Lower Bounds On The Efficiency Of Transforming Static Data Structures Into Dynamic Structures

In numerous computer applications there is a need of storing large sets of objects in such a way that some questions about those objects can be answered efficiently. Data structures that store such sets of objects can be either static (built for a fixed set of objects) or dynamic (insertions of new objects and deletions of existing objects can be performed). Especially for more complex searching problems as they arise in such fields as computational geometry, database design and computer graphics, only static data structures are available. This book aims at remedying this lack of flexibility by providing a number of general techniques for turning static data structures for searching problems into dynamic structures. Although the approach is basically theoretical, the techniques offered are often practically applicable. The book is written in such a way that it is readable for those who have some elementary knowledge of data structures and algorithms. Although this monograph was first published in 1983, it is still unique as a general treatment of methods for constructing dynamic data structures.

This first part presents chapters on models of computation, complexity theory, data structures, and efficient computation in many recognized sub-disciplines of Theoretical Computer Science.

In this paper we will investigate transformations that serve as tools in the design of new data structures. Specifically, we study general methods for converting static structures (in which all elements are known before any searches are performed) to dynamic structures (in which insertions of new elements can be mixed with searches). We will exhibit three classes of such transformations, each based on a different counting scheme for representing the integers, and then use a combinatorial model to show the optimality of many of the transformations. Issues such as online data structures and deletion of elements are also examined. To demonstrate the applicability of these tools, we will study six new data structures that have been developed by applying the transformations. (Author).

This volume contains articles accepted for presentation during The Intel ligent Information Processing and Web Mining Conference IIS:IIPWM'04 which was held in Zakopane, Poland, on May 17-20, 2004. This conference is a continuation of a series of 13 successful symposia and conferrences on Intel ligent Information Systems, organized by the Institute of Computer Science of Polish Academy of Sciences, devoted to new trends in (broadly understood) Artificial Intelligence. The idea of organizing such meetings dates back to 1992. Our main in tention guided the first, rather small-audience, workshop in the series was to resume the results gained in Polish scientific centers as well as contrast them with the research performed by Polish scientists working at the universities in Europe and USA and their foreign collaborators. This idea proved to be attractive enough that we decided to continue such meetings. As the years went by, the workshops has transformed into regular symposia devoted to such fields like Machine Learning, Knowledge Discovery, Natural Language Processing, Knowledge Based Systems and Reasoning, and Soft Computing (i. e. Fuzzy and Rough Sets, Bayesian Networks, Neural Networks and Evo lutionary Algorithms). At present, about 50 papers prepared by researches from Poland and other countries are usually presented. This year conference devotes much more attention to the newest devel opments in the area of Artificial Intelligence, related to broadly understood Web mining.

There is arguably no field in greater need of a comprehensive handbook than computer engineering. The unparalleled rate of technological advancement, the explosion of computer applications, and the now-in-progress migration to a wireless world have made it difficult for engineers to keep up with all the developments in specialties outside their own