waashk/dblp huggingface dataset:
an evaluation of resource description quality measures. an open problem for distributed information retrieval is how to represent large document repositories (known as resources) efficiently. to facilitate resource selection, estimated descriptions of each resource are required, especially when faced with non-cooperative distributed environments[1]. accurate and efficient resource description estimation is required as this can have an affect on resource selection, and as a consequence retrieval quality. query-based sampling (qbs) has been proposed as a novel solution for resource estimation[2], with proceeding techniques developed therafter[3]. however, the challenge to determine if one qbs technique is better at generating resource description than another is still an unresolved issue. the initial metrics tested and deployed for measuring resource description quality were the collection term frequency ratio (ctf) and spearman rank correlation coefficient (srcc)[2]. the former provides an indication of the percentage of terms seen, whilst the later measures the term ranking order, although neither consider the term frequency, which is important for resource selection. we re-examine this problem and consider measuring the quality of a resource description in context to resource selection, where an estimate of the probability of a term given the resource is typically required. we believe a natural measure for comparing the estimated resource against the actual resource is the kullback-leibler divergence (kl) measure. kl addresses the concerns put forward previously, by not over-representing low frequency terms, and also considering term order[2]. in this paper, we re-assess the two previous measures alongside kl. our preliminary investigation revealed that the former metrics display contradictory results. whilst, kl suggested a different qbs technique than that prescribed in [2], would provide better estimates. this is a significant result, because it now remains unclear as to which technique will consistently provide better resource descriptions. the remainder of this paper details the three measures, the experimental analysis of our preliminary study and outlines our points of concern along with further research directions.
on using oo techniques to establish workflow conformance. workflow schema are constantly changing [6][7] driven by new customer requirements or business processes re-engineering. schema evolution is less of a problem when no work-flow is active, which could be achieved by waiting until all workflows are terminated, or by aborting active ones. these are however not viable solutions, because workflows can be of long duration and comprise considerable amounts of work. this results in a number of variants that may become problematic to manage especially when creating new instances of the schema. however, many of these variants can be merged together to reduce the number of templates to choose from while instantiating a new workflow instance. merging can be accomplished only when two workflows are compatible or conformant. in this effort we aim at solving the problem of defining workflow conformance using oo concepts of inheritance and merging conformant workflows.the rest of this paper is organized as follows. we first formulate the problem and then present our solution which is based on task inheritance. we finally present some conclusions and opportunities for future work.
xspace: a tuple space for xml & its application in orchestration of web services. today's extended enterprise calls for the integration of several disparate systems built using multiple technologies and executing across firewall boundaries. the integration is usually done in the context of workflow orchestration and in its current incarnation, this extends across multiple enterprises over the internet. given the disparity of these systems that need to be integrated in the workflow, these systems are usually exposed as web services to bring about a common denominator. by implication, there is a need to transfer xml documents asynchronously from one system to another since xml is the language of web service interaction. an ideal way to accomplish this asynchronous interaction is to use the concept of tuple spaces which provide a distributive, associative shared memory concept. usually tuple spaces have dealt with the either simple types or language specific objects as tuple attributes and do not span enterprise boundaries but our need for exchanging xml documents over the internet forces us to reconsider how spaces are architected. in this paper, we present xspace - a tuple space that deals with xml documents natively and is distributed across the internet. we also show how it can serve as a vehicle to orchestrate web services by providing an asynchronous interaction paradigm.
a robust deception-free coalition formation model. we study two properties of coalition formation algorithms, very important for their application in real-life scenarios: robustness and tolerance to some agent misbehaviors. the study is performed for a previously proposed coalition formation model-based upon game theory for a class of task-oriented problems that guarantees an optimum task allocation and a stable (fair) profit division. the results show acceptable behavior and performance.
agent coordination for bus fleet management. this paper presents an abstract multiagent architecture useful for decision support systems (dss), and shows how this architecture can be instantiated to a particular real-world domain, bus fleet management (bfm). after discussing the benefits of adopting a multiagent approach for dss, the paper introduces the real world case study and analyzes it. next, an abstract mas architecture for dss in general, and specialized then for bfm case study is presented. the architecture includes a set of different agents which are in charge of different social roles, and what is needed for their coordination, the coordination facilitator and the coordination protocols. the paper is concentrated in this point showing a concrete example in the bfm domain.
