ppxscal/embedding_network huggingface dataset:
An Analysis of the Origin of Ontology Mismatches on the Semantic Web
Authors: Paul R. Smart, Paula C. Engelbrecht
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

Despite the potential of domain ontologies to provide consensual representations of domain-relevant knowledge, the open, distributed and decentralized nature of the Semantic Web means that individuals will rarely, if ever, countenance a common set of terminological and representational commitments during the ontology design process. More often than not, differences between ontologies are likely to occur, and this is the case even when the ontologies describe identical or overlapping domains of interest. Differences between ontologies are often referred to as ontology mismatches and there is an extensive research literature geared towards the technology-mediated reconciliation of such mismatches. Our approach in the current paper is not to comment on the relative merits or demerits of the various technological solutions that could be used to resolve ontological differences; rather, we aim to explore the reasons why such differences may arise in the first place. In addition to a review of the various factors that contribute to ontology mismatches on the Semantic Web, we also discuss a number of focus areas for future research in this area. An improved understanding of the origins of ontology mismatches will, we argue, complement existing research into semantic integration techniques. In particular, by understanding more about the complex cognitive, epistemic and socio-cultural factors associated with the ontology development process, we may be able to develop knowledge acquisition and modeling tools/techniques that attenuate the impact of ontology mismatches for large-scale information sharing and data integration on the Semantic Web.
Improved On-the-Fly Equivalence Checking Using Boolean Equation Systems
Authors: Radu Mateescu, Emilie Oudot
Venue: Proceedings of the 15th international workshop on Model Checking Software (2008)

Equivalence checking is a classical verification method for ensuring the compatibility of a finite-state concurrent system (protocol) with its desired external behaviour (service) by comparing their underlying labeled transition systems (Ltss) modulo an appropriate equivalence relation. The local (or on-the-fly) approach for equivalence checking combats state explosion by exploring the synchronous product of the Ltss incrementally, thus allowing an efficient detection of errors in complex systems. However, when the two Ltss being compared are equivalent, the on-the-fly approach is outperformed by the global one, which completely builds the Ltss and computes the equivalence classes between states using partition refinement. In this paper, we consider the approach based on translating the on-the-fly equivalence checking problem in terms of the local resolution of a boolean equation system (Bes). We propose two enhancements of the approach in the case of equivalent Ltss: a new, faster encoding of equivalence relations in terms of Bess, and a new local Bes resolution algorithm with a better average complexity. These enhancements were incorporated into the Bisimulator 2.0 equivalence checker of the Cadp toolbox, and they led to significant performance improvements w.r.t. existing on-the-fly equivalence checking algorithms.
Evolution Strategies for Direct Policy Search
Authors: Verena Heidrich-Meisner, Christian Igel
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

The covariance matrix adaptation evolution strategy (CMA-ES) is suggested for solving problems described by Markov decision processes. The algorithm is compared with a state-of-the-art policy gradient method and stochastic search on the double cart-pole balancing task using linear policies. The CMA-ES proves to be much more robust than the gradient-based approach in this scenario.
An Improved Recursive Frisch Scheme Identification Algorithm
Authors: Jens G. Linden, Tomasz Larkowski, Keith J. Burnham
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

A modification for a recently developed recursive Frisch scheme algorithm to identify dynamical linear time-invariant errors-in-variables systems is proposed for the case of white measurement noise. For the update of the estimated model parameters, a recursive bias-compensating least squares algorithm is considered. The estimate of the output measurement noise variance is determined using a conjugate gradient method, which tracks the smallest eigenvalue of a slowly varying matrix. The modification concerns the update of the input measurement noise variance estimate: the cost function which is based on the high order Yule-Walker equations is approximated using linearisations of the Frisch scheme equations. For this approximated cost function, a closed form solution for its minimum can be computed directly, which forms the update equation for the input measurement noise estimate. The local convergence properties of the corresponding iterative scheme are analysed in simulation.
From Schema and Model Translation to a Model Management System
Authors: Paolo Atzeni, Luigi Bellomarini, Francesca Bugiotti, Giorgio Gianforme
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

