waashk/dblp huggingface dataset:
on using collection for aggregation and association relationships in xml object-relational storage. xml data can be stored in different databases including object-relational database (ordb). using ordb, we get the benefit of the relational maturity and the richness of oo modeling. one modeling concept that can be captured is the collection. collection structures frequently occur in xml documents especially in two relationship types: aggregation and association. however, very often when the data is stored in a database repository, the collection is flattened. we believe that preserving the collection semantics in the logical and the implementation level will create a better solution.in this paper we propose methods to preserve the collection in xml data into ordb using the concept of collection types. we use the semantic network diagram to represent the collection of the aggregation and the association in xml data. each of these relationship types will then be transformed into storage in an ordb environment. for aggregation, we propose different methods based on the hierarchy constraint. for association, our method is differentiated based on the cardinality.
fluid: supporting a transportable and adaptive web service. web services introduce new capabilities in the distributed application development model. this model is built on widely used internet standards, thereby presenting interoperability among different platforms. however, there are still several restrictions within the current standards, for instance, lack of the capability to react swiftly given poor-performance or requirements of maintenance on the host that is executing the web service. this paper proposes a nomadic and resource-aware web service framework, which provides the capabilities of migrating a web service to different hosts dynamically and adjusting itself to the available resources of the new host. therefore, allowing web services to react as a result of run-time requirements and poor-performance of hosts, as well as placing itself closer to the group of clients that frequently accesses the web service for performance enhancement. such an approach is applicable to ad-hoc networks of individually resource-poor mobile devices. implementation issues are also discussed and demonstrated.
automatic construction of drama school timetables based on a generic evolutionary framework for allocation and scheduling problems. we present the application of the generic framework evalloc for the solution of allocation and scheduling problems (asps) to a real-world problem. the solution engine integrated in the framework is based on an evolutionary algorithm (ea). the general design of the java framework allows for application to all asps, whose problem data description can be fit into the generic data representation of evalloc. the framework can be transformed into different applications by loading single xml (extended markup language) problem definition files. experimental results for the real-world application, timetabling of the complete teaching activities at the institute for drama at the mozarteum university of music and dramatic arts in salzburg, austria, are presented.
visual exploration of genetic likelihood space. linkage analysis is used to localize human disease genes on the genome and it can involve the exploration and interpretation of a seven-dimensional genetic likelihood space. existing genetic likelihood exploration techniques are quite cumbersome and slow, and do not help provide insight into the shape and features of the high-dimensional likelihood surface. the objective of our visualization is to provide an efficient visual exploration of the complex genetic likelihood space so that researchers can assimilate more information in the least possible time. in this paper, we present new visualization tools for interactive and efficient exploration of the multi-dimensional likelihood space. our tools provide interactive manipulation of active ranges of the six model parameters determining the dependent variable, scaled genetic likelihood, or hlod. using filtering, color, and an approach inspired by "worlds-within-worlds" [5, 6], researchers can quickly obtain a more informative and insightful visual interpretation of the space.
a network independent broker for obtaining the position of nomadic users. positioning is an essential component for the deployment of the evolving context-aware concepts. information society technologies (ist) project polos investigates existing schemes for location-based services, geographical information systems, positioning techniques and network interfaces, in order to design and implement a platform catering for the majority of location based services issues. facilitating towards this direction, polos' positioning component (pos) is introduced as a generic, scalable portable, open, modular and efficient qos enabled framework, offering independence from the underlying heterogeneous network infrastructures and positioning techniques.
continuous spatial queries via wireless data broadcast. this paper proposes a generic framework for continuous range queries via wireless data broadcast. this framework distinguishes itself from existing work by being the first to address the continuous spatial query issue, without an index, making effective use of the low wireless bandwidth, and therefore being ideal for achieving maximal scalability with the fastest access time. the task of the query processor is to selectively monitor the wireless broadcast channel, as the data items are disseminated according to their location by the server.
