Short abstract, isn't it? P.A.C.S. numbers 05.20, 02.50, 87.10 1 Introduction Large Numbers "...the optimal tour displayed (see Figure 6) is the possible unique tour having one arc fixed from among 10 655 tours that are possible among 318 points and have one arc fixed. Assuming that one could possibly enumerate 10 9 tours per second on a computer it would thus take roughly 10 639 years of computing to establish the optimality of this tour by exhaustive enumeration." This quote shows the real difficulty of a combinatorial optimization problem. The huge number of configurations is the primary difficulty when dealing with one of these problems. The quote belongs to M.W Padberg and M. Grotschel, Chap. 9., "Polyhedral computations", from the book The Traveling Salesman Problem: A Guided tour of Combinatorial Optimization [124]. It is interesting to compare the number of configurations of real-world problems in combinatorial optimization with those large numbers arising in Cosmol...

Several clustering algorithms have been suggested to analyse genome expression data, but fewer solutions have been implemented to guide the design of clusteringbased experiments and assess the quality of their outcomes. A cluster validity framework provides insights into the problem of predicting the correct the number of clusters. This paper presents several validation techniques for gene expression data analysis. Normalisation and validity aggregation strategies are proposed to improve the prediction about the number of relevant clusters. The results obtained indicate that this systematic evaluation approach may significantly support genome expression analyses for knowledge discovery applications.

Introduction. 1.1. Information retrieval in the WWW. T he Internet and its associated WWW (World Wide Web) hypertext protocol have been experiencing an exponential growth during the past few years. Not only the number of users and Internet servers but also the amount of electronic information stored has been growing at an astounding pace. In spite of its popularity among publishers and users, the WWW doesn't seem to be entirely living up to expectations. With a growing number of pages and an increasing number of links, users are experiencing more and more difficulties in retrieving the information they require The retrieval of information from (electronic) databases and other information repositories has been the domain of the science of Information Retrieval (IR). Techniques and methods developed in IR have focused on indexing methods, automated retrieval by queries, query relevance improvement, database management, user inter

This study is designed to clarify important features of social network analysis for analyzing community-based activities in a CSCL setting. The theoretical and methodological background is social/communication network analysis, which is employed to identify and understand students' communication and interaction patterns when collaborating through wireless computer networking tools. Thirty-two students were given high-end laptops with access to the wireless Internet, and their use of and communicative patterns via these systems were gathered through a proxy server. Findings show that social influences, in the form of network prestige effects, strongly affected the likelihood and the extent to which information posted in the CSCL environment was shared by peers in this learning community.

Graph edit distance provides an error-tolerant way to measure distances between attributed graphs. The effectiveness of edit distance based graph classification algorithms relies on the adequate definition of edit operation costs. We propose a cost inference method that is based on a distribution estimation of edit operations. For this purpose we employ an Expectation Maximization algorithm to learn mixture densities from a labeled sample of graphs and derive edit costs that are subsequently applied in the context of a graph edit distance computation framework. We evaluate the performance of the proposed distance model in comparison to another recently introduced learning model for edit costs. 1.

Many methods for the description of social network structural properties are concerned with the dual notions of social position and social role. Common goals of these methods are to represent patterns in complex social network data in simplified form, to reveal sets of actors who are similarly embedded in networks of relations, and to describe the associations among relations in multirelational social networks. Often these representations take the form of a blockmodel. In a blockmodel actors are assigned to positions and network relations are presented among positions, rather than among actors, The literature on blockmodels is extensive and is overflowing with computation and applications of blockmodels. However, there is a surprising lack of attention to two very important aspects of blockmodel analyses: the interpretation and evaluation of the results. The purpose of this paper is to focus on these topics, primarily reviewing and synthesizing the approaches to interpretation and evaluation currently in use.

Although graph matching and graph edit distance computation have become areas of intensive research recently, the automatic inference of the cost of edit operations has remained an open problem. In the present paper we address the issue of learning graph edit distance cost functions for numerically labeled graphs from a corpus of sample graphs. We propose a system of self-organizing maps that represent the distance measuring spaces of node and edge labels. Our learning process is based on the concept of self-organization. It adapts the edit costs in such a way that the similarity of graphs from the same class is increased while the similarity of graphs from different classes decreases. The learning procedure is demonstrated on two different applications involving line drawing graphs and graphs representing diatoms, respectively.

Clustering is crucial for many NLP tasks and applications. However, evaluating the results of a clustering algorithm is hard. In this paper we focus on the evaluation setting in which a gold standard solution is available. We discuss two existing information theory based measures, V and VI, and show that they are both hard to use when comparing the performance of different algorithms and different datasets. The V measure favors solutions having a large number of clusters, while the range of scores given by VI depends on the size of the dataset. We present a new measure, NVI, which normalizes VI to address the latter problem. We demonstrate the superiority of NVI in a large experiment involving an important NLP application, grammar induction, using real corpus data in English, German and Chinese. 1

Turbine balancing is an important and regular maintenance operation at airline companies. Because of manufacturing inaccuracies, variations occur in the weights of the blades that can, in turn, lead to significant out-of-balance forces on the engine. The overall time required for balancing can be significantly decreased if the best placement of turbine blades is first determined mathematically. This problem is formulated as a variation of the quadratic assignment problem and a number of solution schemes are investigated. A neighbourhood search algorithm is found to significantly outperform the other solution approaches when applied to data from a major South Pacific airline. The neighbourhood search algorithm can be combined with various strategies to initialize starting points. The use of starting points obtained from a Lagrangean dual scheme is shown to improve results for large problems. Scope and Purpose The balancing of turbines is a regular maintenance operation at airlines. Ty...

ABSTRACT: This paper examines the degree to which the constraints imposed by various social contexts influence social interaction. We draw on two data sets. In each, we compare the patterning of interaction of the same individuals across different contexts. If minimal constraints are imposed, then the interaction patterns among the individuals in the two contexts should be similar. But if one of the contexts involves major constraints, then interaction patterns in the two should differ. The results suggest further that the constraints found in any context are not unlimited in their impact. Moreover, individuals who can, apparently do manipulate the context to minimize the constraint imposed by the context.