Content-Based Filtering
A recommendation system technique that suggests items similar to those a user has shown interest in, based on item features. Important for providing personalized recommendations and improving user satisfaction.
17 topics found for:
“recommendation systems”
Collaborative Filtering
A recommendation system technique that makes predictions about user interests based on preferences from many users. Essential for personalizing user experiences and improving recommendation accuracy.
Adaptive AI
AI systems that can dynamically adjust their behavior based on new data or changes in the environment. Important for developing systems that can respond to real-time changes and improve over time.
Recommendation Engine
A system that suggests products, services, or content to users based on their preferences and behavior. Essential for personalizing user experiences and increasing engagement and conversion rates.
SKOS
Simple Knowledge Organization System (SKOS) is a standard for representing knowledge organization systems such as thesauri, classification schemes, and taxonomies. Essential for enabling interoperability and sharing of structured knowledge across different systems.
Machine Learning
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
SOAP
Simple Object Access Protoco (SOAPl) is a protocol for exchanging structured information in web services. Crucial for enabling communication between applications over a network.
Social Foraging
The behavior of seeking information or resources based on social interactions and cues. Important for understanding how users gather information in social contexts and designing systems that support collaborative information seeking.
Knowledge Graphs
A network of real-world entities and their interrelations, organized in a graph structure, used to improve data integration and retrieval. Crucial for enhancing data connectivity and providing deeper insights.
Social Proof
A psychological phenomenon where people follow the actions of others in an attempt to reflect correct behavior for a given situation. Essential for designing interfaces and experiences that leverage social influence to guide user behavior and increase trust and engagement.
Naive Allocation
A heuristic where individuals evenly distribute resources across all options, regardless of their specific needs or potential. Useful for understanding and designing around simplistic decision-making strategies.
Illusion of Completeness
A cognitive bias where users believe they have explored all available content, even when more is present. Important for designing interfaces that clearly indicate the presence of additional content.
Data Science
An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Essential for driving data-informed decision making, predicting trends, and uncovering valuable insights in digital product design and development.
Train/Test
A method of splitting a dataset into two subsets: one for training a model and another for testing its performance. Fundamental for developing and evaluating machine learning models in digital product design.
Nielsen’s Heuristics
A set of ten general principles for user interface design created by Jakob Nielsen to improve usability. Essential for evaluating and improving user interface designs.
Egocentric Bias
A cognitive bias where people rely too heavily on their own perspective and experiences when making decisions. Important for designers to recognize and mitigate their own perspectives influencing design decisions.
Decision Paralysis
A state of overthinking and indecision that prevents making a choice, often due to too many options or uncertainty. Important for designing interfaces that simplify decision-making processes for users.