waashk/dblp huggingface dataset:
a model for association rules based on clustering. association rules and clustering are fundamental data mining techniques used for different goals. we propose a unifying theory by proving association support and rule confidence can be bounded and estimated from clusters on binary dimensions. three support metrics are introduced: lower, upper and average support. three confidence metrics are proposed: lower, upper and average confidence. clusters represent a simple model that allows understanding and approximating association rules, instead of searching for them in a large transaction data set.
a new algorithm for gap constrained sequence mining. the sequence mining problem consists in finding frequent sequential patterns in a database of time-stamped events. several application domains require limiting the maximum temporal gap between events occurring in the input sequences. however pushing down such constraint is critical for most sequence mining algorithms.in this paper we describe ccsm (cache-based constrained sequence miner), a new level-wise algorithm that overcomes the troubles usually related to this kind of constraints. ccsm adopts an innovative approach based on k-way intersections of idlists to compute the support of candidate sequences. our k-way intersection method is enhanced by the use of an effective cache that stores intermediate idlists for future reuse. the reuse of intermediate results entails a surprising reduction in the actual number of join operations performed on idlists.ccsm has been experimentally compared with cspade, a state of the art algorithm, on several synthetically generated datasets, obtaining better or similar results in most cases.
interval-based robust statistical techniques for non-negative convex functions, with application to timing analysis of computer chips. in chip design, one of the main objectives is to decrease its clock cycle. on the design stage, this time is usually estimated by using worst-case (interval) techniques, in which we only use the bounds on the parameters that lead to delays. this analysis does not take into account that the probability of the worst-case values is usually very small; thus, the resulting estimates are over-conservative, leading to unnecessary over-design and under-performance of circuits. if we knew the exact probability distributions of the corresponding parameters, then we could use monte-carlo simulations (or the corresponding analytical techniques) to get the desired estimates. in practice, however, we only have partial information about the corresponding distributions, and we want to produce estimates that are valid for all distributions which are consistent with this information.in this paper, we develop a general technique that allows us, in particular, to provide such estimates for the clock time.
an enablement detection algorithm for open multiparty interactions. coordination amongst an arbitrary number of entities has become an important issue in recent years in fields such as e-commerce, web-based applications and so on. traditionally, classical client/server primitives have been used to implement synchronisation and communication. but, when more than two entities need to coordinate by means of those primitives, the coordination must be decomposed into a number of client/server biparty interactions, leading the programmer to the need of thinking in terms of the protocols needed to achieve properties like livenes, atomicity and so on. in this paper, we present an algorithm to perform enablement detection to implement open multiparty interactions. this primitive provides a high level of abstraction since the programmer can implement multiparty coordination without the need of thinking in terms of protocols.
graphical modelling for aspect oriented sa. aspect-oriented programming (aop) has emerged in recent years as a new paradigm for software development. prisma is an approach for developing complex and large software systems. it combines the aspect-oriented software development (aosd) and the component-based software development (cbsd) in an elegant and novel way achieving a better management of crosscutting-concerns and software reusability. prisma approach proposes the separation of concerns from the very beginning of the software life-cycle in order to introduce them as reusable aspects of software architecture. in this paper, we focus on how the prisma modelling tool supports the graphical modelling of aspects and weavings.
an initial analysis and presentation of malware exhibiting swarm-like behavior. the slammer, which is currently the fastest computer worm in recorded history, was observed to infect 90 percent of all vulnerable internets hosts within 10 minutes. although the main action that the slammer worm takes is a relatively unsophisticated replication of itself, it still spreads so quickly that human response was ineffective. most proposed countermeasures strategies are based primarily on rate detection and limiting algorithms. however, such strategies are being designed and developed to effectively contain worms whose behaviors are similar to that of slammer.in our work, we put forth the hypothesis that next generation worms will be radically different, and potentially such techniques will prove ineffective. specifically, we propose to study a new generation of worms called "swarm worms", whose behavior is predicated on the concept of "emergent intelligence". emergent intelligence is the behavior of systems, very much like biological systems such as ants or bees, where simple local interactions of autonomous members, with simple primitive actions, gives rise to complex and intelligent global behavior. in this manuscript we will introduce the basic principles behind the idea of "swarm worms", as well as the basic structure required in order to be considered a "swarm worm". in addition, we will present preliminary results on the propagation speeds of one such swarm worm, called the zachik worm. we will show that zachik is capable of propagating at a rate 2 orders of magnitude faster than similar worms without swarm capabilities.
