ppxscal/embedding_network huggingface dataset:
Learning a Self-organizing Map Model on a Riemannian Manifold
Authors: D. J. Yu, E. R. Hancock, W. A. Smith
Venue: Proceedings of the 13th IMA International Conference on Mathematics of Surfaces XIII (2009)

We generalize the classic self-organizing map (SOM) in flat Euclidean space (linear manifold) onto a Riemannian manifold. Both sequential and batch learning algorithms for the generalized SOM are presented. Compared with the classical SOM, the most novel feature of the generalized SOM is that it can learn the intrinsic topological neighborhood structure of the underlying Riemannian manifold that fits to the input data. We here compared the performance of the generalized SOM and the classical SOM using real 3-Dimensional facial surface normals data. Experimental results show that the generalized SOM outperforms the classical SOM when the data lie on a curved Riemannian manifold.
Soft-supervised learning for text classification
Authors: Amarnag Subramanya, Jeff Bilmes
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

We propose a new graph-based semi-supervised learning (SSL) algorithm and demonstrate its application to document categorization. Each document is represented by a vertex within a weighted undirected graph and our proposed framework minimizes the weighted Kullback-Leibler divergence between distributions that encode the class membership probabilities of each vertex. The proposed objective is convex with guaranteed convergence using an alternating minimization procedure. Further, it generalizes in a straightforward manner to multi-class problems. We present results on two standard tasks, namely Reuters-21578 and WebKB, showing that the proposed algorithm significantly outperforms the state-of-the-art.
Realizing the costs: template-based surface realisation in the GRAPH approach to referring expression generation
Authors: Ivo Brugman, Mariët Theune, Emiel Krahmer, Jette Viethen
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

We describe a new realiser developed for the TUNA 2009 Challenge, and present its evaluation scores on the development set, showing a clear increase in performance compared to last year's simple realiser.
Statistical inference for doubly stochastic multichannel Poisson processes: A PCA approach
Authors: R. M. Fernández-Alcalá, J. Navarro-Moreno, J. C. Ruiz-Molina
Venue: Computational Statistics Data Analysis (2009)

Efficient computational algorithms for making inferences about the intensity process of an observed doubly stochastic multichannel Poisson process are designed. The proposed solution is based on a numerical version of principal component analysis (PCA) of stochastic processes and hence it can be applied simply with knowledge of the first- and second-order moments of the intensity process of interest. The technique provided is valid for solving all types of estimation problems: filtering, prediction and smoothing.
A framework for annotating information structure in discourse
Authors: Sasha Calhoun, Malvina Nissim, Mark Steedman, Jason Brenier
Venue: Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky (2005)

We present a framework for the integrated analysis of the textual and prosodic characteristics of information structure in the Switchboard corpus of conversational English. Information structure describes the availability, organisation and salience of entities in a discourse model. We present standards for the annotation of information status (old, mediated and new), and give guidelines for annotating information structure, i.e. theme/rheme and back-ground/kontrast. We show that information structure in English can only be analysed concurrently with prosodic prominence and phrasing. This annotation, using stand-off XML in NXT, can help establish standards for the annotation of information structure in discourse.
Automatic construction of domain-specific dictionaries on sparse parallel corpora in the Nordic languages
Authors: Sumithra Velupillai, Hercules Dalianis
Venue: Proceedings of the Workshop on Multi-source Multilingual Information Extraction and Summarization (2008)

Hall&aring; Norden is a web site with information regarding mobility between the Nordic countries in five different languages; Swedish, Danish, Norwegian, Icelandic and Finnish. We wanted to create a Nordic cross-language dictionary for the use in a cross-language search engine for Hall&aring; Norden. The entire set of texts on the web site was treated as one multilingual parallel corpus. From this we extracted parallel corpora for each language pair. The corpora were very sparse, containing on average less than 80 000 words per language pair. We have used the Uplug word alignment system (Tiedemann 2003a), for the creation of the dictionaries. The results gave on average 213 new dictionary words (frequency > 3) per language pair. The average error rate was 16 percent. Different combinations with Finnish had a higher error rate, 33 percent, whereas the error rate for the remaining language pairs only yielded on average 9 percent errors. The high error rate for Finnish is possibly due to the fact that the Finnish language belongs to a different language family. Although the corpora were very sparse the word alignment results for the combinations of Swedish, Danish, Norwegian and Icelandic were surprisingly good compared to other experiments with larger corpora.
Application of IPK (Information, Preferences, Knowledge) Paradigm for the Modelling of Precautionary Principle Based Decision-Making
Authors: Adam Maria Gadomski, Tomasz Adam Zimny
Venue: Critical Information Infrastructure Security: Third International Workshop, CRITIS 2008, Rome, Italy, October13-15, 2008. Revised Papers (2009)

