Contextual bandit algorithms are a type of machine learning method used to make decisions based on both past results and current information. They help choose the best action by considering the context or situation at each decision point. These algorithms learn from feedback over time to improve future choices, balancing between trying new actions and…
Category: Data Science
Low-Rank Factorization
Low-Rank Factorisation is a mathematical technique used to simplify complex data sets or matrices by breaking them into smaller, more manageable parts. It expresses a large matrix as the product of two or more smaller matrices with lower rank, meaning they have fewer independent rows or columns. This method is often used to reduce the…
Process Discovery Algorithms
Process discovery algorithms are computer methods used to automatically create a process model by analysing data from event logs. These algorithms look for patterns in the recorded steps of real-life processes, such as how orders are handled in a company. The resulting model helps people understand how work actually happens, spot inefficiencies, and suggest improvements.
Automated Data Validation
Automated data validation is the process of using software tools to check that data is accurate, complete, and follows the required format before it is used or stored. This helps catch errors early, such as missing values, wrong data types, or values outside of expected ranges. Automated checks can be set up to run whenever…
Knowledge Graph Reasoning
Knowledge graph reasoning is the process of drawing new conclusions or finding hidden connections within a knowledge graph. A knowledge graph is a network of facts, where each fact links different pieces of information. Reasoning uses rules or algorithms to connect the dots, helping computers answer complex questions or spot patterns that are not immediately…
Graph-Based Clustering
Graph-based clustering is a method of grouping items by representing them as points, called nodes, and connecting similar ones with lines, called edges, to form a network or graph. The method looks for clusters, which are groups of nodes that are more closely linked to each other than to the rest of the network. This…
Subgraph Matching Algorithms
Subgraph matching algorithms are methods used to find if a smaller graph, called a subgraph, exists within a larger graph. They compare the structure and connections of the nodes and edges to identify matches. These algorithms are important in fields where relationships and patterns need to be found within complex networks, such as social networks,…
Graph-Based Recommendation Systems
Graph-Based Recommendation Systems use graphs to model relationships between users, items, and other entities. In these systems, users and items are represented as nodes, and their interactions, such as likes or purchases, are shown as edges connecting them. By analysing the structure of these graphs, the system can find patterns and suggest items to users…
Off-Policy Evaluation
Off-policy evaluation is a technique used to estimate how well a new decision-making strategy would perform, without actually using it in practice. It relies on data collected from a different strategy, called the behaviour policy, to predict the outcomes of the new policy. This is especially valuable when testing the new strategy directly would be…
Knowledge Graphs
A knowledge graph is a way of organising information that connects facts and concepts together, showing how they relate to each other. It uses nodes to represent things like people, places or ideas, and links to show the relationships between them. This makes it easier for computers to understand and use complex information, helping with…