Model management addresses problems dealing with forms of collaboration among heterogeneous databases. This collaboration may include exchange of data, schema integration, synchronization, translation and, in general, any issue characterized by a data evolving scenario. It provides a structured framework allowing standard solutions to data programmability problems in terms of the application of some recurring operators. The main mid-term target in this field is the definition of a model management system, a software platform providing the data architect with a complete set of tools addressing a wide spectrum of possible problems. In this paper we recall MIDST, a platform that works as an applicator of schema transformations. It was firstly conceived to perform model-independent schema and data translation. Then it has been extended to an applicator of general schema transformations including model management operators. Leveraging on MIDST rich representation of models, schemas and data based on a metalevel approach, we reason about potentialities and possible developments of this platform with the target of laying the basis for a real runtime model management system.
An Interactive Computer Aided Decision Support System for Detection of Masses in Mammograms
Authors: Nico Karssemeijer, Andrea Hupse, Maurice Samulski, Michiel Kallenberg, Carla Boetes, Gerard Heeten
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

A mammographic screening workstation has been developed in which CAD results for mass detection are presented fundamentally different than in current practice. Instead of displaying all CAD findings as prompts the reader can probe image regions for the presence of CAD information. The aim of the system is to help radiologists with decision making rather than avoiding oversight errors. In a preliminary observer study we studied the effect of using the interactive CAD system. Four non-radiologists and two radiologists participated. Each observer read 60 cases two times, once with and once without CAD. The set included 20 cases with subtle cancers that were missed at screening. It was found that performance of the readers increased significantly with interactive use of CAD.
Customisable Model Transformations Based on Non-Functional Requirements
Authors: Ashley Sterritt, Vinny Cahill
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

The Model-to-Model (M2M) transformation stage in a Model-Driven Engineering (MDE) tool chain is used to bridge the large semantic gap between problem-domain abstractions and software artifacts. This transformation is typically specified in a closed, monolithic way. Since no two systems have identical requirements, some work has been done to create explicit support for customisation of the transformation process based on functional requirements. The same is not true for non-functional requirements.The contribution of this paper is a customizable M2M transformation process that takes as an input the users priorities, in terms of non-functional properties, to select between design trade-offs in the transformation. These trade-offs are expressed as contrasting architectural styles, which describe common patterns of interactions and constraints with well understood non-functional implications. The target of the M2M transformation is an Architecture Description Language (ADL) that can be used to express styles. Model checking tools can be used to ensure that styles are adhered to during the entire MDE process. This early work focuses on describing contrasting architectural styles that address distribution issues, such as fault tolerance.
Functional-Specialization Multi-Objective Real-Coded Genetic Algorithm: FS-MOGA
Authors: Naoki Hamada, Jun Sakuma, Shigenobu Kobayashi, Isao Ono
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

This paper presents a Genetic Algorithm (GA) for multi-objective function optimization. In multi-objective function optimization, we believe that GA should adaptively switch search strategies in the early stage and the last stage for effective search. Non-biased sampling and family-wise alternation are suitable to overcome local Pareto optima in the early stage of search, and extrapolation-directed sampling and population-wise alternation are effective to cover the Pareto front in the last stage. These situation-dependent requests make it difficult to keep good performance through the whole search process by repeating a single strategy. We propose a new GA that switches two search strategies, each of which is specialized for global and local search, respectively. This is done by utilizing the ratio of non-dominated solutions in the population. We examine the effectiveness of the proposed method using benchmarks and a real-world problem.
Mathematical Microprocessor Software: A ?x Comparison
Authors: Michael Andrews
Venue: IEEE Micro (1982)

Mathematical software has been analyzed almost exclusively in the context of large-scale systems. Here, five algorithms for square root evaluation are compared for use in small systems.
Integrated Model for Informal Inference Based on Neural Networks
Authors: Kyung-Joong Kim, Sung-Bae Cho
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Inference is one of human's high-level functionalities and it is not easy to implement in machine. It is believed that inference is not results of single neuron's activity. Instead, it is a complex activity generated by multiple neural networks. Unlike computer, it is more flexible and concludes differently even for the similar situations in case of human. In this paper, these characteristics are defined as "informality." Informality in inference can be implemented using the interaction of multiple neural networks with the inclusion of internal or subjective properties. Simple inference tasks such as pattern recognition and robot control are solved based on the informal inference ideas. Especially, fuzzy integral and behavior network methods are adopted to realize that. Experimental results show that the informal inference can perform better with more flexibility compared to the previous static approaches.
A Two Phases Statistical Approach for Dialog Management
Authors: David Griol, Lluìs F. Hurtado, Encarna Segarra, Emilio Sanchis
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

