Vassilios S. Verykios

TAILOR: a record linkage toolbox

Data cleaning is a vital process that ensures the quality of data stored in real-world databases. Data cleaning problems are frequently encountered in many research areas, such as knowledge discovery in databases, data warehousing, system integration and e-services. The process of identifying the record pairs that represent the same entity (duplicate records), commonly known as record linkage, is one of the essential elements of data cleaning. In this paper, we address the record linkage problem by adopting a machine learning approach. Three models are proposed and are analyzed empirically. Since no existing model, including those proposed in this paper, has been proved to be superior, we have developed an interactive record linkage toolbox named TAILOR (backwards acronym for RecOrd LInkAge Toolbox). Users of TAILOR can build their own record linkage models by tuning system parameters and by plugging in in-house-developed and public-domain tools. The proposed toolbox serves as a framework for the record linkage process, and is designed in an extensible way to interface with existing and future record linkage models. We have conducted an extensive experimental study to evaluate our proposed models using not only synthetic but also real data. The results show that the proposed machine-learning record linkage models outperform the existing ones both in accuracy and in performance.

A knowledge based system for evaluation of option pricing algorithms

Presents the design and prototype implementation of a system built around the FINANZIA system that aims in the automated analysis and classification of option pricing algorithms based on experimental data. The main objective is to assist in the generation, storage and evaluation of large amounts of experimental option pricing data and to facilitate the identification of performance properties of the pricing algorithms with respect to the various problems. The analysis of the data is achieved using statistical and inductive logic techniques and the identified properties are used to expand the knowledge base. We demonstrate the use of the system in the context of a case study covering the pricing of American vanilla options in a Black & Scholes (1973) modeling framework.