waashk/dblp huggingface dataset:
specifying temporal data models for semistructured data by a constraint-based approach. in the past few years some models for semistructured temporal data, which propose different strategies to deal with temporal dimensions, have been defined. in this paper we analyze these models by applying the recently proposed meta-model gsmm (general semistructured meta-model) for semistructured information. gsmm allows us to represent semistructured temporal data models with a unifying formalism; constraints that are specified in these models are also represented and classified on the basis of their expressiveness.
architectures for a temporal workflow management system. workflows describe business processes as the coordinated execution of simple activities (tasks) by human or automatic executors (agents). workflow management systems (wfms) are software systems supporting the automatic execution of workflows. most wfmss rely on database management systems (dbms) where temporal aspects, which are relevant for the execution of a workflow, are managed explicitly. in this paper we discuss different architectures for a temporal wfms: then we propose yet another workflow system which novelly manages temporal aspects via a temporal database system, composed by a temporal layer on top of a relational dbms (oracle). the adoption of a temporal database system both benefitted the development of the engine and increased its efficiency by allowing some additional features, as the management of process model evolution and the selection of executing agents via a workload balance over time.
a parallel index for semistructured data. database systems are increasingly being used to manage semistructured data, which may not have a fixed structure or set of relationships between data items. indexes which use tree structures to manage semistructured data become unbalanced and difficult to parallelize due to the complex nature of the data. we propose a mechanism by which an unbalanced vertical tree is managed in a balanced way by additional layers of horizontal index. then, the vertical tree can be partitioned among parallel computing nodes in a balanced fashion. we discuss how to construct, search and update such a horizontal structure using the example of a patricia trie index. we also present simulation results that demonstrate the speedup offered by such parallelism, for example, with three-way parallelism, our techniques can provide almost a factor of three speedup.
automatic test program generation for pipeline processors. the continuous advances in microelectronics design are creating a significant challenge to design validation in general, but tackling piplined microprocessors is remarkably more demanding. this paper presents a methodology to automatically induce a test program for a microprocessor maximizing a given verification metric. the approach exploits a new evolutionary algorithm, close to genetic programming, able to cultivate effective assembly-language programs. the proposed methodology was used to verify the dlx/pii, an open-source processor with a 5-stage pipeline. code-coverage was adopted in the paper, since it can be considered the required starting point for any simulation-based functional verification processes. experimental results clearly show the effectiveness of the approach.
an evolutionary algorithm for reducing integrated-circuit test application time. the cost for testing integrated circuits represents a growing percentage of the total cost for their production. the former strictly depends on the length of the test session, and its reduction has been the target of many efforts in the past. this paper proposes a new method for reducing the test length by adopting a new architecture and exploiting an evolutionary optimization algorithm. a prototype of the proposed approach was tested on iscas standard benchmarks and the experimental results show its effectiveness.
operating system multilevel load balancing. this paper describes an algorithm that allows linux to perform multilevel load balancing in numa computers. the linux scheduler implements a load balancing algorithm that uses structures called sched domains to build a hierarchy that represents the machine's topology. although sched domains implementation allows linux to build a multilevel hierarchy to represent multilevel machines, the generic code of the current kernel version builds no more than two levels in the sched domains hierarchy. thus, for numa systems with three or more memory access levels, the constructed hierarchy does not represent correctly the machine's topology. when linux load balancing algorithm uses an incorrect sched domains hierarchy, process execution time can increase, because processes can be moved to nodes that are distant from their memory areas. in order to solve this problem, we have implemented an algorithm to build multilevel sched domains hierarchies for numa computers. our proposed algorithm uses acpi slit table data to recognize how many memory access levels a machine contains. then, it builds an n-level sched domains hierarchy, where n is the number of memory access levels. through benchmarking and simulation results we demonstrate that the linux load balancing performance when the sched domains hierarchy is built using our proposed algorithm is better than using the current linux algorithm.
software performance model-driven architecture. model transformations in mda mostly aim at stepping from a platform independent model (pim) to a platform specific model (psm) from a functional viewpoint. in order to develop high quality software products, non-functional attributes (such as performance) must be taken into account. in this paper we extend the canonical view of the mda approach to embed additional types of models that allow to structure a model driven approach keeping into account performance issues. we define the relationships between mda typical models and the newly introduced models, as well as relationships among the latter ones. in this extended framework new types of model-to-model transformations also need to be devised. we place an existing methodology for transforming software models into performance models within the scope of this framework.
