Testing the predictive power of variable history web usage

• Tipo: Artigo em Revista Científica Internacional
• Data: 2007

Autores

José Luís Moura Borges (Autor) FEUP; Levene, M (Autor) Outra

Revista

Título: Soft Computing

Vol. 11 Nº 8

Páginas: 717-727

ISSN: 1432-7643

Editora: Springer Nature

Indexação

ISI Web of Knowledge - 4 Citações

Scopus - 5 Citações

Outras Informações

ID Authenticus: P-004-9Z0

DOI: 10.1007/s00500-006-0115-1

Abstract (EN): We present two methods for testing the predictive power of a variable length Markov chain induced from a collection of user web navigation sessions. The collection of sessions is split into a training and a test set. The first method uses a chi(2) statistical test to measure the significance of the distance between the distribution of the probabilities assigned to the test trails by a Markov model build from the full collection of sessions and a model built from the training set. The statistical test measures the ability of the model to generalise its predictions to the unseen sessions from the test set. The second method evaluates the model ability to predict the last page of a navigation session based on the preceding pages viewed by recording the mean absolute error of the rank of the last occurring page among the predictions provided by the model. Experimental results conducted on both real and random data sets are reported and the results show that in most cases a second-order model is able to capture sufficient history to predict the next link choice with high accuracy.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11