dynamic scheduling of scientific workflow applications on the grid: a case study. the existing grid workflow scheduling projects do not handle recursive loops which are characteristic to many scientific problems. we propose a hybrid approach for scheduling directed graph (dg)-based workflows in a grid environment with dynamically changing computational and network resources. our dynamic scheduling algorithm is based on the iterative invocation of classical static directed acyclic graphs (dags) scheduling heuristics generated using well-defined cycle elimination and task migration techniques. we approach the static scheduling problem as an application of a modular optimisation tool using genetic algorithms. we report successful implementation and experimental results on a pilot real-world material science workflow application.
compression of mammograms for medical practice. this paper considers effective compression methods for mammogram storing and interchange. a controversy problem of irreversible compression of medical images is studied in clinical tests to check usefulness and possibility of acceptance of wavelet-based compression for clinical applications. diagnostic accuracy is measured in abnormality detection tests with roc-based analysis, and by subjective rating of diagnostically important image features affecting lesion symptoms and image ordering according to preserved diagnostic accuracy. the efficiency of the most approved lossless coders is compared to efficiency of irreversible wavelet coding in acceptable rate range. general conclusion is that more effective irreversible compression of mammograms up to 1bpp is safe (i.e. preserves diagnostic accuracy), according to opinions of radiologists participating the experiments and presented results.
extending invalid-access prevention policy protocols for mobile-client data caching. due to the proliferation of multimedia objects and the subsequent need for managing a large number of multimedia objects within mobile client/server computing environments, there may exist multiple physical copies of the same data object in client caches at the same time with the server as the primary owner of all data objects. this brings new challenges of dealing with caching multimedia data for mobile clients. invalid-access prevention policy protocols developed in traditional dbms environment have to be extended to ensure that the serializability involving data updates is achieved in mobile environments. toward this goal, we have performed analysis, proposed three extended protocols, and conducted experimental studies under the invalid-access prevention policy in mobile environments, to meet the serializability requirement in a mobile client/server environment that deals with multimedia objects. these three protocols, referred to as extended server-based two phase locking (es2pl), extended call back locking (ecbl), and extended optimistic two phase locking (eo2pl) protocols, have included additional attributes to ensure multimedia object serializability in mobile client/server computing environments. in this paper, the rationale of developing these extended protocols, the basic idea behind the extension, a sketch of experimental studies, as well as the overall observation, are presented.
a top down approach for mas protocol descriptions. when the protocol of a complex multi-agent system (mas) needs to be developed, the top-down approach emphasises to start with abstract descriptions that should be refined incrementally until we achieve the detail level necessary to implement it. unfortunately, there exist a semantic gap in protocol description methodologies because most of them first identify which tasks have to be performed, and then use low level descriptions such as sequences of messages to detail them. in this paper, we propose an approach to bridge this gap. we model mas protocols using several abstract views of the tasks to be performed, and provide a systematic method to simplify them. tasks are represented by means of interactions that may be refined into lower-level interactions with the techniques proposed in this paper (simpler interactions are easier to describe and implement using message passing.) unfortunately, deadlocks may appear due to protocol design mistakes or due to the refinement process. thus, we also propose an algorithm to ensure that protocols are deadlock free.
methods for ranking information retrieval systems without relevance judgments. in this paper we present some new methods of ranking information retrieval systems without relevance judgement. the common ground of these methods is using a measure we called reference count. an extensive experimentation was conducted to evaluate the effectiveness of the proposed methods using various different standards information retrieval evaluation measures for the ranking, like average precision, r-precision, and precision and different document levels. we also compared the effectiveness of the proposed methods with the method proposed by soboroff et al. the experimental results showed that the proposed methods are effective, and in many cases are more effective than soboroff at al.'s method.
particle swarm optimization method in multiobjective problems. this paper constitutes a first study of the particle swarm optimization (pso) method in multiobjective optimization (mo) problems. the ability of pso to detect pareto optimal points and capture the shape of the pareto front is studied through experiments on well-known non-trivial test functions. the weighted aggregation technique with fixed or adaptive weights is considered. furthermore, critical aspects of the vega approach for multiobjective optimization using genetic algorithms are adapted to the pso framework in order to develop a multi-swarm pso that can cope effectively with mo problems. conclusions are derived and ideas for further research are proposed.