sf-hme system: a hierarchical mixtures-of-experts classification system for spam filtering. many linear statistical models have been lately proposed in text classification related literature and evaluated against the unsolicited bulk email filtering problem. despite their popularity - due both to their simplicity and relative ease of interpretation - the non-linearity assumption of data samples is inappropriate in practice, due to its inability to capture the apparent non-linear relationships, which characterize these samples. in this paper, we propose the sf-hme, a hierarchical mixture-of-experts system, attempting to overcome limitations common to other machine-learning based approaches when applied to spam mail classification. by reducing the dimensionality of data through the usage of the effective simba algorithm for feature selection, we evaluated our sf-hme system with a publicly available corpus of emails, with very high similarity between legitimate and bulk email - and thus low discriminative potential - where the traditional rule based filtering approaches achieve considerable lower degrees of precision. as a result, we confirm the domination of our sf-hme method against other machine learning approaches, which appeared to present lesser degree of recall.
powerjava: ontologically founded roles in object oriented programming languages. in this paper we introduce a new view on roles in object oriented programming languages, based on an ontological analysis of roles. a role is always associated with an object instance playing the role and also to an object instance (its institution) which represents its context. the definition of a role depends on the definition of the institution. this property allows to endow role-players with powers that can modify the state of the institution and of the other roles defined in it. as an example, we introduce a role construct in java, where the abolve features are interpreted as follows. roles are implemented as classes, which can be instantiated only in presence of an instance of the player and of an instance of an institution. the definition of a class implementing a role is included in the class of the institution, the role belongs to. powers are methods which can access private fields and methods of the institution they belong to, and of the other roles of the same institution.
adaptive resolution modeling of regional air quality. we discuss an adaptive resolution system for modeling regional air pollution based on the chemical transport model stem. the grid adaptivity is implemented using the generic tool paramesh, which enables the grid management operations while harnessing the power of parallel computers. the computational algorithm is based on a decomposition of the domain, with the solution in different sub-domains being solved at different spatial resolutions. numerical experiments confirm that adaptive resolution leads to the decrease in spatial error with an acceptable increase in computational time. advantages and shortcomings of the present approach are also discussed.
management of unspecified semi-structured data in multi-agent environment. amounts of available heterogeneous semi-structured data grow rapidly on the web and other data repositories. this raises the need to provide simple and universal ways to access this data. to provide such an interface, we propose to exploit the notion of "unspecified ontologies", describing the data objects as a list of attributes and their respective values. in order to facilitate an efficient management of the unspecified data objects we use a multi-agent channeled multicast communication platform. the data objects are stored distributively, such that each attribute is assigned a designated channel. this allows performing efficient searches by parallel querying of the relevant channels only, and aggregating the partial results. moreover, the multi-agent platform facilitates advanced data management through extracting metadata from the data objects. we implemented a prototype system and experimented with a corpus of real-life e-commerce advertisements. our results demonstrate scalability of the proposed approach and the accuracy of the extracted meta-data.
advanced model transformation language constructs in the viatra2 framework. we present the model transformation language of the viatra2 framework, which provides a rule and pattern-based transformation language for manipulating graph models by combining graph transformation and abstract state machines into a single specification paradigm. this language offers advanced constructs for querying (e.g. recursive graph patterns) and manipulating models (e.g. generic and meta transformation rules) in unidirectional model transformations frequently used in formal model analysis to carry out powerful abstractions. in addition, powerful language constructs are provided for multi-level metamodeling to design modeling languages and template-based code generation.
a distributed stand-in agent based algorithm for opportunistic resource allocation. mobile ad-hoc networks (manet) are expected to form the basis of future mission critical applications such as combat and rescue operations. in this context, communication and computational tasks required by overlying applications will rely on the combined capabilities and resources provided by the underlying network nodes. this paper introduces an integrated flexfeed/a-globe technology and distributed algorithm for opportunistic resource allocation in resource-and policy-constrained mobile ad-hoc networks. the algorithm is based on agent negotiation for the bidding, contract and reservation of resources, relying primarily on the concept of remote presence. in the proposed algorithm, stand-in agents technology is used to create a virtual, distributed co-ordination component for opportunistic resource allocation in mobile ad-hoc networks.
