Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2009

Autores

Luis Torgo (Autor) FCUP; Welma Pereira (Autor) Outra; Carlos Soares (Autor) FEP

Ata de Conferência Internacional

Título: Progress in Artificial Intelligence: Proceedings of the 14th Portuguese Conference on Artificial Intelligence, EPIA2009

Páginas: 435-446

14th EPIA - Portuguese Conference on Artificial Intelligence - EPIA 2009

Universidade de Aveiro, Portugal, 12 a 15 de Outubro de 2009

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 1 Citação

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-003-RW4

DOI: 10.1007/978-3-642-04686-5_36

Abstract (EN): This paper describes a data mining approach to the problem of detecting erroneous foreign trade transactions in data collected by the Portuguese Institute of Statistics (INE). Erroneous transactions are a minority, but still they have an important impact: on the official statistics produced by INE. Detecting these rare errors is a manual, time-consuming task, which is constrained by a limited amount of available resources (e.g. financial, human). These constraints are common to many other data analysis problems (e.g. fraud detection). Our previous work addresses this issue by producing a ranking of outlyingness that allows a better management of the available resources by allocating them to the most, relevant cases. It is based on an adaptation of hierarchical clustering methods for outlier detection. However, the method cannot be applied to articles with a small number of transactions. In this paper, we complement the previous approach with some standard statistical methods for outlier detection for handling articles with few transactions. Our experiments clearly show its advantages in terms of the criteria, outlined by INE for considering any method applicable to this business problem. The generality of the approach remains to be tested in other problems which share the same constraints (e.g. fraud detection).

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12