ppxscal/embedding_network huggingface dataset:
Visual OntoBridge: Semi-automatic Semantic Annotation Software
Authors: Miha Grcar, Dunja Mladenic
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

Machine learning methods have been successfully used for data labeling, also referred to as data annotation, either in semi-automatic or fully automatic way. We present a system for semi-automatic annotation of Web service schemas and other resources with the motivation to support efficient browse and search through those resources and to enable efficient composition and execution of Web services. The presented system, Visual OntoBridge (VOB), provides a graphical user interface and employs a set of machine learning algorithms to support the user in the annotation task.
A Universal Metamodel and Its Dictionary
Authors: Paolo Atzeni, Giorgio Gianforme, Paolo Cappellari
Venue: Transactions on Large-Scale Data- and Knowledge-Centered Systems I (2009)

We discuss a universal metamodel aimed at the representation of schemas in a way that is at the same time model-independent (in the sense that it allows for a uniform representation of different data models) and model-aware (in the sense that it is possible to say to whether a schema is allowed for a data model). This metamodel can be the basis for the definition of a complete model-management system. Here we illustrate the details of the metamodel and the structure of a dictionary for its representation. Exemplifications of a concrete use of the dictionary are provided, by means of the representations of the main data models, such as relational, object-relational or XSD-based. Moreover, we demonstrate how set operators can be redefined with respect to our dictionary and easily applied on it. Finally, we show how such a dictionary can be exploited to automatically produce detailed descriptions of schema and data models, in a textual (i.e. XML) or visual (i.e. UML class diagram) way.
A new pattern matching approach to the recognition of printed Arabic
Authors: Ali M. Obaid
Venue: Proceedings of the Workshop on Computational Approaches to Semitic Languages (1998)

The paper presents a new segmentation-free approach to the Arabic optical character recognition. Extended with a suitable pre-and post-processing the method offers a simple and fast framework to develop a full OCR system. The method was developed primarily for the Naskhi font, it is however robust and flexible and can be easily extended.
A QoS-Driven Approach for Semantic Service Composition
Authors: Yixin Yan, Bin Xu, Zhifeng Gu, Sen Luo
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

Semantic information, which is well-regulated and easy to be retrieved, has greatly enriched the expressive ability of the Web. These advantages can be applied in Web Services to meet the increasing complexity of Web applications. In this paper, we propose a service composition approach. It combines the large-scaled Web Services and semantic information which is described in WSC’09. Besides, QoS has become a critical issue to evaluate the performance of Web applications. Being different from improving the QoS of single services, our approach focuses on the overall QoS of the service composition. The algorithm shows that the semantic information based and QoS driven approach improves the efficiency and QoS performance of service composition.
A customizable multiprocessor for Globally Asynchronous Locally Synchronous execution
Authors: Avinash Malik, Zoran Salcic, Alain Girault, Adam Walker, Sung Chul Lee
Venue: Proceedings of the 7th International Workshop on Java Technologies for Real-Time and Embedded Systems (2009)

This paper presents a novel execution architecture for Globally Asynchronous Locally Synchronous (GALS) systems, in our case particularly targeting system level programming language SystemJ. SystemJ extends Java with both synchronous and asynchronous concurrency and reactivity to control program execution. The proposed architecture is based on separating the control-driven and data-driven operations onto two types of processors, respectively control and data processors, and it is aimed at complex embedded applications designed as GALS. The control processor is introduced to execute efficiently the control constructs, which implement concurrency, reactivity, and control flow in SystemJ. The data processor executes the Java data-driven transformational operations and can be any traditional processor. Control and data processors form hybrid multiprocessors, called GALS multiprocessors, which can then be easily customized for specific application and are implemented as a system on programmable chip (SoPC). Benchmarks show significant improvement in code size and execution speed of the resulting architecture over traditional processors.
Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations Session
Venue: European Chapter Meeting of the ACL (2009)

The short papers reproduced here describe implemented systems that were presented at the demo session of EACL-2009 in Athens, March 30 - April 3, 2009. Upon the call for demos, a total of 33 papers were submitted. Each submission was reviewed by at least two members of the programme committee. Based on these reviews, 17 submissions were accepted for presentation at the demo session and publication in the conference proceedings. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
DTorial: An Interactive Tutorial Framework for Blind Users in a Web 2.0 World
Authors: Joshua Hailpern, Loretta Guarino Reid, Richard Boardman
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

