There has been a great deal of interest in recent years on ranking query results in relational databases. This paper presents a novel method to rank objects (e.g., tuples) by exploiting the correlations among their attribute values. Given a query, each attribute value is assigned a score according to mutual occurrences with the query and its distribution status in the columns of the attribute. ...

USA Abstract This paper describes a classical logic for attribute-value (or feature description) languages which ate used in urfification grammar to describe a certain kind of linguistic object commonly called attribute-value structure (or feature structure). Tile algorithm which is used for deciding satisfiability of a feature description is based on a restricted deductive closure construction...

In this paper, the traditional k-modes clustering algorithm is extended by weighting attribute value matches in dissimilarity computation. The use of attribute value weighting technique makes it possible to generate clusters with stronger intra-similarities, and therefore achieve better clustering performance. Experimental results on real life datasets show that these value weighting based k-mo...

This paper addresses a new version of the exible ow line prob- lem, i.e., the budget constrained one, in order to determine the required num- ber of processors at each station along with the selection of the most eco- nomical process routes for products. Since a number of parameters, such as due dates, the amount of available budgets and the cost of opting particular routes, are imprecise (fuzz...

Nowadays, towns and villages usually try to get funds for community constructions by following empirical rules. It is not possible to predict the effectiveness. And in the previous researches related to community development, there is no decision support model built using mathematical planning for fund allocation. This study obtains index weights for community industrial development by applying...

k-anonymity is an important model in the field of privacy protection and it is an effective method to prevent privacy disclosure in micro-data release. However, it is ineffective for the attribute disclosure by the homogeneity attack. The existing models based on k-anonymity have solved this problem to a certain extent, but they did not distinguish the different values of the sensitive attribut...

Preface The work for this thesis has been carried out at Systems Analysis Laboratory at Helsinki University of Technology. I want to express my warmest thanks to my thesis supervisor, professor Raimo P. Hämäläinen, for his dynamic way to supervise me. I learned a lot during these years. It was a great pleasure to collaborate with Dr. Ahti Salo and Dr. Hans C. Vrolijk. Ahti provided me a good st...

Bottom Clause Propositionalization (BCP) is a recent propositionalization method which allows fast relational learning. Propositional learners can use BCP to obtain accuracy results comparable with Inductive Logic Programming (ILP) learners. However, differently from ILP learners, what has been learned cannot normally be represented in first-order logic. In this paper, we propose an approach an...