shadow document methods of resutls merging. in distributed information retrieval systems, document overlaps occur frequently across results from different databases. this is especially the case for meta-search engines which merge results from several general-purpose web search engines. this paper addresses the problem of merging results which contain overlaps in order to achieve better performance. several algorithms for merging results are proposed, which take advantage of the use of duplicate documents in two ways: one correlates scores from different results; the other regards duplicates as increasing evidence of being relevant to the given query. a variety of experiments have demonstrated that these methods are effective.
a method to define an enterprise architecture using the zachman framework. the proliferation of it and its consequent dispersion is an enterprise reality, however, most organizations do not have adequate tools and/or methodologies that enable the management and coordination of their information systems. the zachman framework provides a structured way for any organization to acquire the necessary knowledge about itself with respect to the enterprise architecture. zachman proposes a logical structure for classifying and organizing the descriptive representations of an enterprise, in different dimensions, and each dimension can be perceived in different perspectives.in this paper, we propose a method for achieving an enterprise architecture framework, based on the zachman framework business and is perspectives, that defines the several artifacts for each cell, and a method which defines the sequence of filling up each cell in a top-down and incremental approach. we also present a tool developed for the purpose of supporting the zachman framework concepts. the tool: (i) behaves as an information repository for the framework's concepts; (ii) produces the proposed artifacts that represent each cell contents, (iii) allows multi-dimensional analysis among cell's elements, which is concerned with perspectives (rows) and/or dimensions (columns) dependency; and (iv) finally, evaluate the integrity, dependency and, business and information systems alignment level, through the answers defined for each framework dimension.
undue influence: eliminating the impact of link plagiarism on web search rankings. link farm spam and replicated pages can greatly deteriorate link-based ranking algorithms such as hits. in order to identify and neutralize link farm spam and replicated pages, we look for sufficient material copied from one page to another. in particular, we focus on the use of "complete hyperlinks" to distinguish link targets by the anchor text used. we build and analyze the bipartite graph of documents and their complete hyperlinks to find pages that share anchor text and link targets. link farms and replicated pages are identified in this process, permitting the influence of problematic links to be reduced in a weighted adjacency matrix. experiments and user evaluations show significant improvement in the quality of results produced using hits-like methods.
identifying topological predicates for vague spatial objects. many geographical applications deal with spatial objects that cannot be adequately described by determinate, crisp concepts because of their intrinsically indeterminate and vague nature. gis and spatial database systems are currently unable to handle this kind of data. based on recent work on vague spatial data types, which are part of a formal data model called vasa (vague spatial algebra) and which leverage exact models of crisp spatial data types, this paper introduces a general mechanism for identifying topological predicates for vague spatial objects by means of topological predicates for crisp spatial objects. we illustrate this mechanism by deducing these predicates for vague points.
the social network of java classes. several works in literature have analyzed the link structure of programs in relation with software engineering: it has been observed that the programming standards caused small-world networks to emerge among classes in object-oriented programming. the need for coherent design and the coding conventions introduce regular patterns in the link structure of code.in this work, we study the social network naturally emerging from unrelated software projects. we studied the links present among java classes coming from different contexts. in this case, any observable patterns come from social behaviors, rather than software engineering practices.in our analysis, we could observe a regular social network, organized according to a power-law distribution that is typical, for instance, of links among web pages. we give a positive value to class links, which we consider a sign of relevance and acceptance. out of this, we propose a way of ranking classes, and we present our prototype search engine for java classes.
an adjustment model in a geometric constraint solving problem. an interesting problem related to geometric constraint solving is the choice of the "good" solution. the suitability and effectiveness of genetic algorithms applied to this problem has been demonstrated but their performance depends on the values assigned to their control parameters. although there are recommendations in the specialised technical literature about values for these parameters, their optimal settings depend on the problem at hand. therefore it would be interesting to define a model that automatically adjusts the values of the evolutive parameters as a function of the geometric problem.this paper proposes a meta-model that generates the recommendations for the right parameter values in genetic algorithms operating as a selector mechanism in constructive geometric constraint solvers. it should be stressed that the proposed model is general and automatic. this means that it is applicable to any context and works without the need for any user supervision.