Effective tutorial systems can help promote products by reducing barriers of learning new applications. With dynamic web applications becoming as complex as desktop programs, there is a growing need for online tutorial/help systems. For visually impaired users the key limitations of traditional help systems are 1) poor access to help content with assistive technology, and 2) frequent reliance on videos/images to identify parts of web applications and demonstrate functionality. In this paper, we present a new interaction model, targeted towards screen-reader users, that describes how to embed an interactive tutorial within a web application. The interaction model is demonstrated within a system called DTorial, a fully functional dynamic audio-based tutorial with embedded content. While remaining within the web application, users can rapidly access any tutorial content, injected inline near relevant application controls, allowing them to quickly apply what they just heard to the application itself, without ever losing their position or having to shift windows. The model and implementation are grounded in sighted user help-systems literature and an analysis of screen-reader and Web-Application interactions. Lessons learned from the incremental design and evaluations indicate that providing visually impaired users with dynamic, embedded, interactive audio-based tutorial systems can reduce the barriers to new Web-Applications.
Share Price Prediction Using Wavelet Transform and Ant Colony Algorithm for Parameters Optimization in SVM
Authors: Xiaoyu Fang, Tao Bai
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

In this paper, an integrated methodology of wavelet transform and ACO-SVM is applied to predicting share price. On the one hand, the instability of the time series could lead to decrease of prediction accuracy, so wavelet transform (WT) is employed as a preprocessor of SVM to eliminate the fluctuant component of original data. On the other hand, two parameters of SVM must be carefully predetermined in establishing an efficient LS-SVM model, in order to solve this problem, the ant colony optimization algorithm (ACO) is used to optimize the parameters of SVM. A practical prediction of Huaneng Guoji show that the integrated methodology of wavelet transform and ACO-SVM can serve as a promising alternative for share price prediction.
Demo abstract: Application of WINTeR industrial testbed to the analysis of closed-loop control systems in wireless sensor networks
Authors: Martin J. Murillo, Jeff A. Slipp
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

WINTeR is an open access, multi-user experimental facility which supports implementation and evaluation of wireless sensor networks for industrial applications in radio-harsh environments. An important new characteristic of the testbed is its ability to incorporate built-in and user generated dynamical models of industrial processes. This allows researchers to inexpensively and realistically evaluate wireless technologies, topologies and other variables in the context of direrent closed-loop dynamical systems. The present demo gives an overview of the testbed and introduces its real-time simulation abilities by utilizing three dynamical models of known processes with direrent response times. As two of a myriad of variables, the demonstration will show the effects of electromagnetic interference and topology in the response of such closed loop control systems.
Mechanism Study on N2O Reduced with Biomass Gas
Authors: Xiaoying Hu, Changqing Dong, Yongping Yang, Junjiao Zhang, Yongsheng Li, Hanfei Zhang, Zhihui Dong
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

The reduction of N2O by adding biomass gas as reburning fuel is studied on a small-scale vertical reactor tube and experimental results are analyzed using the theory of chemical kinetics. The result showed that for the flue gas containing a certain concentration of N2O, when the biomass gas contained H2, CH4, CO and CO2 was used, the reburning fuel ratio should be more than 1.4%. The decomposition of N2O is caused by free radicals, including H and OH in the process.
Making semantic topicality robust through term abstraction
Authors: Paul M. Heider, Rohini K. Srihari
Venue: Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions (2009)

Despite early intuitions, semantic similarity has not proven to be robust for splitting multiparty interactions into separate conversations. We discuss some initial successes with using thesaural headwords to abstract the semantics of an utterance. This simple profiling technique showed improvements over baseline conversation threading models.
A cross entropy based algorithm for reliability problems
Authors: Marco Caserta, Marta Cabo Nodar
Venue: Journal of Heuristics (2009)

The Cross Entropy method has recently been applied to combinatorial optimization problems with promising results. This paper proposes a Cross Entropy based algorithm for reliability optimization of complex systems, where one wants to maximize the reliability of a system through optimal allocation of redundant components while respecting a set of budget constraints. We illustrate the effectiveness of the proposed algorithm on two classes of problems, software system reliability optimization and complex network reliability optimization, by testing it on instances from the literature as well as on randomly generated large scale instances. Furthermore, we show how a Cross Entropy-based algorithm can be fine-tuned by using a training scheme based upon the Response Surface Methodology. Computational results show the effectiveness as well as the robustness of the algorithm on different classes of problems.
Formalising FinFuns --- Generating Code for Functions as Data from Isabelle/HOL
Authors: Andreas Lochbihler
Venue: Proceedings of the 22nd International Conference on Theorem Proving in Higher Order Logics (2009)