compiling model transformations to ejb3-specific transformer plugins. we present a technique for compiling model transformations defined by a combination of graph transformation and abstract state machine rules (as used within the viatra2 framework) into stand-alone transformer plugins for the ejb 3.0 platform. as a result, the design of transformations can be separated from the execution of transformations. this also enables to run viatra2 model transformations on very large models stored in underlying relational databases or to integrate such transformations into existing business applications.
prediction of inherited and genetic mutations using the software model checker spin. genetic testing is becoming an important tool for detection of many genetic diseases. designing a genetic test requires accurate data and an efficient means of comparing sequences that are present in the databases. however, as prodigious amount of data continue to emerge, querying the database to make important predictions is becoming arduous. it is essential that better tools be designed to analyze these data. in this paper, a model-based approach to gene tests and the analysis of metabolic pathways is proposed. gene sequences and metabolic processes are modeled using formal language, and predictions are made through the verification mechanism of a software model checker. the technique is demonstrated with models of genes for cystic fibrosis tranmembrane conductance regulator protein and the map kinase pathway.
a product line architecture for web applications. increasingly, web applications are used in similar environments to fulfill similar tasks. sharing a common infrastructure and reusing assets to deploy recurrent services may be considered an advantage in terms of economic significance and overall quality. thus, it may be appropriate to design web applications as members of a product family.the paper illustrates koriandol, a product-line architecture designed to develop, deploy and maintain web application families. in contrast with usual component-based systems, koriandol prescribes that variability handling mechanisms are reflective and built-in into the components.
a framework for the classification and the reclassification of electronic catalogs. electronic marketplaces are virtual communities where buyers may meet proposals of several suppliers and make the best choice. the exponential increment of the e-commerce amplifies the proliferation of different standards and joint initiatives for the classification of products and services. therefore, b2b and b2c marketplaces have to classify products and goods according to different product classification standards. in this paper, we propose a framework to classify and reclassify electronic catalogs based on a semi-automatic methodology to define semantic mappings among different product classification standards and catalogs.
a secure method for signature delegation to mobile agents. this paper presents a novel method that allows the delegation of signature power to one or more entities that jointly play the role of a proxy signer. this work is different from other related proxy signature schemes in that in addition to providing confidentiality protection to the proxy key, the method provides non-repudiation services to all the parties involved. in particular, it protects against repudiation of signature delegation by the original signer, repudiation of proxy signature generation by the proxy signer, and repudiation of receipt of the proxy signature by the signature recipient. this feature is attractive for signature delegation in agent-based paradigm in which proxy signers are mobile agents that are executed in remote untrustworthy hosts.
impact of peer incentives on the dissemination of polluted content. recent studies have reported a new form of malicious behavior in file-sharing peer-to-peer systems: content pollution. the dissemination of polluted content in a p2p system has the detrimental effect of reducing content availability, and ultimately, decreasing the confidence of users in such systems. two potential strategies for polluting p2p content are decoy insertion, which consists of injecting corrupted copies of a file into the system, and hash corruption, which consists of injecting a corrupted file with the same hash code as a non-corrupted one. polluted content disseminates through p2p networks because users typically do not delete the corrupted files that they download.this paper investigates the effectiveness of peer incentives to delete corrupted files in reducing the dissemination of polluted content, considering the two aforementioned pollution mechanisms. our simulation results show that the effectiveness of incentives is highly dependent on the pollution mechanism. we show that for a pollution dissemintation techinique called hash corruption, only effective incentive mechanisms are able to avoid spreading of polluted content.
towards chemical coordination for grids. in [6], ian foster and karl kesselman explain that grids need "a rethinking of existing programming models and, most likely, new thinking about novel models". in this work, we investigate a "novel programming model" for grids based on the chemical metaphor.
profile and context filtering of streaming data for a mobile personal assistant. a key component in an ubiquitous computing environment is a personal assistant that can provide a link between devices and services and a human user. a large part of interactions in such an environment is expected to be using xml data. in this paper we present the use of profiles and context to obtain useful information from streaming documents. the user profile contains all the preferences and information on typical behavior for the user. this information can be entered by the user and learned over time. as the profile is never shared or transmitted, strict user privacy is maintained. context information includes current day and time, and the user's location. we have implemented our ideas in an intelligent personal assistant, ipa, within the context of mobile commerce.