pine - podium incremental neighbor evaluator for classifying spatial data. given a set of training data, nearest neighbor classification predicts the class value for an unknown tuple x by searching the training set for the k nearest neighbors to x and then classifying x according to the most frequent class among the k neighbors. each of the k nearest neighbors casts an equal vote for the class of x. in this paper, we propose a new algorithm, podium incremental neighbor evaluator (pine), in which nearest neighbors are weighted for voting. a metric called hobbit is used as the distance metric, and a data structure, the p-tree, is used for efficient implementation of the pine algorithm on spatial data. our experiments show that by using a gaussian podium function, pine outperforms the k-nearest neighbor (knn) method in terms of classification accuracy for spatial data. in addition, in the pine algorithm, all the instances are potential neighbors so that the value of k need not be pre-specified as in knn methods. by assigning high weights to the nearest neighbors and low (even zero) weights to other neighbors, high classification accuracy can be achieved.
editoral message: special track on coordination models, languages and applications. in last few years, the field of coordination models and languages has earned the respect of other computer science researchers as they recognized that the understanding of how parts can be efficiently organized as a ensemble is of prime importance to the design of distributed complex systems. the proliferation of network computing and mobile computation, and especially the ubiquity of the internet has made coordination one of the key areas in modern computing. this track aims at bringing together researchers working on applied issues in coordination, ranging from new models to applications.coordination is a multidisciplinary topic related to almost every aspect of computer science. from information security to mobile computation, from artificial intelligence to wireless communication, it is difficult to find a computer science field in which coordination does not play a central role. the glue between the many research agendas in the coordination field is the notion of a coordination model that represents and shapes the space of interaction among entities.the coordination track at the 2004 symposium on applied computing deliberately acknowledges this diversity, taking a broad perspective on the coordination topic. throughout the years, the track has served as a forum for cutting edge research on coordination. yet, the track's main focus is on practical (applied) aspects of coordination so as to fit well with the general objectives of the symposium.
special track on coordination models, languages and applications. in last few years, the field of coordination models and languages has earned the respect of other computer science researchers as they recognized that the understanding of how parts can be efficiently organized as a ensemble is of prime importance to the design of distributed complex systems. the proliferation of network computing and mobile computation, and especially the ubiquity of the internet has made coordination one of the key areas in modern computing. this track aims at bringing together researchers working on applied issues in coordination, ranging from new models to applications.
hybrid lagrangian relaxation for bandwidth-constrained routing: knapsack decomposition. to deliver quality of service, internet service providers are seeking effective solutions to optimize their networks. one of the main tasks is to optimally route a set of traffic demands, each along a single path, while satisfying their bandwidth requirements and without exceeding edge capacities. this is an integer multicommodity flow problem, which is known to be np-hard. to solve this problem efficiently, a new complete and scalable hybrid solver (hlr) integrating lagrangian relaxation and constraint programming has been proposed. it exploits the shortest path decomposition of the problem and has been shown to yield significant benefits over several other algorithms, such as cplex and well-known routing heuristics. in this paper we explore an alternative dualization within the same hybrid. we present a variant of hlr, adapted to the knapsack decomposition of the problem. although this relaxation seems less natural, experimental results show that it has some advantages. the paper provides an interesting insight of where the benefits may lie, in particular for larger and harder cases where the ratio of total demand to available capacity is higher.
handwritten character skeletonisation for forensic document analysis. a new method of skeletonisation (stroke extraction) of handwritten character images is presented. the method has been designed to extract the skeleton which is very close to human perception of the original pen tip trajectory. the need in such skeletonisation arises from feature extraction algorithms which are sensitive to inaccuracies in positions of skeleton curves. one class of such algorithms are those for extraction of features used in forensic analysis of handwriting. the skeleton is constructed in three steps directly from the grayscale image and is represented as a set of curves, which, in turn, are represented as cubic b-splines. such representation also eases feature extraction.experiments have been performed on 150 images of grapheme "th" written by different writers. the assessment of the skeletonisation results are presented.