FinFuns are total functions that are constant except for a finite set of points, i.e. a generalisation of finite maps. We formalise them in Isabelle/HOL and present how to safely set up Isabelle's code generator such that operations like equality testing and quantification on FinFuns become executable. On the code output level, FinFuns are explicitly represented by constant functions and pointwise updates, similarly to associative lists. Inside the logic, they behave like ordinary functions with extensionality. Via the update/constant pattern, a recursion combinator and an induction rule for FinFuns allow for defining and reasoning about operators on FinFuns that directly become executable. We apply the approach to an executable formalisation of sets and use it for the semantics for a subset of concurrent Java.
Domain Name Valuation Model Based on Semantic Theory and Content Analysis
Authors: Zu-guang Wu, Guo-hua Zhu, Rui Huang, Bin Xia
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

Domain name is a new type intangible of enterprise and it is important to value it in firm’s management and control system.For the reason that we don’t recognize and measure the domain self-constructed in financial accounting system,there are little study on domain’s value estimation and the factors influencing its value.For the absence of value measurement, domain name’s valuation management is weak in firm.With the growth of domain trade-off,How to value it become crisis important.we find that traditional estimation methods,such as discount cash flow method etc,ignore some crucial non-financial factors that influence the domain value for instance creativity. we use the semantic theory and content analysis to analyze the value-influence factors which include Domain structure and Meaning and Impression and Creativity etc. Based on the analysis we establish a two-stage model which integrate the financial and non-financial factors to value the domain name using fuzzy method. Finally we give anconcrete example to illustrate the use of the model. The originity of the model is that it is based on semantic theory and content analysis and the model combines the traditional method with the modification process forming a two-stage model.
Satellite image segmentation using hybrid variable genetic algorithm
Authors: Mohamad M. Awad, Kacem Chehdi
Venue: International Journal of Imaging Systems and Technology (2009)

Image segmentation is an important task in image processing and analysis. Many segmentation methods have been used to segment satellite images. The success of each method depends on the characteristics of the acquired image such as resolution limitations and on the percentage of imperfections in the process of image acquisition due to noise. Many of these methods require a priori knowledge which is difficult to obtain. Some of them are parametric statistical methods that use many parameters which are dependent on image property. In this article, a new unsupervised nonparametric method is developed to segment satellite images into homogeneous regions without any a priori knowledge. The new method is called hybrid variable genetic algorithm (HVGA). The variability is found in the variable number of cluster centers and in the changeable mutation rate. In addition, this new method uses different heuristic processes to increase the efficiency of genetic algorithm in avoiding local optimal solutions. Experiments performed on two different satellite images (Landsat and Spot) proved the high accuracy and efficiency of HVGA compared with another two unsupervised and nonparametric segmentation methods genetic algorithm (GA) and self-organizing map (SOM). The verification of the results included stability and accuracy measurements using an evaluation method implemented from the functional model (FM) and field surveys. &copy; 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 199&ndash;207, 2009
ViridiScope: design and implementation of a fine grained power monitoring system for homes
Authors: Younghun Kim, Thomas Schmid, Zainul M. Charbiwala, Mani B. Srivastava
Venue: Proceedings of the 11th international conference on Ubiquitous computing (2009)

A key prerequisite for residential energy conservation is knowing when and where energy is being spent. Unfortunately, the current generation of energy reporting devices only provide partial and coarse grained information or require expensive professional installation. This limitation stems from the presumption that calculating per-appliance consumption requires per-appliance current measurements. However, since appliances typically emit measurable signals when they are consuming energy, we can estimate their consumption using indirect sensing. This paper presents ViridiScope, a fine-grained power monitoring system that furnishes users with an economical, self-calibrating tool that provides power consumption of virtually every appliance in the home. ViridiScope uses ambient signals from inexpensive sensors placed near appliances to estimate power consumption, thus no in-line sensor is necessary. We use a model-based machine learning algorithm that automates the sensor calibration process. Through experiments in a real house, we show that ViridiScope can estimate the end-point power consumption within 10% error.
Adapting ADtrees for high arity features
Authors: Robert Van Dam, Irene Langkilde-Geary, Dan Ventura
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