enterprise architecture: business and it alignment. organizations have existing systems infrastructure that are the result of decades of one-by-one implementations of specific solutions. as organizations, products, customers and technologies continue to change at an increasingly rapid rate, managers have sought overviews that will allow them to understand how business and it within their organization fits together. enterprise architecture is a representation of the organization to enable the planning of the organization changes. it includes the current and future business objectives, goals, visions, strategies, informational entities, business processes, people, organization structures, application systems, technological infrastructures, and so on.in this paper, we show how the alignment between business and it can be disaggregated into four different dimensions and we present some heuristics to ensure such alignment.
the impact of sample reduction on pca-based feature extraction for supervised learning. "the curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimensions. in this paper, different feature extraction (fe) techniques are analyzed as means of dimensionality reduction, and constructive induction with respect to the performance of na&iuml;ve bayes classifier. when a data set contains a large number of instances, some sampling approach is applied to address the computational complexity of fe and classification processes. the main goal of this paper is to show the impact of sample reduction on the process of fe for supervised learning. in our study we analyzed the conventional pca and two eigenvector-based approaches that take into account class information. the first class-conditional approach is parametric and optimizes the ratio of between-class variance to the within-class variance of the transformed data. the second approach is a nonparametric modification of the first one based on the local calculation of the between-class covariance matrix. the experiments are conducted on ten uci data sets, using four different strategies to select samples: (1) random sampling, (2) stratified random sampling, (3) kd-tree based selective sampling, and (4) stratified sampling with kd-tree based selection. our experiments show that if the sample size for fe model construction is small then it is important to take into account both class information and data distribution. further, for supervised learning the nonparametric fe approach needs much less instances to produce a new representation space that result in the same or higher classification accuracy than the other fe approaches.
core selection with end-to-end qos support. core-based routing with quality of service (qos) support is essential to facilitate multi-sender multimedia multicast applications such as video conferencing and virtual collaboration applications. in this paper, we introduce (i) a new application-level service class framework that allows group members to easily indicate their desired service quality and (ii) the use of as many cores per group as necessary in corebased routing to maximize the number of group members with satisfied qos requirements. under the service class framework, we formulate the novel core selection problem that selects as many cores as necessary while maximizing the number of satisfied group members. we propose a new core selection algorithm to address the problem and provide a complete core selection protocol using the algorithm. experimental results show that our core selection algorithm performs as well as the optimal algorithm and significantly outperforms a recent core selection algorithm with qos support using a single core.
similarity between euclidean and cosine angle distance for nearest neighbor queries. understanding the relationship among different distance measures is helpful in choosing a proper one for a particular application. in this paper, we compare two commonly used distance measures in vector models, namely, euclidean distance (eud) and cosine angle distance (cad), for nearest neighbor (nn) queries in high dimensional data spaces. using theoretical analysis and experimental results, we show that the retrieval results based on eud are similar to those based on cad when dimension is high. we have applied cad for content based image retrieval (cbir). retrieval results show that cad works no worse than eud, which is a commonly used distance measure for cbir, while providing other advantages, such as naturally normalized distance.
interval and dynamic time warping-based decision trees. this work presents decision trees adequate for the classification of series data. there are several methods for this task, but most of them focus on accuracy. one of the requirements of data mining is to produce comprehensible models. decision trees are one of the most comprehensible classifiers. the use of these methods directly on this kind of data is, generally, not adequate, because complex and inaccurate classifiers are obtained. hence, instead of using the raw features, new ones are constructed.this work presents two types of trees. in interval-based trees, the decision nodes evaluate a function (e.g., the average) in an interval and the result is compared to a threshold. for dtw-based trees each decision node has a reference example. the distance from the example to classify to the reference example is calculated and then it is compared to a threshold.the method for obtaining these trees it is based on 1) to develop a method that obtains for a 2-class data set a classifier formed by a new feature (a function in an interval or the distance to a reference example) and a threshold, 2) to use the boosting method to obtain an ensemble of these classifiers, and 3) to use a method for constructing decision trees using as data set the features selected by boosting.