a reflective middleware architecture to support adaptive mobile applications. mobile applications are required to operate in environments in which the availability for resources and services may change significantly during system operation. as a result, mobile applications need to be capable of adapting to these changes to offer the best possible level of service to their users. however conventional middleware is limited in its capability of adapting to the environment changes and different users requirements. computational reflection applied to middleware design has introduced a new research field, reflective middleware. in this paper we propose a reflective middleware architecture which can be used to develop adaptive mobile applications. in order to validate the architecture proposed we developed a prototype using the web services technology which focuses on the problem of adapting on a set of attributes in a coordinated manner.
incremental collaborative filtering for mobile devices. this paper describes how collaborative filtering can be used for mobile devices. when the user is connected to a central repository, the algorithm selects a subset of profiles to store on the device. when the user is not connected to the repository, the predictions can be incrementally updated to reflect new or updated ratings. experiments on a movie data set show that the method can dramatically reduce the data needed while still performing nearly as good as a centralized approach.
classifying biological articles using web resources. text classification systems on biomedical literature aim to select relevant articles to a specific issue from large corpora. most systems with an acceptable accuracy are based on domain knowledge, which is very expensive and does not provide a general solution. this paper presents a novel approach for text classification on biomedical literature, involving the use of information extracted from related web resources. we validated this approach by implementing the proposed method and testing it on the kdd2002 cup challenge: bio-text task. results show that our approach can effectively improve efficiency on text classification systems for biomedical literature.
a contingency view of organizational infrastructure requirements engineering. delivery of it projects in today's rapidly changing business environment is a challenge. conventional investment approaches result in lumpy capital allocations, which encourage managers to include many potential future business requirements in each capital request. this locks in the delivery of future requirements despite high market uncertainty. the resulting projects are large and complex from both a technical and management perspective. in the management literature, new frameworks are emerging that draw on real options valuations to justify early infrastructure investment and provide fine-grained control over business initiatives in an uncertain world. business managers can then build on the infrastructure by selecting business initiatives to maximise option value. however, this requires engineering approaches that separates infrastructure and business requirements and minimises their dependencies. this paper explores a contingency approach to requirements engineering (re) to minimise initial requirements and maximise future strategic options, challenging the research community's dominant paradigm of completeness, correctness and consistency.
protein classification using transductive learning on phylogenetic profiles. phylogenetic profiles of proteins - strings of ones and zeros encoding respectively the presence and absence of proteins in a group of genomes - have recently been used to identify homologous proteins and/or proteins that are functionally linked, such as participating in a metabolic pathway. we proposed a novel learning method for protein classification based on phylogenetic profiles, which takes into account both the phylogenetic tree structure and the likelihood of proteins presence in genomes. the method consists of a mechanism to extend the profiles with extra bits encoding the phylogenetic tree, whose interior nodes, representing hypothetical ancestral genomes, are scored in a way to reflect their chances of developing divergence in the descendants. the scoring scheme also incorporates the likelihood of proteins presence in genomes as weighting factors, which are collected from the training data initially and integrated as part of kernel of a support vector machine. in a transductive learning scheme, when the svm is used for classifying test data, the weighting factors are updated iteratively using the predicted results. we tested our method on the proteome of saccharomyces cerevisiae and used the mips classification as a benchmark. the results showed that the classification accuracy was greatly increased.
bootstrapping multi-party ad-hoc security. in pervasive-computing scenarios users may wish to achieve some degree of security in their interaction with other people or equipment, in contexts where they cannot be confident of the others' long-term identities and where there may be no reliable pki. we examine the problem of bootstrapping security in an ad-hoc network formed by a group of users.in [4] a number of protocols using low-bandwidth channels involving the human agent(s) "in the loop" to bootstrap secure communication over an untrusted infrastructure were presented, the point being that the attacker's powers are more limited with regard to these empirical channels in one or more respects than in the standard dolev-yao view. the two-party protocols proved easy to verify [3] (relative to those weakened powers) by adapting the csp/fdr-based approach of casper[9], but the multi-party network-formation protocol (based on a combination of low bandwidth non-forgeable channels and an ordinary dolev-yao communication medium) proved more problematic.addressing the verification of this protocol [11] led to consideration of a number of simplified variants, which appear interesting in their own right.
