ppxscal/embedding_network huggingface dataset:
Simple Morpheme Labelling in Unsupervised Morpheme Analysis
Authors: Delphine Bernhard
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper describes a system for unsupervised morpheme analysis and the results it obtained at Morpho Challenge 2007. The system takes a plain list of words as input and returns a list of labelled morphemic segments for each word. Morphemic segments are obtained by an unsupervised learning process which can directly be applied to different natural languages. Results obtained at competition 1 (evaluation of the morpheme analyses) are better in English, Finnish and German than in Turkish. For information retrieval (competition 2), the best results are obtained when indexing is performed using Okapi (BM25) weighting for all morphemes minus those belonging to an automatic stop list made of the most common morphemes.
Measuring Brain Lesion Progression with a Supervised Tissue Classification System
Authors: Evangelia I. Zacharaki, Stathis Kanterakis, R. Nick Bryan, Christos Davatzikos
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Brain lesions, especially White Matter Lesions (WMLs), are associated with cardiac and vascular disease, but also with normal aging. Quantitative analysis of WML in large clinical trials is becoming more and more important. In this paper, we present a computer-assisted WML segmentation method, based on local features extracted from conventional multi-parametric Magnetic Resonance Imaging (MRI) sequences. A framework for preprocessing the temporal data by jointly equalizing histograms reduces the spatial and temporal variance of data, thereby improving the longitudinal stability of such measurements and hence the estimate of lesion progression. A Support Vector Machine (SVM) classifier trained on expert-defined WML's is applied for lesion segmentation on each scan using the AdaBoost algorithm. Validation on a population of 23 patients from 3 different imaging sites with follow-up studies and WMLs of varying sizes, shapes and locations tests the robustness and accuracy of the proposed segmentation method, compared to the manual segmentation results from an experienced neuroradiologist. The results show that our CAD-system achieves consistent lesion segmentation in the 4D data facilitating the disease monitoring.
A Problem Oriented Approach to Data Mining in Distributed Spatio-temporal Database
Authors: Zhou Huang, Yu Fang, Xia Peng, Bin Chen, Xuetong Xie
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Recently, a fast increment of spatio-temporal data volume has been achieved and more importantly the data might distribute everywhere. So, there is a need for spatio-temporal data mining systems that are able to support such distributed spatio-temporal query and analysis operations. Distributed spatio-temporal data mining technologies were discussed in this paper. After discussing the process of spatio-temporal data mining in distributed environment, one actual DSTDMS (Distributed Spatio-Temporal Data Mining System) was designed and then implemented. The system is based on data model of sequent snapshot and accomplished through spatio-temporal extension on PostgreSQL. Various spatio-temporal analyses and mining queries could be carried out in the system through simple SQL statements. By using the system, effective mining of distributed spatio-temporal data were achieved.
Fast Face Orientation Estimation from an Uncalibrated Monocular Camera
Authors: Xunheng Wang, Haiqing Huang, Zongcai Ruan, Zuhong Lu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In this paper we present a model based method for fast face orientation estimation and pose recovery from a monocular image sequence captured by an uncalibrated camera. To accomplish this method, CANDIDE-3 model is used to construct 3D individual face model manually. Four facial feature points (outer corners of eyes and mouth) are tracked by SIFT algorithm. Taking advantage of these feature points and 3D individual face model, facial pose recovery can be quickly completed with a Fast Face Orientation Estimation Algorithm. An experimental system has been built to carry out the estimation method. The estimation results are robust and flexible.
Japanese Neuroinformatics Node and Platforms
Authors: Shiro Usui, Teiichi Furuichi, Hiroyoshi Miyakawa, Hidetoshi Ikeno, Soichi Nagao, Toshio Iijima, Yoshimi Kamiyama, Tadashi Isa, Ryoji Suzuki, Hiroshi Ishikane
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Neuroinformatics is a new discipline which combines neuroscience with information technology. The Japan-Node of INCF was established at NIJC of RIKEN Brain Science Institute to address the task of integrating outstanding neuroscience researches in Japan. Each platform subcommittee from selected research areas develops a platform on the base-platform XooNIps. NIJC operates the J-Node portal to make platform resources open accessible in public. We introduce our concepts and the scheme of J-Node including nine platforms.
Recovering RC4 Permutation from 2048 Keystream Bytes if j Is Stuck
Authors: Subhamoy Maitra, Goutam Paul
Venue: Proceedings of the 13th Australasian conference on Information Security and Privacy (2008)

