Agent-based problem solving methods in Big Data environment
This special issue particularly focuses on using agent-based methods to solve the complex computational problems arising in Big Data environments. It covers the recent advances in the areas of distributed problem solving, agent-based data mining, as ...
Multi-agent orienteering problem with time-dependent capacity constraints
In this paper, we formulate and study the Multi-agent Orienteering Problem with Time-dependent Capacity Constraints (MOPTCC). MOPTCC is similar to the classical orienteering problem at the single-agent level: given a limited time budget, an agent ...
Scalable approximating SVD algorithm for recommender systems
With the rapid development of Internet, the amount of information on the Web grows explosively, people often feel puzzled and helpless in finding and getting the information they really need. For overcoming this problem, recommender systems such as ...
Detecting cyberbullying in social networks using multi-agent system
State-of-the-art studies on cyberbullying detection, using text classification, predominantly take it for granted that streaming text can be completely labelled. However, the rapid growth of unlabelled data generated in real time from online content ...
Web usage mining based recommender systems using implicit heterogeneous data: A Particle Swarm Optimization based clustering approach
Recommender systems have become one of the necessary tools to help a web user find a potentially interesting resource based on their preferences. In implicit recommender systems, the recommendations are made based on the implicit information of the web ...
