pinecone/core-2020-05-10-deduplication huggingface dataset:
Clustering in P2P exchanges and consequences on performances.

We propose here an analysis of a rich dataset which gives an exhaustive and dynamic view of the exchanges processed in a running eDonkey system. We focus on correlation in term of data exchanged by peers having provided or queried at least one data in common. We introduce a method to capture these correlations (namely the data clustering), and study it in detail. We then use it to propose a very simple and efficient way to group data into clusters and show the impact of this underlying structure on search in typical P2P systems. Finally, we use these results to evaluate the relevance and limitations of a model proposed in a previous publication. We indicate some realistic values for the parameters of this model, and discuss some possible improvements
Evaluating DHT-Based Service Placement for Stream Based Overlays

<i>Stream-based overlay networks</i> (SBONs) are one approach to implementing large-scale stream processing systems. A fundamental consideration in an SBON is that of <i>service placement</i>, which determines the physical location of in-network processing services or operators, in such a way that network resources are used efficiently. Service placement consists of two components: <i>node discovery</i>, which selects a candidate
 set of nodes on which services might be placed, and <i>node selection</i>, which chooses the particular node to host a service. By viewing the placement problem as the composition of these two processes we can trade-off quality and efficiency between them. A bad discovery scheme can yield a good placement, but at the cost of an expensive selection mechanism.
     Recent work on operator placement [3, 9] proposes to leverage routing paths in a distributed hash table (DHT) to obtain a set of candidate nodes for service placement. We evaluate the appropriateness of using  DHT routing paths for service placement in an SBON, when aiming to minimize network usage. For this, we consider two DHT-based algorithms for node discovery, which use either the <i>union</i> or <i>intersection</i> of DHT routing paths in the SBON, and compare their performance to other techniques. We show that current DHT-based schemes are actually rather poor node discovery algorithms, when minimizing network utilization. An efficient DHT may not traverse enough hops to obtain a sufficiently large candidate set for placement. The union of DHT routes may result in a low-quality set of discovered nodes that requires an expensive node selection algorithm. Finally, the intersection of DHT routes relies on route convergence, which prevents the placement of services with a large fan-in.Engineering and Applied Science
A new color constancy algorithm based on the histogram of feasible mappings

International Conference on Image Analysis and Recognition (ICIAR), 2005, Toronto (Canada)Color is an important cue both in machine vision and image processing applications, despite its dependence upon illumination changes. We propose a color constancy algorithm that estimates both the set and the likelihood of feasible color mappings in respect to their frequency and effectiveness. The best among this set is selected to rendered back image colors as seen under a canonical light. Experiments were done to evaluate its performance compared to Finlayson’s 2D gamut–mapping algorithm, outperforming it. Our approach is a helpful alternative wherever illumination is poorly known since it employs only image data.This work was supported by the project 'Integration of robust perception, learning, and navigation systems in mobile robotics' (J-0929).Peer Reviewe
Agilo: A Highly Flexible Groupware Framework

Today there exist many frameworks for the development of synchronous groupware applications. Although the domain of these applications is very heterogeneous, existing frameworks provide only limited flexibility to integrate diverse groupware applications in a meaningful way. We identify five variation points that a groupware framework needs to offer in a flexible way in order to facilitate the integration of diverse groupware applications. Based on these variation points, we propose a groupware framework called Agilo that tries to overcome the limited flexibility of existing frameworks by offering multiple realizations of these variation points and providing a modular architecture to simplify the integration of applications and the extensibility and adaptability to different application and integration requirements.
Finding Resource Bounds in the Presence of Explicit Deallocation

A software program requesting a resource that is not available usually raises an out-of-resource exception. Component software is software that has been assembled from standardized, reusable components which, in turn, may also composed from other components. Due to the independent development and reuse of components, component software has a high risk of causing out-of-resource exceptions. We present a small component language and develop a type system which can statically prevent this type of errors .