In this paper, we study the behaviour of RC4 when the index j is stuck at a certain value not known to the attacker. Though it seems quite natural that RC4 would be weak if j does not change, it has never been studied earlier in a disciplined manner. This work presents the nontrivial issues involved in the analysis, identifying how the information regarding S starts leaking with as low as 258 keystream output bytes. The leakage of information increases as more bytes are available and finally the complete S is recovered with 211 bytes in around 225 time complexity. The attack considers that "the deterministic index i at the point when j got stuck" and "the value at which j remains stuck" are unknown. Further, the study presents a nice combinatorial structure that is relevant to the fault analysis of RC4.
Design & Implementation of Mobile GUI Testing Tool
Authors: Sun-Myung Hwang, Hyeon-Cheol Chae
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

GUI of mobile application software has been used as important elements that users easely operate the software functions. Since it becomes established as an important factor of software success, GUI test is required for the software success. But its test takes much efforts and time. Therefore, we propose a method and automatic tool for mobile GUI test.
Computer-Aided Delivery of High-Intensity Focused Ultrasound (HIFU) for Creation of an Atrial Septal Defect in Vivo
Authors: Hiromasa Yamashita, Tetsuko Ishii, Akihiko Ishiyama, Noriyoshi Nakayama, Toshinobu Miyoshi, Yoshitaka Miyamoto, Gontaro Kitazumi, Yasumasa Katsuike, Makoto Okazaki, Takashi Azuma, Masayuki Fujisaki, Shinichi Takamoto, Toshio Chiba
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

In recent years, several fetal cardiac malformations have been increasingly treated before birth with gradually improved outcome, although the technique is still demanding and invasive. We newly developed a computer-aided system for energy delivery of high-intensity focused ultrasound (HIFU) to correct cardiac morphologic abnormalities in vivo much less invasively. The HIFU system could be controlled in real-time by a computer-based analysis of 2D-sonographic left ventricular images for optimal triggering off HIFU. Using beating heart of two anesthetized adult rabbits, the system successfully achieved a non-touch gross ablation of the atrial septum in one animal, and in the other HIFU energy was inadvertently mistargeted on the posterior wall of the left atrium with a resultant small transmural opening. We believe that the HIFU system will be introduced with pinpoint accuracy to minimally invasive treatment of fetal cardiac abnormalities that have intact or highly restrictive atrial septum.
Extending KDDML with a Visual Metaphor for the KDD Process
Authors: Valerio Grossi, Andrea Romei
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

The spreading application of data mining techniques is clearly represented by the large number of suites supporting the knowledge discovery process. The latter can be viewed as real visual programming environments. Based on this assumption, we define some requirements which a typical data mining high-level graphical user interface should satisfy, in order to guarantee a good level of interactivity and expressiveness. The aim of this study is to use these requirements during the engineering and development of visual knowledge flow abstraction for the existing KDDML (Knowledge Discovery in Databases Markup Language) system. We introduce some features not only directly related to the visual metaphor, but also to the whole system, here intended as a real visual programming environment for the knowledge discovery process.
Ripple effect in object oriented programs
Authors: Nashat Mansour, Hani Salem
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

Upon introducing a local change in a method or a class in an object oriented program, the ripple effect gives a measure of the amount by which this change may affect other methods/classes. That is, the ripple effect shows maintainers the ramifications of any change they may make before that change is actually implemented. In this paper, we propose techniques for measuring the ripple effect in object oriented programs and use it to compute an indicator of logical stability. First, we investigate object oriented dependences and illustrate how these dependences and some metrics can be used to determine change impact and propagation. Then, we use matrix arithmetic techniques for computing the ripple effect in object oriented programs and show their application at the intra-class, inter-class and architectural levels.
Optimizing high latency links in the developing world
Authors: Yaw Anokwa, Colin Dixon, Gaetano Borriello, Tapan Parikh
Venue: Proceedings of the 2008 ACM workshop on Wireless networks and systems for developing regions (2008)

Long distance Wi-Fi links, satellite connections, and other low-bandwidth, high-latency, intermittent options are becoming the norm for providing connectivity in the developing world. For network administrators who must manage these connections, providing users the "best" (or even adequate) service is not a trivial problem. Previous work has focused on optimizing throughput and while we acknowledge the importance of this approach, we argue that latency is an important and often ignored component of network performance. The intrinsically high latencies seen in the developing world are exacerbated by excessive queueing from traffic which often swamp links with miss-sized queues. Current solutions to this problem tend to require resources (people, time and money) that are generally not available in developing environments. In this paper, we demonstrate that latency is a problem in real world deployments and propose an easy to deploy solution.
A field-based versus a protocol-based approach for adaptive task assignment
Authors: Danny Weyns, Nelis Boucké, Tom Holvoet
Venue: Autonomous Agents and Multi-Agent Systems (2008)