In this paper, we present a statistical methodology for dialog management. This methodology is based on a classification procedure that considers all of the previous history of the dialog and the result of the queries to the module that controls the application. The classification procedure is divided into two phases to generate the next system turn. We summarize the work that has been carried out to apply this methodology for developing a dialog system for booking sports facilities. A dialog simulation technique has been used to acquire a dialog corpus for this task and to develop a dialog manager following the proposed methodology. The final model has been evaluated using a corpus recorded for the task with real users.
Cooperative CBR System for Peer Agent Committee Formation
Authors: Hager Karoui, Rushed Kanawati, Laure Petrucci
Venue: Agents and Peer-to-Peer Computing: 5th International Workshop, AP2PC 2006, Hakodate, Japan, May 9, 2006, Revised and Invited Papers (2006)

This paper deals with the problem of peer agent selection in an unstructured P2P recommendation system. The problem is studied in the context of a collaborative P2P bibliographical data management and recommendation system. In this system, each user is assisted with a personal software agent that helps her/him in managing bibliographical data and recommending new bibliographical references that are known by peer agents. One key issue is to define the set of peer agents that can provide the most relevant recommendations. Here, we treat this problem by using CBR methodology. We aim at enhancing the system overall performances by reducing network load (i.e. number of contacted peers, avoiding redundancy) and enhancing the relevance of computed recommendations by reducing the number of noisy recommendations. The peer selection learning cycle is described in detail. Experimental results are also provided and discussed.
Supporting Parameter Sweep Applications with Synthesized Grid Services
Authors: Jürgen Hofer, Thomas Fahringer
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Specialized tools already provide support for creation and execution of parameter sweeps. In such applications many tasks perform similar computations for varying input parameters. So far however none of these existing tools integrates well into service-oriented architectures or allows parametric modeling directly at the service interface. We address exactly this gap and demonstrate practical applicability with a concrete system architecture and implementation. Moreover we extend our services with reduction operators well known from parallel programming that perform certain aggregations or selections over the result set from all tasks of a given parameter study. Our efforts are substantial extensions to previous work on the service synthesis tool the 'Otho Toolkit' that allows smooth integration of scientific applications into service-oriented Grids. An experimental evaluation concludes our paper.
A Bayesian Student Model without Hidden Nodes and its Comparison with Item Response Theory
Authors: Michel C. Desmarais, Xiaoming Pu
Venue: International Journal of Artificial Intelligence in Education (2005)

The Bayesian framework offers a number of techniques for inferring an individual's knowledge state from evidence of mastery of concepts or skills. A typical application where such a technique can be useful is Computer Adaptive Testing (CAT). A Bayesian modeling scheme, POKS, is proposed and compared to the traditional Item Response Theory (IRT), which has been the prevalent CAT approach for the last three decades. POKS is based on the theory of knowledge spaces and constructs item-to-item graph structures without hidden nodes. It aims to offer an effective knowledge assessment method with an efficient algorithm for learning the graph structure from data. We review the different Bayesian approaches to modeling student ability assessment and discuss how POKS relates to them. The performance of POKS is compared to the IRT two parameter logistic model. Experimental results over a 34 item Unix test and a 160 item French language test show that both approaches can classify examinees as master or non-master effectively and efficiently, with relatively comparable performance. However, more significant differences are found in favor of POKS for a second task that consists in predicting individual question item outcome. Implications of these results for adaptive testing and student modeling are discussed, as well as the limitations and advantages of POKS, namely the issue of integrating concepts into its structure.
Modeling some composite laminates subjected to temperature and humidity variations
Authors: Horatiu Teodorescu, Sorin Vlase, Virgil Mihalcica, Marian Vasii
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