This work continues our previous works by including explicit deallocation. We prove that the type system is sound with respect to safe deallocation and that sharp resource bounds can be computed statically
On refinement of software architectures

Although increasingly popular, software component techniques still lack suitable formal foundations on top of which rigorous methodologies for the description and analysis of software architectures could be built. This paper aims to contribute in this direction: building on previous work by the authors on coalgebraic semantics, it discusses component refinement at three different but interrelated levels: behavioural, syntactic, i.e., relative to component interfaces, and architectural. Software architectures are defined through component aggregation. On the other hand, such aggregations, no matter how large and complex they are, can also be dealt with as components themselves, which paves the way to a discipline of hierarchical design. In this context, a major contribution of this paper is the introduction of a set of rules for architectural refinement. Keywords: Software component, software architecture, refinement, coalgebra.Fundação para a Ciência e a Tecnologia (FCT
High efficiency realization for a wide-coverage unification grammar

We give a detailed account of an algorithm for efficient tactical generation from underspecified logical-form semantics, using a wide-coverage grammar and a corpus of real-world target utterances. Some earlier claims about chart realization are critically reviewed and corrected in the light of a series of practical experiments. As well as a set of algorithmic refinements, we present two novel techniques: the integration of subsumption-based local ambiguity factoring, and a procedure to selectively unpack the generation forest according to a probability distribution given by a conditional, discriminative model
ArchiTRIO: a UML-compatible language for architectural description and its formal semantics

ArchiTRIO [14] is a formal language, which complements
UML 2.0 concepts with a formal, logic-based notation that allows users
to state system-wide properties, both static and dynamic, including real-
time constraints. In this paper we present the semantics of the core con-
cepts of the ArchiTRIO language. As the core elements of ArchiTRIO
coincide with those of UML 2.0 (operation, interface, port, class), the
semantics of ArchiTRIO provides also a formal definition for the basic
concepts on which UML 2.0 is built
Polynomial interpretations as a basis for termination analysis of logic programs

This paper introduces a new technique for termination analysis of definite logic programs based on polynomial interpretations. The principle of this technique is to map each function and predicate symbol to a polynomial over some domain of natural numbers, like it has been done in proving termination of term rewriting systems. Such polynomial interpretations can be seen as a direct generalisation of the traditional techniques in termination analysis of LPs, where (semi-) linear norms and level mappings are used. Our extension generalises these to arbitrary polynomials. We extend a number of standard concepts and results on termination analysis to the context of polynomial interpretations. We propose a constraint based approach for automatically generating polynomial interpretations that satisfy termination conditions.status: publishe
Guard and continuation optimization for occurrence representations of CHR

Constraint Handling Rules (CHR) is a high-level rule-based language extension, commonly embedded in Prolog. We introduce a new occurrence representation of CHR programs, and a new operational semantics for occurrence representations, equivalent to the widely implemented refined operational semantics. The occurrence representation allows in a natural way to express guard and continuation optimizations, which remove redundant guards and eliminate redundant code for subsumed occurrences. These optimizations allow CHR programmers to write self-documented rules with a clear logical reading. We show correctness of both optimizations, present an implementation in the K.U.Leuven CHR compiler, and discuss speedup measurements.status: publishe
An experiment with association rules and classification: post-bagging and conviction

In this paper we study a new technique we call post-bagging, which consists in
resampling parts of a classification model rather then the data. We do
this with a particular kind of model: large sets of classification association rules, and
in combination with ordinary best rule and weighted voting approaches.
We empirically evaluate the effects of the technique in terms of classification accuracy.
We also discuss the predictive power of different metrics used for association rule mining, such as confidence, lift, conviction and X². We conclude that, for the described experimental conditions, post-bagging improves classification results and that the best metric is conviction.Programa de Financiamento Plurianual de Unidades de I & D.Comunidade Europeia (CE). Fundo Europeu de Desenvolvimento Regional (FEDER).Fundação para a Ciência e a Tecnologia (FCT) - POSI/SRI/39630/2001/Class Project
CLASSIC'CL: An integrated ILP system

A novel inductive logic programming system, called Classic'cl is presented. Classic'cl integrates several settings for learning, in particular learning from interpretations and learning from satisfiability. Within these settings, it addresses descriptive and probabilistic modeling tasks. As such, Classic'cl (C-armr, cLAudien, icl-S(S)at, ICI, and CLI-pad) integrates several well-known inductive logic programming systems such as Claudien, Warmr (and its extension C-armr), ICL, ICL-SAT, and LLPAD. We report on the implementation, the integration issues as well as on some experiments that compare Classic'cl with some of its predecessors.status: publishe
Defensive universal learning with experts

This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedback from the actions actually chosen (bandit setup), (b) it can be applied with countably infinite expert classes, and (c) it copes with losses that may grow in time appropriately slowly. We prove loss bounds against an adaptive adversary. From this, we obtain a master algorithm for “reactive” experts problems, which means that the master’s actions may influence the behavior of the adversary. Our algorithm can significantly outperform standard experts algorithms on such problems. Finally, we combine it with a universal expert class. The resulting universal learner performs – in a certain sense – almost as well as any computable strategy, for any online decision problem. We also specify the (worst-case) convergence speed, which is very slow
Robust Bayesian Linear Classifier Ensembles