an improved formal specification of the internet open trading pprotocol. the internet open trading protocol (iotp) is an electronic commerce protocol being developed by the internet engineering task force. the core of iotp is a set of electronic transactions that reflect common trading activities such as purchasing goods or depositing funds. we use coloured petri nets (cpns) to specify iotp. we enhance our previous specifications to include procedures for error handling and arbitrary transaction cancellation. this provides a complete specification of iotp's authentication and payment related transactions. modularity and re-use are also improved. the new specification conforms to the narrative description of iotp and allows us to analyse the protocol throughly.
mtree: an xml xpath graph index. this paper introduces the mtree index algorithm, a special purpose xml xpath index designed to meet the needs of the hierarchical xpath query language. with the increasing importance of xml, xpath, and xquery, several methods have been proposed for creating xml structure indexes and many variants using relational technology have been proposed. this work proposes a new xml structure index, called mtree, which is designed to be optimal for traversing all xpath axes. the primary feature of mtree lies in its ability to provide the next subtree root node in document order, for all axes, to each context node in o(1). mtree is a special purpose xpath index structure that matches the special purpose query requirements for xpath. this approach is in contrast to other approaches that map the problem domain into general purpose index structures such as b-tree that must reconstruct the xml tree from those structures for every query. mtree supports modification operations such as insert and delete. mtree has been implemented both in memory and on disk, and performance results using xmark benchmark data are presented showing up to two orders of magnitude improvement over other well-known implementations.
relevance feedback methods for logo and trademark image retrieval on the web. relevance feedback is the state-of-the-art approach for adjusting query results to the needs of the users. this work extends the existing framework of image retrieval with relevance feedback on the web by incorporating text and image content into the search and feedback process. some of the most powerful relevance feedback methods are implemented and tested on a fully automated web retrieval system with more than 250,000 logo and trademark images. this evaluation demonstrates that term re-weighting based on text and image content is the most effective approach.
a benchmark on soap's transport protocols performance for mobile applications. handheld mobile devices with wireless capability are gaining popularity. soap is a text-based protocol for web services, but it has high overhead and its suitability for resource-constrained devices over wireless networks needs to be reevaluated. soap uses http; http in turn uses tcp as the underlying transport protocol for transmitting messages. however, tcp has a high overhead and high network latency. in this paper, a benchmark of the performance of different underlying transport protocols for soap is reported. we show that soap-over-http and soap-over-tcp are inefficient and lead to high latency and transmission overhead for wireless networks. the results also show that soap-over-udp provides much higher throughput compared to soap-over-http.
active contour on the basis of inertia. this paper present a method for image segmentation, which is an adaptation of the classical active contours algorithm, also called "snakes", using a new internal energy approach. the classical model computes the energy function based on changes in gradient values, thus determining the detection of the object's edges. in the proposed model, the active contour moves attracted or repelled by its mass center, thus keeping the inertia towards shape compression or expansion. this represents an intuitive, simple and efficient scheme that constitutes an alternative to classical segmentation methods.
lights: a lightweight, customizable tuple space supporting context-aware applications. the tuple space model inspired by linda has recently been rediscovered by distributed middleware. moreover, some researchers also applied it in the challenging scenarios involving mobility and more specifically context-aware computing. context information can be stored in the tuple space, and queried like any other data.nevertheless, it turns out that conventional tuple space implementations fall short of expectations in this new domain. on one hand, many of the available systems provide a wealth of features, which make the resulting implementation unnecessarily bloated and incompatible with the tight resource constraints typical of this field. moreover, the traditional linda matching semantics based on value equality are not appropriate for context-aware computing, where queries are often formulated over value ranges, and where there is a prominent need to deal with imprecise information coming from multiple sources.in this paper, we describe a new tuple space implementation called lights. originally developed as the tuple space core of the lime [11] system, lights provides a flexible framework that makes it easy to introduce extensions to the tuple space and in general to customize the tuple space implementation. the design and programming interface of lights is presented, and its flexibility demonstrated by illustrating extensions that proved useful in the development of context-aware applications.
