ppxscal/embedding_network huggingface dataset:
A quantitative computational model for complete partial metric spaces via formal balls†
Authors: Salvador Romaguera, Oscar Valero
Venue: Mathematical Structures in Computer Science (2009)

Given a partial metric space (X, p), we use (BX, ⊑dp) to denote the poset of formal balls of the associated quasi-metric space (X, dp). We obtain characterisations of complete partial metric spaces and sup-separable complete partial metric spaces in terms of domain-theoretic properties of (BX, ⊑dp). In particular, we prove that a partial metric space (X, p) is complete if and only if the poset (BX, ⊑dp) is a domain. Furthermore, for any complete partial metric space (X, p), we construct a Smyth complete quasi-metric q on BX that extends the quasi-metric dp such that both the Scott topology and the partial order ⊑dp are induced by q. This is done using the partial quasi-metric concept recently introduced and discussed by H. P. Künzi, H. Pajoohesh and M. P. Schellekens (Künzi et al. 2006). Our approach, which is inspired by methods due to A. Edalat and R. Heckmann (Edalat and Heckmann 1998), generalises to partial metric spaces the constructions given by R. Heckmann (Heckmann 1999) and J. J. M. M. Rutten (Rutten 1998) for metric spaces.
Characterizing Dynamic Data Driven Applications Systems (DDDAS) in Terms of a Computational Model
Authors: Frederica Darema
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

The DDDAS (Dynamic Data Driven Applications Systems) concept creates new capabilities in applications and measurements, through a new computational paradigm where application simulations can dynamically incorporate and respond to online field-data and measurements, and/or control such measurements. Such capabilities entail dynamic integration of the computational and measurement aspects of an application in a dynamic feed-back-loop, leading to unified SuperGrids of the computational and the instrumentation platforms. Examples of advances in applications capabilities enabled through DDDAS over traditional computational modeling methods, and advances in measurements methods, and instrumentation and sensor network systems, have appeared extensively in the literature. This paper concentrates in discussing a computational model representing the unified DDDAS computation-measurement environments, and asymptotic cases leading to traditional computational environments, data assimilation, and traditional control systems.
Comparing the performance of traditional cluster analysis, self-organizing maps and fuzzy C-means method for strategic grouping
Authors: Cenk Budayan, Irem Dikmen, M. Talat Birgonul
Venue: Expert Systems with Applications: An International Journal (2009)

Strategic group analysis comprises of clustering of firms within an industry according to their similarities with respect to a set of strategic dimensions and investigating the performance implications of strategic group membership. One of the challenges of strategic group analysis is the selection of the clustering method. In this study, the results of the strategic group analysis of Turkish contractors are presented to compare the performances of traditional cluster analysis techniques, self-organizing maps (SOM) and fuzzy C-means method (FCM) for strategic grouping. Findings reveal that traditional cluster analysis methods cannot disclose the overlapping strategic group structure and position of companies within the same strategic group. It is concluded that SOM and FCM can reveal the typology of the strategic groups better than traditional cluster analysis and they are more likely to provide useful information about the real strategic group structure.
Auto-completion for diagram editors based on graph grammars
Authors: Steffen Mazanek, Sonja Maier, Mark Minas
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

Graphs are known to be well-suited as an intermediate data structure in diagram editors. The syntax of a particular visual language can be defined by means of a graph grammar. In recent work we have proposed approaches to graph completion: given a possibly “incomplete” graph, this graph is modified in such a way that the resulting graph is a member of the grammar’s language. In this paper we describe how graph completion can be used to realize diagram completion, an important requirement for the realization of content assist in diagram editors. With our approach, the advantages of free-hand and structured editing can be effectively combined: drawing of diagrams with maximal freedom and powerful guidance whenever needed.
An adaptive PNN-DS approach to classification using multi-sensor information fusion
Authors: Ning Chen, Fuchun Sun, Linge Ding, Hongqiao Wang
Venue: Neural Computing and Applications (2009)