The original publication is available at\ud
http://www.springerlink.comEnsemble classifiers combine the classification results of several classifiers.\ud
Simple ensemble methods such as uniform averaging over a set of models\ud
usually provide an improvement over selecting the single best model. Usually probabilistic\ud
classifiers restrict the set of possible models that can be learnt in order to\ud
lower computational complexity costs. In these restricted spaces, where incorrect\ud
modelling assumptions are possibly made, uniform averaging sometimes performs\ud
even better than bayesian model averaging. Linear mixtures over sets of models provide\ud
an space that includes uniform averaging as a particular case. We develop two\ud
algorithms for learning maximum a posteriori weights for linear mixtures, based on\ud
expectation maximization and on constrained optimization. We provide a nontrivial\ud
example of the utility of these two algorithms by applying them for one dependence\ud
estimators.We develop the conjugate distribution for one dependence estimators and\ud
empirically show that uniform averaging is clearly superior to BMA for this family\ud
of models. After that we empirically show that the maximum a posteriori linear mixture\ud
weights improve accuracy significantly over uniform aggregation.Peer reviewe
A comparison of approaches for learning probability trees

Acceptance rate = 20%Probability trees (or Probability Estimation Trees, PET's) are decision trees with probability distributions in the leaves. Several alternative approaches for learning probability trees have been proposed but no thorough comparison of these approaches exists.
In this paper we experimentally compare the main approaches using the relational decision tree learner Tilde (both on non-relational and on relational datasets). Next to the main existing approaches, we also consider a novel variant of an existing approach based on the Bayesian Information Criterion (BIC). Our main conclusion is that overall trees built using the C4.5-approach or the C4.4-approach (C4.5 without post-pruning) have the best predictive performance. If the number of classes is low, however, BIC performs equally well. An additional advantage of BIC is that its trees are considerably smaller than trees for the C4.5- or C4.4-approach.status: publishe
Protein sequence pattern mining with constraints

Considering the characteristics of biological sequence databases, which typically have a small alphabet, a very long length and a relative small size (several hundreds of sequences), we propose a new sequence mining algorithm (gIL). gIL was developed for linear sequence pattern mining and results from the combination of some of the most efficient techniques used in sequence and itemset mining. The algorithm exhibits a high adaptability, yielding a smooth and direct introduction of various types of features into the mining process, namely the extraction of rigid and arbitrary gap patterns. Both breadth or a depth first traversal are possible. The experimental evaluation, in synthetic and real life protein databases, has shown that our algorithm has superior performance to state-of-the art algorithms. The use of constraints has also proved to be a very useful tool to specify user interesting patternsFundação para a Ciência e a Tecnologia (FCT
A kernel based method for discovering market segments in beef meat

9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, PortugalIn this paper we propose a method for learning the reasons why groups of consumers prefer some food products instead of others of the same type. We emphasize the role of groups given that, from a practical point of view, they may represent market segments that demand different products. Our method starts representing people’s preferences in a metric space; there we are able to define a kernel based similarity function that allows a clustering algorithm to discover significant groups of consumers with homogeneous tastes. Finally in each cluster, we learn, with a SVM, a function that explains the tastes of the consumers grouped in the cluster. To illustrate our method, a real case of consumers of beef meat was studied. The panel was formed by 171 people who rated 303 samples of meat from 101 animals with 3 different aging period
Generating dynamic higher-order Markov models in web usage mining

Markov models have been widely used for modelling users’ web navigation behaviour. In previous work we have presented a dynamic clustering-based Markov model that accurately represents second-order transition probabilities given by a collection of navigation sessions. Herein, we propose a generalisation of the method that takes into account higher-order conditional probabilities. The method makes use of the state cloning concept together with a clustering technique to separate the navigation paths that reveal differences in the conditional probabilities. We report on experiments conducted with three real world data sets. The results show that some pages require a long history to understand the users choice of link, while others require only a short history. We also show that the number of additional states induced by the method can be controlled through a probability threshold parameter
3D Freehand Ultrasound Reconstruction based on Probe Trajectory

3D freehand ultrasound imaging is a very attractive technique in medical examinations and intra-operative stage for its cost and field of view capacities. This technique produces a set of non parallel B-scans which are irregularly distributed in the space. Reconstruction amounts to computing a regular lattice volume and is needed to apply conventional computer vision algorithms like registration. In this paper, a new 3D reconstruction method is presented, taking explicitly into account the probe trajectory. Experiments were conducted on different data sets with various probe motion types and indicate that this technique outperforms classical methods, especially on low acquisition frame rate
Pattern-based Analysis of the Control-Flow Perspective of UML Activity Diagram