Original models to estimate the behavior at temperature and humidity variations of some fibers reinforced composite structures are shown. Especially, the coefficients of thermal- and humidity expansion, along and perpendicular to fibers direction are presented. Two types of structures are taking into account: laminate [0/45/-45/90]s based on glass fibers reinforced epoxy resin and laminate [(0/90)2] based on carbon fibers reinforced epoxy resin.
Query reformulation, search performance, and term suggestion devices in question-answering tasks
Authors: Ying-Hsang Liu, Nicholas J. Belkin
Venue: Proceedings of the second international symposium on Information interaction in context (2008)

Capturing context within query in query reformulation tasks has been identified as a promising technique for supporting users who are engaged with interactive information retrieval systems. User queries represent the evolution of information problems. A deeper understanding of the structure and process of query reformulation, in particular, could provide further information for system adaptations. The present study characterizes the query reformulation process in two types of term suggestion devices, relevance feedback (RF) and Local Context Analysis (LCA), in simulated question-answering tasks using Rutgers' TREC-8 Interactive Track dataset. Four types of query reformulation were identified on the basis of semantic contents and relations, as well as sequences in users' modifications of queries. We found a significant relationship between the types of query reformulations and the use of term suggestion devices. But we did not find significant correlations between types of query reformulations and search performance. Some issues regarding systematic biases in query reformulations and capturing context within queries in interactive IR system are discussed.
Round Peg, Square Hole: Supporting Via the Web Staff and Learners Who Do Not Fit into Traditional Learner-Teacher-Institution Scenarios
Authors: Simon Ball, Alistair Mcnaught
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Increasingly learners are acquiring their learning in settings that do not feature a traditional learner-teacher-institution scenario. It is important if we are to meet our obligations of inclusive practice and education opportunities for all that we cater effectively for these learners. This may involve modifying the way we offer learning, or offering something completely new. This paper describes some of the key considerations in adapting learning or learning techniques to better suit those learners.
Background Subtraction Based on Local Orientation Histogram
Authors: Dongheon Jang, Xianghua Jin, Yongjun Choi, Taeyong Kim
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

Background Subtraction is an important preprocessing step for extracting the features of tracking objects in the vision-based HCI system. In this paper, the orientation histogram between the foreground image and the background image is compared to extract the foreground probability in the local area. The orientation histogram-based method is partially robust against illumination change and small moving objects in background. There are two major drawbacks of using histograms which are quantization errors in histogram binning and slow computation speed. With Gaussian binning and integral histogram, we present the recursive partitioning method that gives false detection suppression and fast computation speed.
Identification of Hammerstein Model of Intelligence Sensor Based on Hybrid Neural Networks
Authors: Xuewen Wu, Limin Zha
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

An identification method based on hybrid neural networks for Hammerstein model is investigated in this paper to analyze the nonlinear dynamic system of intelligence sensor, and the corresponding algorithm is presented. In this model, the nonlinear dynamic characteristic of sensor is expressed by cascading a nonlinear static subunit (NLSS) with a linear dynamic subunit (LDS). According to the characteristic of the model, a PID nonlinear neural network (PID-NLNN) simulating the NLSS and a LDN linear neural network (LDN-LNN) simulating the LDS form a hybrid neural network (HNN), which is used to identify Hammerstein model. By means of the HNN approach, the parameter of the model can be identified and separated into two parts simultaneously, one part is the coefficient of the NLSS, the other is the coefficient of the LDS. The simulation has proved the efficiency of the proposed method.
Managing Large Scale Reuse Across Multiple Software Product Lines
Authors: N. Ilker Altintas, Semih Cetin
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

For large scale applications in today's competitive business environment, partial reuse at class, library, component or module level is still inadequate. Software product lines provide systematic reuse only within a product family. Better gains in productivity and high confidentiality can be achieved by large scale reuse across multiple product lines. This paper puts a methodical way, articulated as "Software Factory Automation", which can manage reusable assets across distinct software product lines based on "domain specific kits" and "software asset meta model". The approach is validated by analyzing the software asset reuse in two different product lines implemented in banking domain and practically used in real life. The results show that high level of reuse within and across multiple product lines can be achieved with the charted roadmap.