wrapping-oriented classification of web pages. data extraction from html web pages is performed by software programs called wrapper. writing wrappers is a costly and labor intensive task; recently several proposal have attacked the problem of automatically generating wrappers. in this paper, we study a problem related to the automation of the wrapping generation process: given a portion of a web site to wrap, we develop techniques to cluster its html pages into page classes with homogeneous organization and layout; these classes can become the input to the wrapper generation process. also, once a wrapper library has been generated for a bunch of web sites, our techniques can be used in order to select, for any new page downloaded from these site, the right wrapper in the library. based on the proposed techniques we have developed a software prototype, and conducted several experiments on html pages from real-life web sites.
editorial message: special track on information access and retrieval. information access technologies, like for example information retrieval (ir) and information filtering (if), aim at modelling, designing and implementing systems able to provide fast and effective content-based access to a large amount of information. information can be of any kind: textual, visual, or auditory. the aim of such systems is to estimate the relevance of documents to a user information need. this is a very hard and complex task for many different reasons than a large volume of research has attempted to explain and tackle. nowadays, research in information access includes modelling, document classification and categorization, system architecture, user interfaces, data visualisation, languages, topic detection, etc.
editorial message: special track on information access and retrieval. information retrieval (ir) aims at modelling, designing and implementing systems able to provide fast and effective content-based access to a large amount of information. information can be of any kind: textual, visual, or auditory. the aim of such systems is to estimate the relevance of documents to a user information need. this is a very hard and complex task for many different reasons that a large volume of research has attempted to explain and tackle. nowadays, research in information retrieval is central to the design and development of advanced information access technologies and spans a number of research topics including document modelling, document classification and categorization, system architecture, user interfaces, data visualisation, languages, topic detection, etc.
evaluating adaptive hypermedia authoring while teaching adaptive systems. in this paper we present an interesting experiment of combining teaching and research: the testing of mot, an adaptive hypermedia authoring tool based on the laos adaptive hypermedia authoring framework, via a class of about twenty graduate students from the eindhoven university of technology, taking a two week intensive course in adaptive systems and user modeling. we will show what the incentives of the experiment were, by giving a short description of laos, the theoretical background; then we will sketch mot, the on-line system gradually implementing laos. the focus of the paper will be the experiment itself, with its parameters: the setting and initial planning, the actual implementation and the results. finally, we will comment on the results and interpret them. moreover, we will discuss what we have learned from these results and how they pointed us to new ways of improving mot.
minimizing the reconfiguration overhead in content-based publish-subscribe. the publish-subscribe model provides strong decoupling among the components of a distributed application. this makes it amenable to highly dynamic environments. nevertheless, publish-subscribe systems exploiting a distributed event dispatcher are typically not able to rearrange dynamically their operations to adapt to changes which impact the topology of the dispatching infrastructure. this paper presents a description and analysis of a novel algorithm to deal with this kind of reconfiguration. the strength of this algorithm is its ability to minimize the portion of the system affected by the reconfiguration by exploiting a novel concept we refer to as the reconfiguration path. simulations compare our approach with two others and show a significant reduction (up to 76%) in the overhead caused by reconfiguration.
topic activation analysis for document streams based on document arrival rate and relevance. with the advance of network technology in recent years, the dissemination and exchange of massive documents has become commonplace. accordingly, the importance of content analysis techniques is increasing. topic analysis in large-scale document streams such as e-mails and news articles is an important research issue. this paper addresses techniques for "topic activation analysis" for document streams. for example, when news articles with a strong relationship to a given topic arrive frequently in a news stream, we can regard the activation level of the topic as high. in [1], kleinberg proposed a method for analyzing document streams. although the main objective of his method was to detect bursts of topics, it can also be used for topic activation analysis. his method, however, has a serious limitation in that it only looks at the arrival rate of documents and ignores the degree of relevance for each document. another limitation is that his method is "batch-oriented." this paper first proposes a novel topic activation analysis scheme that incorporates both document arrival rate and relevance to address the first problem. it then presents an incremental scheme more appropriate for a document streaming environment. the proposed schemes are validated by experiments using real cnn news articles.