ADtrees, a data structure useful for caching sufficient statistics, have been successfully adapted to grow lazily when memory is limited and to update sequentially with an incrementally updated dataset. For low arity symbolic features, ADtrees trade a slight increase in query time for a reduction in overall tree size. Unfortunately, for high arity features, the same technique can often result in a very large increase in query time and a nearly negligible tree size reduction. In the dynamic (lazy) version of the tree, both query time and tree size can increase for some applications. Here we present two modifications to the ADtree which can be used separately or in combination to achieve the originally intended space-time tradeoff in the ADtree when applied to datasets containing very high arity features.
Persistence Diagrams of Cortical Surface Data
Authors: Moo K. Chung, Peter Bubenik, Peter T. Kim
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

We present a novel framework for characterizing signals in images using techniques from computational algebraic topology. This technique is general enough for dealing with noisy multivariate data including geometric noise. The main tool is persistent homology which can be encoded in persistence diagrams. These diagrams visually show how the number of connected components of the sublevel sets of the signal changes. The use of local critical values of a function differs from the usual statistical parametric mapping framework, which mainly uses the mean signal in quantifying imaging data. Our proposed method uses all the local critical values in characterizing the signal and by doing so offers a completely new data reduction and analysis framework for quantifying the signal. As an illustration, we apply this method to a 1D simulated signal and 2D cortical thickness data. In case of the latter, extra homological structures are evident in an control group over the autistic group.
Attending to multiple visual streams: Interactions between location-based and category-based attentional selection
Authors: Sabrina Fagioli, Emiliano Macaluso
Venue: Journal of Cognitive Neuroscience (2009)

Behavioral studies indicate that subjects are able to divide attention between multiple streams of information at different locations. However, it is still unclear to what extent the observed costs reflect processes specifically associated with spatial attention, versus more general interference due the concurrent monitoring of multiple streams of stimuli. Here we used a factorial design to disentangle the correlates of location-versus category-based selection processes during fMRI. In all conditions, participants were presented with two overlapping visual stimuli (red shapes and green shapes) in each hemifield. In different blocks, subjects either: (1) attended to one single stimulus category, red shapes or green shapes, in one hemifield; (2) attended to both stimulus categories in the same hemifield; (3) attended to one single stimulus category, but monitoring both hemifields at the same time; or (4) attended to one stimulus category in one hemifield, and the other category in the opposite hemifield. The behavioral data showed the expected costs of dividing spatial attention across the two hemifields, and the cost of monitoring two stimulus categories versus one category. The imaging data revealed activation of a dorsal fronto-parietal network, both for dividing spatial attention and for monitoring multiple stimulus categories. However, unlike behavioral data, the imaging results also showed a significant interaction between location-and category-based attention within the same network. This demonstrates that the fronto-parietal cortex engages in both of these selective attention functions, and that a mere increase in task difficulty cannot explain colocalization of these processes. We conclude that, under conditions of multiple streams monitoring, fronto-parietal regions control location-and category-based attentional selection.
On the Hairpin Completion of Regular Languages
Authors: Volker Diekert, Steffen Kopecki, Victor Mitrana
Venue: Proceedings of the 6th International Colloquium on Theoretical Aspects of Computing (2009)

The hairpin completion is a natural operation of formal languages which has been inspired by molecular phenomena in biology and by DNA-computing. The hairpin completion of a regular language is linear context-free and we consider the problem to decide whether the hairpin completion remains regular. This problem has been open since the first formal definition of the operation.In this paper we present a positive solution to this problem. Our solution yields more than decidability because we present a polynomial time procedure. The degree of the polynomial is however unexpectedly high, since in our approach it is more than n 14. Nevertheless, the polynomial time result is surprising, because even if the hairpin completion $\mathcal{H}$ of a regular language L is regular, there can be an exponential gap between the size of a minimal DFA for L and the size of a smallest NFA for $\mathcal{H}$.
Alternative Formulas for Rating Prediction Using Collaborative Filtering
Authors: Amar Saric, Mirsad Hadzikadic, David Wilson
Venue: Proceedings of the 18th International Symposium on Foundations of Intelligent Systems (2009)

This paper proposes and evaluates several alternate design choices for common prediction metrics employed by neighborhood-based collaborative filtering approach. It first explores the role of different baseline user averages as the foundation of similarity weighting and rating normalization in prediction, evaluating the results in comparison to traditional neighborhood-based metrics using the MovieLens data set. The approach is further evaluated on the Netflix movie data set, using a baseline correlation formula between movies, without meta-knowledge. For the Netflix domain, the approach is augmented with a significance weighting variant that results in an improvement over the original metric. The resulting approach is shown to improve accuracy for neighborhood-based collaborative filtering, and it is general and applicable to establishing relationships among agents with a common list of items which establish their preferences.