In this paper, an adaptive neural network approach to classification which combines modified probabilistic neural network and D-S evidence theory (PNN-DS) is proposed. It attempts to deal with the drawbacks of information uncertainty and imprecision using single classification algorithm. This PNN-DS approach firstly adopts a modified PNN to obtain posteriori probabilities and make a primary classification decision in feature-level fusion. Then posteriori probabilities are transformed to masses noting the evidence of the D-S evidential theory. Finally advanced D-S evidential theory is utilized to gain more accurate classification results in the last decision-level fusion. In order to implement PNN-DS, covariance matrices are firstly employed in the modified PNN module to replace the singular smoothing factor in the PNN&#x2019;s kernel function, and linear function is utilized in the pattern of summation layer. Secondly, the whole scheme of the proposed approach is explained in depth. Thirdly, three classification experiments are carried out on the proposed approach and a large amount of comparable analyses are done to demonstrate the effectiveness and robustness of the proposed approach. Experiments reveal that the PNN-DS outperforms BPNN-DS, which provides encouraging results in terms of classification accuracy and the speed of learning convergence.
Delegating revocations and authorizations in collaborative business environments
Authors: Hua Wang, Jinli Cao, Yanchun Zhang
Venue: Information Systems Frontiers (2009)

Efficient collaboration allows organizations and individuals to improve the efficiency and quality of their business activities. Delegations, as a signif icant approach, may occur as workflow collabora tions, supply chain collaborations, or collaborative commerce. Role-based delegation models have been used as flexible and efficient access management for collaborative business environments. Delegation revocations can provide significant functionalities for the models in business environments when the delegated roles or permissions are required to get back. However, problems may arise in the revocation process when one user delegates user U a role and another user delegates U a negative authorization of the role. This paper aims to analyse various role-based delegation revocation features through examples. Revocations are categorized in four dimensions: Dependency, Resilience, Propagation and Dominance. According to these dimensions, sixteen types of revocations exist for specific requests in collaborative business environments: DependentWeakLocalDelete, Dependent WeakLocalNegative, DependentWeakGlobalDelete, DependentWeakGlobalNegative, IndependentWeak LocalDelete, IndependentWeakLocalNegative, Inde pendentWeakGlobalDelete, IndependentWeakGlobal Negative, and so on. We present revocation delegating models, and then discuss user delegation authorization and the impact of revocation operations. Finally, comparisons with other related work are discussed.
Embedding Knowledge Patterns into OWL
Authors: Luigi Iannone, Alan Rector, Robert Stevens
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

We describe the design and use of the Ontology Pre-Processor Language (OPPL) as a means of embedding the use of Knowledge Patterns in OWL ontologies. We illustrate the specification of patterns in OPPL and discuss the advantages of its adoption by Ontology Engineers with respect to ontology generation, transformation, and maintainability. The consequence of the declarative specification of patterns will be their unambiguous description inside an ontology in OWL. Thus, OPPL enables an ontology engineer to work at the level of the pattern, rather than of the raw OWL axioms. Moreover, patterns can be analysed rigorously, so that the repercussions of their reuse can be better understood by ontology engineers and tools implementers. Thus the delivery of patterns with OPPL can provide a means of addressing the opacity and sustainability of OWL ontologies.
Calligraphic Shortcuts for Comics Creation
Authors: Ricardo Lopes, Tiago Cardoso, Nelson Silva, Manuel J. Fonseca
Venue: Proceedings of the 10th International Symposium on Smart Graphics (2009)

The interactive creation of comics on the World Wide Web has become increasingly relevant over the last few years as a way for amateur creators to produce, share and distribute their comics. However, web applications that allow this kind of creation still restrict users interaction by not considering the repetition of previous elements across a comics story. Moreover, they use very simple methods for creating new content, therefore not allowing visually complex and rich comics.In this paper, we present a solution that seeks to converge the creation of web comics with the basic principles of traditional paper comics. To that end, we propose a new approach that combines rich interaction methods and geometric transformations for free hand drawings with a retrieval mechanism based on calligraphic shortcuts, to retrieve previous elements of comics.Experimental evaluation with users demonstrated that our approach is better suited for these problems than existent applications. Our solution allows creating comics online with higher flexibility and efficiency, while achieving visually more complex and rich content.
Developing Content for LKIF: Ontologies and Frameworks for Legal Reasoning
Authors: Joost Breuker, Alexander Boer, Rinke Hoekstra, Kasper van den Berg
Venue: Proceeding of the 2006 conference on Legal Knowledge and Information Systems: JURIX 2006: The Nineteenth Annual Conference (2006)