Task assignment in multi-agent systems is a complex coordination problem, in particular in systems that are subject to dynamic and changing operating conditions. To enable agents to deal with dynamism and change, adaptive task assignment approaches are needed. In this paper, we study two approaches for adaptive task assignment that are characteristic for two classical families of task assignment approaches. FiTA is a field-based approach in which tasks emit fields in the environment that guide idle agents to tasks. DynCNET is a protocol-based approach that extends Standard Contract Net (CNET). In DynCNET, agents use explicit negotiation to assign tasks. We compare both approaches in a simulation of an industrial automated transportation system. Our experiences show that: (1) the performance of DynCNET and FiTA are similar, while both outperform CNET; (2) the complexity to engineer DynCNET is similar to FiTA but much more complex than CNET; (3) whereas task assignment with FiTA is an emergent solution, DynCNET specifies the interaction among agents explicitly allowing engineers to reason on the assignment of tasks, (4) FiTA is inherently robust to message loss while DynCNET requires substantial additional support. The tradeoff between (3) and (4) is an important criteria for the selection of an adaptive task assignment approach in practice.
Integrating Document-Based and Knowledge-Based Models for Clinical Guidelines Analysis
Authors: Gersende Georg, Marc Cavazza
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

Research in the computerization of Clinical Guidelines (CG) has often opposed document-based approaches to knowledge-based ones. In this paper, we suggest that both approaches can be used simultaneously to assess the contents of textual Clinical Guidelines. In this first experiment, we investigate the mapping between a document model, which has been marked-up to structure its recommendations, and a knowledge structure representing the management of specific disease. This knowledge representation is based on planning formalisms, more specifically Hierarchical Task Networks (HTN). Our system operates by first automatically encoding the textual guideline through the identification of specific expressions with surface natural language processing, as described in previous work. In a subsequent step, the HTN, constructed manually and independently, and represented as an explicit AND/OR graph, is searched for a solution sub-graph using an algorithm derived from AO*. Whilst the HTN is being traversed, corresponding information is accessed in the encoded textual CG, to guide the solution extraction process. We illustrate this through a case study developed around French guidelines for the management of hypertension. Recommendations included in the textual guideline provide complementary information for the instantiation of an HTN on specific patient data. The mapping takes place at different levels, from the pre-condition of operators to the rules playing a role as selection heuristics when extracting a solution sub-graph. Such a process, which explores the textual document from the prospective of a task model, can help analyzing the overall structure of clinical guidelines and ultimately improving its applicability.
On Automating the Calculus of Relations
Authors: Peter Höfner, Georg Struth
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

Relation algebras provide abstract equational axioms for the calculus of binary relations. They name an established area of mathematics and have found numerous applications in computing. We prove more than hundred theorems of relation algebras with off-the-shelf automated theorem provers. They form a basic calculus from which more advanced applications can be explored. We also present two automation experiments from the formal methods literature. Our results further demonstrate the feasibility of automated deduction with complex algebraic structures. They also open a new perspective for automated deduction in relational formal methods.
Towards Independent Software Architecture Review
Authors: Antony Tang, Fei-Ching Kuo, Man F. Lau
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

Many software architecture evaluation methods, proposed by the research community, have a common problem of engaging the same architects to perform architecture design and evaluation. This violates the independence of quality assurance and hence may lead to biased evaluation, thereby resulting in inferior architectural design. In this paper, we analyze current approaches and issues to software architecture quality assurance. We propose seven conditions for architectural design quality assurance and discuss existing challenges towards independent software architecture design review.
Categorization of Web Users by Fuzzy Clustering
Authors: Giovanna Castellano, Maria Alessandra Torsello
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

