This article introduces the use of a multi-instance genetic programming algorithm for modelling user preferences in web index recommendation systems.

This article introduces the use of a multi-instance genetic programming algorithm for modelling user preferences in web index recommendation systems.

Computational experiments show that, the MOG3PMI algorithm obtains the best results, solves problems of k-nearest neighbour algorithms, such as sparsity and ...

In this chapter we introduce MOG3P-MI, a multiobjective grammar guided genetic programming algorithm to handle multi-instance problems. In this algorithm, based ...

Abstract. The aim of this paper is to present a new tool of multi- ple instance learning which is designed using a grammar based genetic programming (GGP) ...

Nov 21, 2024 · This paper introduces the use of multi-objective evolutionary algorithms in multiple instance learning. In order to achieve this purpose, ...

The approach proposed developes user profiles based on evolutionary multi instance learning which determines what users find interesting and uninteresting by ...

This work focuses on the design of grammatical genetic programming models for solving different paradigm of learning applications with multiple instances. First ...

In this paper we introduce a novel model for providing users with recommendations about web index pages of their interests. The ap-.

A Web Page-Oriented Model of User Interests Mining and Recommendation · Multi-objective Genetic Programming for Multiple Instance Learning.