In this article we present the structure and outline of the proposed content of the LKIF-Core ontology. LKIF is an interchange format for legal knowledge, under development in Estrella, a 6th framework European project. One of the layers of expressiveness in LKIF is to consist of a combination of the OWL-DL and SWRL knowledge representation languages. LKIF-Core adds an ontology containing definitions of basic legal concepts. A number of these concepts are used to define frameworks that capture their use in legal reasoning. LKIF-Core is intended to enable re-use in the construction of legal knowledge bases and as semantic grounding for the translation of existing knowledge formats into LKIF.
Incentives for social annotation
Authors: Heather Roinestad, John Burgoon, Benjamin Markines, Filippo Menczer
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

Researchers are exploring the use of folksonomies, such as in social bookmarking systems, to build implicit links between online resources. Users create and reinforce links between resources through applying a common tag to those resources. The effectiveness of using such community-driven annotation depends on user participation to provide the critical information. However, the participation of many users is motivated by selfish reasons. An effective way to encourage these users is to create useful or entertaining applications. We demo two such tools -- a browser extension for bookmark management and navigation and a game.
FPGA-based ROM-free network intrusion detection using shift-OR circuit
Authors: Wen-Jyi Hwang, Huang-Chun Roan, Ying-Nan Shih, Chia-Tien Dan Lo, Chien-Min Ou
Venue: Journal of Embedded Computing (2009)

This paper introduces a novel FPGA-based signature match co-processor that can serve as the core of a hardware-based network intrusion detection system (NIDS). The co-processor is based on simple shift registers and bitmap encoders for the efficient signature match in hardware. As compared with related work, experimental results show that the proposed work achieves higher throughput and less hardware resource in the FPGA implementations of NIDS systems.
Evaluation of Internet Connections
Authors: Andrzej Siemiński
Venue: Proceeding of the 2008 conference on New Trends in Multimedia and Network Information Systems (2008)

The user perceived latency of displaying Internet pages is one of main factors in his/her assessment of the network. There are many factors that have an influence on the latency. The paper studies one of them-the Internet connection provided by an ISP. Up to now, there is no comprehensive theoretical model of the relationship. Therefore, an experiment was necessary. During the experiment the latency of a variety of Web pages was measured. The results indicate that a popular assumption that tightly binds network throughput with browser latency is not well justified. The analysis of low level network connection properties shows a significant level of correlation between the duration of pages download and the trace route length between the browser and the source server. The trace routes to a given host recorded for a single ISP have a considerable, stable number of common hosts. Therefore, the analysis of trace routes can be used in the process of selection of an ISP.
Oblivious routing of highly variable traffic in service overlays and IP backbones
Authors: Murali Kodialam, T. V. Lakshman, James B. Orlin, Sudipta Sengupta
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

The emergence of new applications on the Internet like voice-over-IP, peer-to-peer, and video-on-demand has created highly dynamic and changing traffic patterns. In order to route such traffic with quality-of-service (QoS) guarantees without requiring detection of traffic changes in real-time or reconfiguring the network in response to it, a routing and bandwidth allocation scheme has been recently proposed that allows preconfiguration of the network such that all traffic patterns permissible within the network's natural ingress-egress capacity constraints can be handled in a capacity efficient manner. The scheme routes traffic in two phases. In the first phase, incoming traffic is sent from the source to a set of intermediate nodes and then, in the second phase, from the intermediate nodes to the final destination. The traffic in the first phase is distributed to the intermediate nodes in predetermined proportions that depend on the intermediate nodes. In this paper, we develop linear programming formulations and a fast combinatorial algorithm for routing under the scheme so as to maximize throughput (or, minimize maximum link utilization). We compare the throughput performance of the scheme with that of the optimal scheme among the class of all schemes that are allowed to even make the routing dependent on the traffic matrix. For our evaluations, we use actual Internet Service Provider topologies collected for the Rocketfuel project. We also bring out the versatility of the scheme in not only handling widely fluctuating traffic but also accommodating applicability to several widely differing networking scenarios, including i) economical Virtual Private Networks (VPNs); ii) supporting indirection in specialized service overlay models like Internet Indirection Infrastructure (i3); iii) adding QoS guarantees to services that require routing through a network-based middlebox; and iv) reducing IP layer transit traffic and handling extreme traffic variability in IP-over-optical networks without dynamic reconfiguration of the optical layer. The two desirable properties of supporting indirection in specialized service overlay models and static optical layer provisioning in IP-over-optical networks are not present in other approaches for routing variable traffic, such as direct source-destination routing along fixed paths.
Partial and Informative Common Subsumers in Description Logics
Authors: Simona Colucci, Eugenio Di Sciascio, Francesco Maria Donini, Eufemia Tinelli
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Least Common Subsumers in Description Logics have shown their usefulness for discovering commonalities among all concepts of a collection. Several applications are nevertheless focused on searching for properties shared by significant portions of a collection rather than by the collection as a whole. Actually, this is an issue we faced in a real case scenario that provided initial motivation for this study, namely the process of Core Competence extraction in knowledge intensive companies. The paper defines four reasoning services for the identification of meaningful common subsumers describing partial commonalities in a collection. In particular Common Sub-sumers adding informative content to the Least Common Subsumer are investigated, with reference to different DLs.
Codespector --a Tool for Increasing Source Code Quality
Authors: Mariusz Jadach, Bogumiła Hnatkowska
Venue: Proceeding of the 2005 conference on Software Engineering: Evolution and Emerging Technologies (2005)