high-integrity extreme programming. we assess the applicability of extreme programming practices to engineering high-integrity systems, focusing on the characteristics of this problem domain that distinguish it from those considered more traditional for agile development. we suggest that extreme programming needs both extension and modification to be applicable to engineering high-integrity systems, and discuss promising extensions.
a black-box approach for web application sla. web servers nowadays have to cope with unprecedented amounts of workload, due to increasing popularity and complexity; in particular, dynamically generated content becomes the standard, hence the term web application. providing enough resources to sustain these workloads is a grand challenge, thus the application's runtime environment is often trusted to third-party hosting providers. to optimize resource utilization, hosting providers tend to share server machines between several applications. in such context, it is desirable to make sure that hosted applications are guaranteed a predictable level of performance, in other words implement service-level agreements (slas).in this paper, we present an approach to web application sla, based on profiling and geared at black-box server components, which allows us to express slas using application-level metrics, such as request rates. we conducted experiments in the context of a two-tiers server architecture shared by two e-commerce applications, and were able to enforce performance guarantees expressed as a number of concurrent user sessions.
an action semantics for mof 2.0. we show how to extend mof 2.0 to include an action semantics to support behavioural modelling. we explain why such an extension is useful, particularly for model transformation and consistency checking.
an intelligent biological information management system. as biomedical researchers are amassing a plethora of information in a variety of forms resulting from the advancements in biomedical research, there is a critical need for innovative information management and knowledge discovery tools to sift through these vast volumes of heterogeneous data and analysis tools. in this paper we present a general model for an information management system that is adaptable and scalable, followed by a detailed design and implementation of one component of the model. the prototype, called biosifter, was applied to problems in the bioinformatics area. the results indicate that biosifter is a powerful tool for biological researchers to automatically retrieve relevant text documents from biological literature based on their interest profile. the paper also presents experimental studies with real users to illustrate the efficacy of the approach.
using genetic programming for the induction of novice procedural programming solution algorithms. this paper describes a genetic programming system for the induction of solutions to novice procedural programming problems. this genetic programming system will form part of a generic architecture for the development of intelligent programming tutors for the procedural and object-oriented programming paradigms. an account of the primitives and system parameters needed for the derivation of solutions to problems for each of the introductory procedural programming topics is provided. this is followed by an analysis of the solutions induced by the genetic programming system. finally, the paper discusses the future work that will be carried as part of the initiative to evaluate genetic programming as a means of inducing solutions to novice procedural and object-oriented programming problems.
editorial message: special track on bioinformatics. advances in bioinformatics are providing the foundations for the convergence of agribusiness, healthcare, pharmaceuticals, computing and other fields, into what promises to be the largest industry in the world, the life sciences industry. much of the information to support biology research is available from online databases in a multitude of formats. the challenge is to obtain information and knowledge from these databases using innovative computational approaches to predict and explain phenomena in many application fields. one example of this computational challenge is to identify biological pathways using data, information, and knowledge scattered over heterogeneous databases. computational tools using system-theoretic approaches are needed to model metabolic pathways, signal-transduction pathways, genetic regulatory circuits and biological systems modeling. by identifying conserved genomes and pathways across several species at a high level, we hope to understand how stable biological systems have evolved. over the last few years, very high throughput techniques, such as microarray analysis, have provided many insights into genomes, metabolmes and transcriptomes and into cellular function. these data are now increasingly complemented by mass spectrometry technology, providing insights into proteomes. this computational analysis technique poses many new challenges.
morphing of image represented objects using a physical methodology. this paper presents a methodology to do morphing between image represented objects, attending to their physical properties. it can be used amongst images of different objects, or otherwise, between different images of the same object.according to the used methodology the given objects are modelled by the finite element method, and some nodes are matched by modal analysis. then, by solving the dynamic equilibrium equation the displacement field is determined, which allows the simulation of the objects' deformation.this physical approach also allows the computation of the involved strain energy, therefore the estimated morphing can be represented by the local or global strain energy values.this paper also describes the solution used to simulate only the non-rigid components of the involved deformation.