analysis of an evolutionary algorithm with hypermacromutation and stop at first constructive mutation heuristic for solving trap functions. the paper presents a theoretical analysis, along with experimental studies, on a new evolutionary algorithm (ea) to optimize basic and complex trap functions. the designed evolutionary algorithm uses perturbation operators based on hypermacromutation and stop at first constructive mutation heuristic. the experimental and theoretical results show that the algorithm successfully achieves its goal in facing this computational problem. the low number of evaluations to solutions expected through the theoretical analysis of the ea have been fully confirmed by the experimental results. to our knowledge the designed ea is the state-of-art algorithm to face trap function problems.
real coded clonal selection algorithm for unconstrained global optimization using a hybrid inversely proportional hypermutation operator. numerical optimization of given objective functions is a crucial task in many real-life problems. this paper introduces a new immunological algorithm for continuous global optimization problems, called opt-immalg; it is an improved version of a previously proposed clonal selection algorithm, using a real-code representation and a new inversely proportional hypermutation operator.we evaluate and assess the performance of opt-immalg and several others algorithms, namely opt-ia, pso, arpso, de, and sea with respect to their general applicability as numerical optimization algorithms. the experiments have been performed on 23 widely used benchmark problems.the experimental results show that opt-immalg is a suitable numerical optimization technique that, in terms of accuracy, outperforms the analyzed algorithms in this comparative study. in addition it is shown that opt-immalg is also suitable for solving large-scale problems.
an accuracy-aware compression technique for multidimensional data cubes. a novel data cube compression technique, based on the well-known lsa method, is presented in this paper, along with its experimental evaluation against state-of-the-art approximate query answering techniques. particularly, the proposed technique is able to drive the lsa-based compression process in dependence on the accuracy (i.e., the quality of the approximate answers) required from olap users/applications, thus drawing new scenarios for delivering summarized knowledge extracted from huge amounts of multidimensional data.
configuring software, reconfiguring memories: the influence of integrated systems on knowledge storage, retrieval and reuse. the recent diffusion of integrated enterprise software systems has created an incentive for firms to codify and standardise their knowledge and practices. codification, and the subsequent delegation of organisational 'memory' to software entails radical structural transformations to knowledge and routines as these are reconfigured in the form of new, computer-embedded representations, which are reproduced across the organisation. we argue that, while intended to improve the integration of data and efforts as well as reducing the heterogeneity of actions and viewpoints across the organisation, the software-induced standardisation highlights existing organisational idiosyncrasies as well as creating new sources of conflict. this holds important implications for the dependability of the wider software-organisation system. our evidence, based on participant observation, is presented in the form of a case study focusing on the implementation of product data manager (pdm) software at a leading automotive organisation.
bridging aop to smp: turning gcc into a metalanguage preprocessor. this article presents an strategy to combine important software engineering techniques, static metaprogramming (smp) and generic programming (gp) with aspect oriented programming (aop). these rely on specific language tools that, today, cannot be deployed in conjunction, thus imposing limitations on the software development process. our strategy consists in adapting the c++ compiler to act as a smp preprocessor. this preprocessor is able to parse the input program, execute eventual metaprograms, and output the resulting single-level program for further processing by an aspect weaver.
seamless integration of rule-based knowledge and object-oriented functionality with linguistic symbiosis. software applications often contain implicit knowledge in addition to functionality which is inherently object-oriented. many approaches and systems exist that focus on separating rule-based knowledge from object-oriented functionality and representing it explicitly in a logic reasoning system. support for seamless integration of this knowledge with the object-oriented functionality improves software development and evolution. our hypothesis is that a linguistic symbiosis is required between the logic reasoning and object-oriented programming paradigms in order to achieve seamless integration.this paper presents a symbiotic extension of soul, a system which implements a logic programming language and a production system in smalltalk. the presence of these two logic reasoning systems in soul ensures a comprehensive coverage of rule-based reasoning styles, more specifically forward and backward chaining. our approach is evaluated by means of two case studies. we summarise a comprehensive survey, which shows that existing systems do not fully support seamless integration.