Software quality is strictly connected with the source code quality. Coding standards may be very helpful in order to assure the high quality of the code, especially that they are supported by many application tools. The paper presents Codespector --the tool for checking the Java source files against a given coding standard. The rules of the standard are written using the special CRL language, elaborated by one of co-authors.
Signature verification (SV) toolbox: Application of PSO-NN
Authors: M. Taylan Das, L. Canan Dulger
Venue: Engineering Applications of Artificial Intelligence (2009)

Analysis of signature is a widely used and developed area of research for personal verification. A typical signature verification (SV) system generally consists of four components: data acquisition, pre-processing, feature extraction and verification. A reliable SV toolbox, based on the verification of off-line signatures is developed with the proposed algorithm. The technique is based on a neural network (NN) approach trained with particle swarm optimization (PSO) algorithm. To test the performance of the proposed PSO-NN algorithm two types of forgeries-unskilled and skilled-are examined. The experimental results are illustrated on the selected signature databases and presented herein.
Combining Multiple Interrelated Streams for Incremental Clustering
Authors: Zaigham Faraz Siddiqui, Myra Spiliopoulou
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

Many data mining applications analyze structured data that span across many tables and accumulate in time. Incremental mining methods have been devised to adapt patterns to new tuples. However, they have been designed for data in one table only. We propose a method for incremental clustering on multiple interrelated streams - a "multi-table stream": its components are streams that reference each other, arrive at different speeds and have attributes of a priori unknown value ranges. Our approach encompasses solutions for the maintenance of cach-es and sliding windows over the individual streams, the propagation of foreign keys across streams, the transformation of all streams into a single-table stream, and an incremental clustering algorithm that operates over that stream. We evaluate our method on two real datasets and show that it approximates well the performance of an ideal method that possesses unlimited resources and knows the future.
Mapping between compositional semantic representations and lexical semantic resources: towards accurate deep semantic parsing
Authors: Sergio Roa, Valia Kordoni, Yi Zhang
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper introduces a machine learning method based on bayesian networks which is applied to the mapping between deep semantic representations and lexical semantic resources. A probabilistic model comprising Minimal Recursion Semantics (MRS) structures and lexicalist oriented semantic features is acquired. Lexical semantic roles enriching the MRS structures are inferred, which are useful to improve the accuracy of deep semantic parsing. Verb classes inference was also investigated, which, together with lexical semantic information provided by VerbNet and PropBank resources, can be substantially beneficial to the parse disambiguation task.
Learning complementary multiagent behaviors: a case study
Authors: Shivaram Kalyanakrishnan, Peter Stone
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

As the reach of multiagent reinforcement learning extends to increasingly complex tasks, it is likely that the diverse challenges encountered can only be surmounted by combining the strengths of different learning methods. We consider this aspect of learning through the case study of Keepaway, a popular benchmark for multiagent reinforcement learning from the robot soccer domain. Whereas previous successful results in this domain have limited learning to an isolated, infrequent decision that amounts to a turn-taking behavior (Pass), we expand the agents' learning capability to include the more ubiquitous action of moving without the ball (GetOpen), such that at any given time, multiple agents are executing learned behaviors simultaneously. We introduce a policy search method for learning GetOpen to complement the temporal difference learning approach employed for learning Pass [4]. The learned GetOpen policy matches the best hand-coded policy for this task, and outperforms the best policy found when Pass is learned. We demonstrate that Pass and GetOpen can be learned simultaneously, and indeed that these learned behaviors specialize towards the counterpart behaviors with which they are trained.