Systems
Explore advanced techniques for estimating treatment effects in recommender systems, focusing on user interest exploration and long-term session recommendations.
Reinforcing Long-Term Performance in Recommender Systems with User-Oriented Exploration Policy
Explore advanced techniques for optimizing recommender systems through user-oriented exploration policies, focusing on enhancing long-term performance and session-based recommendations.
Disentangling ID and Modality Effects for Session-based Recommendation
Explore advanced techniques for disentangling identity and modality effects in session-based recommendation systems, focusing on long-term user behavior analysis and pattern recognition.
Improving YouTube Recommender Systems for Big Screen Users
Dive into the complexities of YouTube's recommendation systems, exploring challenges and solutions for delivering personalized content to billions of users across different platforms.
User Behavior Hashing for Audience Expansion - Deep Learning Approach
Explore deep learning-based hashing for sequential behavior data, utilizing Spark for large-scale preprocessing and distributed inference on Databricks with Pandas UDF.
Who Would You Like to Work With?
Explores how users search for and choose teammates on online platforms, revealing discrepancies between initial preferences and final choices, and the impact on team diversity and expertise distribution.