a multi-agent system for remote psychological profiling with role playing games based tests. this paper describes a web-based computer system to support psychological evaluation for employee selection or assessment. candidate profiling is based on jungian psychology and the theory of archetypes. the test is proposed to the candidate in the form of a role playing game session to avoid repetitiveness and predictability, and therefore to increase its effectiveness. the profiling engine is a multi-agent system that dynamically builds the test, basing on the candidate's behaviour and on the kind of job he is being tested for, choosing between available story modules. information about psychological model, scenographic modules and operative data is stored in a object oriented dbms. the system provides a remote test interface for candidates and configuration tools as well.
three approaches to the coordination of multiagent systems. the engineering of the social aspects has been acknowledged as one of the principal issues in the realization of real-world multiagent systems. the literature proposes a number of solutions to this problem and in this paper we consider three of them and we discuss their relationships. first, we take into account hybrid coordination models based on tuple centres. then, we consider interaction protocols as a means to coordinate multiagent systems. finally, we address the implicit coordination that the semantics of classic agent communication languages propose. we base our discussion on the common ground of coordination models and we sketch a comparison between such approaches.
exploiting partial decision trees for feature subset selection in e-mail categorization. in this paper we propose partfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. in particular, it is shown that an aggressive reduction of the feature space can be achieved with partfs while still allowing for comparable classification results with conventional feature selection metrics. the approach is empirically verified by employing two different document representations and four different text classification algorithms that are applied to a document collection consisting of personal e-mail messages. the results show that a reduction of the feature space in the magnitude of ten is achievable without loss of classification accuracy.
a geolibrary for multimedia data sets: design and implementation issues. this paper describes the design and implementation issues of the steplib geolibrary. steplib aims to manipulate both spatiotemporal and multimedia data. currently, the steplib model supports maps, still images, video, audio and documents, as first class objects. this allows not only for the support of storage and presentation capabilities, but also for indexing and searching of these complex data types. metadata are used in the model to represent semantic abstraction of the underlying geo-objects, based on different layers of abstraction. spatiotemporal operations are performed at various levels, and data type specific operations are available for improving searching on multimedia data.
organizational engineering in public administrations: a method for process-oriented egovernment projects. in the move of egovernment, process analysis and optimization of administrative procedures are key prerequisites for successful organizational and technical re-structuring of municipal administrations. the full exploitation of the potential of information and communications technology can only be achieved through structured procedures. an integrated process view, which gives an overview of organization units, is vital in the context of any attempts at administration modernization. the high degree of complexity of process models, resulting from the multitude of modelling aims, objects, methods and users, requires both systematic preparation, and a methodical approach to the implementation of process-oriented e-government projects. therefore this article provides a procedure model for process-oriented organizational engineering, with reference to the example of local government building permission procedures.
a privacy preserving web recommender system. in this paper we propose a recommender system that helps users to navigate though the web by providing dynamically generated links to pages that have not yet been visited and are of potential interest. to this end, traditional recommender systems use web usage mining (wum) techniques in order to automatically extract knowledge from web usage data. thanks to wum techniques we are able to classify users and adaptively provide useful recommendations. the drawback of a user classification approach is that it makes the system prone to privacy breaches.our contribution here is &pi;suggest, a privacy enhanced recommender system that allows for creating serendipity recommendations without breaching users privacy. we will show that our system does not provide malicious users with any mean to track or detect users activity or preferences.
cyber-surfing: the state-of-the-art in client server browsing and navigation. modern network technology has spawned an entirely new cybernetic experience: cyberspace surfing. this surfing is as much a social experience as an information gathering resource. while providing the communication infrastructure for an ever-increasing percentage of the global population, it is also becoming the focal point of an identifiable sub-culture of cybernauts who are attracted to the internet as moths to light. there is every indication that the forthcoming cyberspace revolution will have an even more dramatic impact on society than the microcomputer revolution.in this paper we analyze the cyber-surfing experience from the point of view of the supportive client-server technologies involved. on the basis of this analysis and some emerging trends we speculate on the future of cyberspace.