Categorization of users is a fundamental task in Web personalization. Fuzzy clustering is a valid approach to derive user categories by capturing similar user interests from web usage data available in log files. Usually, fuzzy clustering is based on the use of Euclidean metrics to evaluate similarity between user preferences. This can lead to user categories that do not capture the semantic information incorporated in the original Web usage data. To better capture similarity between users, in this paper we propose the use of a measure that is based on the evaluation of similarity between fuzzy sets. The proposed fuzzy measure is employed in a relational fuzzy clustering algorithm to discover clusters embedded in the Web usage data and derive categories modeling the preferences of similar users. An application example on usage data extracted from log files of a real Web site is reported and a comparison with the results obtained using the cosine measure is shown to demonstrate the effectiveness of the fuzzy similarity measure.
LEO-II - A Cooperative Automatic Theorem Prover for Classical Higher-Order Logic (System Description)
Authors: Christoph Benzmüller, Lawrence C. Paulson, Frank Theiss, Arnaud Fietzke
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

LEO-II is a standalone, resolution-based higher-order theorem prover designed for effective cooperation with specialist provers for natural fragments of higher-order logic. At present LEO-II can cooperate with the first-order automated theorem provers E, SPASS, and Vampire. The improved performance of LEO-II, especially in comparison to its predecessor LEO, is due to several novel features including the exploitation of term sharing and term indexing techniques, support for primitive equality reasoning, and improved heuristics at the calculus level. LEO-II is implemented in Objective Caml and its problem representation language is the new TPTP THF language.
Building Synthetic Graphical Documents for Performance Evaluation
Authors: Mathieu Delalandre, Tony Pridmore, Ernest Valveny, Hervé Locteau, Eric Trupin
Venue: Graphics Recognition. Recent Advances and New Opportunities: 7th International Workshop, GREC 2007, Curitiba, Brazil, September 20-21, 2007. Selected Papers (2008)

In this paper we present a system that allows to build synthetic graphical documents for the performance evaluation of symbol recognition systems. The key contribution of this work is the building of whole documents like drawings or maps. We exploit the layer property of graphical documents by positioning symbol sets in different ways from a same background using positioning constraints. Experiments are presented to build two kinds of test document databases : bags of symbol and architectural drawings.
Clustering-Based Reference Set Reduction for k-Nearest Neighbor
Authors: Seongseob Hwang, Sungzoon Cho
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Response Modeling is concerned with computing the likelihood of a customer to respond to a marketing campaign. A major problem encountered in response modeling is huge volume of data or patterns. The k-NN has been used in various classification problems for its simplicity and ease of implementation. However, it has not been applied to problems for which fast classification is needed since the classification time rapidly increases as the size of reference set increases. In this paper, we propose a clustering-based preprocessing step in order to reduce the size of reference set. The experimental results showed an 85% decrease in classification time without a loss of accuracy.
A Comparative Impact Study of Attribute Selection Techniques on Naïve Bayes Spam Filters
Authors: J. R. Méndez, I. Cid, D. Glez-Peña, M. Rocha, F. Fdez-Riverola
Venue: Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects (2008)

The main problem of Internet e-mail service is the massive spam message delivery. Everyday, millions of unwanted and unhelpful messages are received by Internet users annoying their mailboxes. Fortunately, nowadays there are different kinds of filters able to automatically identify and delete most of these messages. In order to reduce the bulk of information to deal with, only distinctive attributes are selected spam and legitimate e-mails. This work presents a comparative study about the performance of five well-known feature selection techniques when they are applied in conjunction with four different types of Naïve Bayes classifier. The results obtained from the experiments carried out show the relevance of choosing an appropriate feature selection technique in order to obtain the most accurate results.
Uncertainty Handling in Model Selection for Support Vector Machines
Authors: Tobias Glasmachers, Christian Igel
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

We consider evolutionary model selection for support vector machines. Hold-out set-based objective functions are natural model selection criteria, and we introduce a symmetrization of the standard cross-validation approach. We propose the covariance matrix adaptation evolution strategy (CMA-ES) with uncertainty handling for optimizing the new randomized objective function. Our results show that this search strategy avoids premature convergence and results in improved classification accuracy compared to strategies without uncertainty handling.
Dynamic Service Discovery Using Active Lookup and Registration
Authors: Haldor Samset, Rolv Bræk
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

Dynamic discovery of available service providers is a key factor in achieving an adaptable and loosely-coupled service-oriented architecture. We consider in this paper active services and how UML 2 collaborations can be used to define contracts for such services, in a way that it is suitable for discovery. We present a service discovery process where the service registry contains knowledge about possible substitutability relationships between the registered services. By extending the traditional lookup and registration services to become active services, the registry may take a more proactive role where it supervises the availability of service providers and actively gives notification to requestors when the availability status of service providers change.