The Unified Modelling Language (UML) is a well-known family of notations for software modelling. Recently, a new version of UML has been released. In this paper we examine the Activity Diagrams notation of this latest version of UML in terms of a collection of patterns developed for assessing control flow capabilities of languages used in the area of process-aware information systems. The purpose of this analysis is to assess relative strengths and weaknesses of control flow specification in Activity Diagrams and to identify ways of addressing potential deficiencies. In addition, the pattern-based analysis will yield typical solutions to practical process modelling problems and expose some of the ambiguities in the current UML 2.0 draft adopted specification
Crympix: Cryptographic multiprecision library

This paper delineates the results gained throughout the development of a cryptographic multiprecision1 integer library, CRYMPIX. To obtain the know-how for cryptographic computation and thus being able to create the high level cryptographic protocols in an in-housefashion are the main reasons of this development. CRYMPIX is mainly designed to supply code readability and portability plus an increased performance over other similar libraries. The whole work is achieved by detailed investigation of current algorithms and multi-precision libraries. The selected algorithms are discussed by means of efficiency and various implementation techniques. The comparative performance measurements of CRYMPIX against other multiprecision libraries show that the overall performance of CRYMPIX is not behind its predecessors if not superior
Optimal control for real-time feedback rate-monotonic schedulers

This paper presents an optimal control scheme for a real-time feedback control rate-monotonic scheduling (FC-RMS) system. We consider two-version tasks composed of a mandatory and an optional part to be scheduled according to the FC-RMS. In FC-RMS, the controller provides a feedback strategy for deciding about the execution or rejection of the optional sub-tasks. By modeling the task execution times as random variables, we first find the statistical model of FC-RMS and then we design a pure optimal controller and an optimal controller with feedforward integral compensation. The comparison of these two schemes with common Proportional-Integral-Derivative (PID) controller highlights the benefit of the optimal scheme with integral compensation. The results are demonstrated through the real implementation of FC-RMS on RT-Linux
Fusion of local and regional approaches for on-line signature verification

Proceedings of International Wokshop on Biometric Recognition Systems, IWBRS 2005, Beijing.The final publication is available at Springer via http://dx.doi.org/10.1007/11569947_24Function-based methods for on-line signature verification are studied. These methods are classified into local and regional depending on the features used for matching. One representative method of each class is selected from the literature. The selected local and regional methods are based on Dynamic Time Warping and Hidden Markov Models, respectively. Some improvements are presented for the local method aimed at strengthening the performance against skilled forgeries. The two methods are compared following the protocol defined in the Signature Verification Competition 2004. Fusion results are also provided demonstrating the complementary nature of these two approaches.This work has been supported by Spanish MCYT TIC2003-08382-C05-01 and by European Commission IST-2002-507634 Biosecure NoE project
Group-based replication of on-line transaction processing servers

Several techniques for database replication using group communication have recently been proposed, namely, the Database State Machine, Postgres-R, and the NODO protocol. Although all rely on a totally ordered multicast for consistency, they differ substantially on how multicast is used. This results in different performance trade-offs which are hard to compare as each protocol is presented using a different load scenario and evaluation method. In this paper we evaluate the suitability of such protocols for replication of On-Line Transaction Processing (OLTP) applications in clusters of servers and over wide area networks. This is achieved by implementing them using a common infra-structure and by using a standard workload. The results allows us to select the best protocol regarding performance and scalability in a demanding but realistic usage scenario.Projecto STRONGRE (POSI/CHS/41285/2001) 
financiado pela Fundação para a Ciência e a Tecnologia (FCT)
Improving the SLA-based management of QoS for secure multimedia services

his paper proposes to integrate security parameters into the Service Level Specification (SLS) template proposed in the Tequila project to improve SLA-based management of QoS [8], [21]. Integrating those parameters in the QoS part of the Service Level Agreement (SLA) specification is essential in particular for secure multimedia services since the QoS is negotiated when the multimedia service is deployed. Security mechanisms need to be negotiated at deployment time when sensible multimedia information is exchanged. In this paper we show that including security parameters in the SLA specification improves the SLA-based management of QoS and therefore the negotiation, deployment and use of the secure multimedia service. The parameters this paper proposes to integrate have the advantage to be understandable by both the end-users and service providers