The aim of the article is modelling of the decision-making, in which Precautionary Principle (PP) is applied. Decisions are often made under time constraints, in lack of proper information, preferences or knowledge (IPK). Since application of PP usually bears additional costs, it should be applied only when more efficient risk management policies are unavailable. Presented d-m framework based on the IPK conceptualization allows identification of PP application criteria and models PP as a decisional rule, which is usually applied when the potential threat is recognized, while the risk is not computational, or its assessment is not economically motivated. The proposed model uses the TOGA (Top-down Object-based Goal-oriented Approach) methodology as a modelling tool.
A Novel Wavelet Transform Algorithm for Feature Extraction of Hyperspectral Remote Sensing Image
Authors: Feng Jing, Shu Ning
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

A new feature extraction method of remote sensing image was proposed based on a novel wavelet transform algorithm. Different form binary wavelet transform partitions the frequency domain by constant Q criteria, the method can partition the frequency domain freely, through setting the ratio of bandwidth of adjacent wavelet. Feature extraction based on discrete cosine transform of the wavelet energy was performed. The results of C-means clustering and RBF neural networks classification experiments show that, the proposed feature of wavelet transform can effectively describe spectral curve, and has better classification rate than traditional wavelet transform.
Divided Chaotic Associative Memory for Successive Learning
Authors: Takahiro Hada, Yuko Osana
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

In this paper, we propose a Divided Chaotic Associative Memory for Successive Learning (DCAMSL). The proposed model is based on the Improved Chaotic Associative Memory for Successive Learning (ICAMSL) and the Divided Chaotic Associative Memory for Successive Learning using Internal Patterns (DCAMSL-IP) which were proposed in order to improve the storage capacity. In most of the conventional neural network models, the learning process and the recall process are divided, and therefore they need all information to learning in advance. However, in the real world, it is very difficult to get all information to learn in advance. So we need the model whose learning and recall processes are not divided. As such model, although some models have been proposed, their storage capacity is small. In the proposed DCAMSL, the learning process and the recall process are not divided and its storage capacity is larger than that of the conventional ICAMSL.
Quality standards versus taxation in a dynamic environmental model of a tourism economy
Authors: Javier Rey-Maquieira, Javier Lozano, Carlos M. Gómez
Venue: Environmental Modelling Software (2009)

The increasing economic importance of tourism activity stimulates research on the more adequate instruments to reach tourism policy targets. This paper concentrates on two tourism policy areas, namely the influence on the pattern of tourism specialization and the correction of environmental externalities, and two policy tools, that is, a tourism tax and an accommodation quality standard. Using a dynamic general equilibrium model for an economy specialized in tourism, we show that both instruments are effective in reaching those targets, although they differ in efficiency terms. The quality standard policy regime yields a more efficient tax system, as it makes Ricardian rents bear a higher share of the tax burden, but the quality standard is in itself distortionary and can create incentives for capital over-accumulation. Looking at the steady state, the quality standard allows for higher long run welfare than the tourism tax, provided that the former does not cause any dynamic inefficiency. More generally, the paper shows that a general equilibrium perspective can unveil possible unexpected complementarities between environmental and other policy targets and instruments as, in this case, quality standards aimed to influence the pattern of tourism specialization.
A Parallel Numerical Library for UPC
Authors: Jorge González-Domínguez, María J. Martín, Guillermo L. Taboada, Juan Touriño, Ramón Doallo, Andrés Gómez
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

Unified Parallel C (UPC) is a Partitioned Global Address Space (PGAS) language that exhibits high performance and portability on a broad class of shared and distributed memory parallel architectures. This paper describes the design and implementation of a parallel numerical library for UPC built on top of the sequential BLAS routines. The developed library exploits the particularities of the PGAS paradigm, taking into account data locality in order to guarantee a good performance. The library was experimentally validated, demonstrating scalability and efficiency.
A Hybrid Fuzzy Approach for Human Eye Gaze Pattern Recognition
Authors: Dingyun Zhu, B. Sumudu Mendis, Tom Gedeon, Akshay Asthana, Roland Goecke
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Face perception and text reading are two of the most developed visual perceptual skills in humans. Understanding which features in the respective visual patterns make them differ from each other is very important for us to investigate the correlation between human's visual behavior and cognitive processes. We introduce our fuzzy signatures with a Levenberg-Marquardt optimization method based hybrid approach for recognizing the different eye gaze patterns when a human is viewing faces or text documents. Our experimental results show the effectiveness of using this method for the real world case. A further comparison with Support Vector Machines (SVM) also demonstrates that by defining the classification process in a similar way to SVM, our hybrid approach is able to provide a comparable performance but with a more interpretable form of the learned structure.
Multi-level Validation of the ISOmetrics Questionnaire Based on Qualitative and Quantitative Data Obtained from a Conventional Usability Test
Authors: Jan-Paul Leuteritz, Harald Widlroither, Michael Klüh
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

Qualitative and quantitative data, collected during a usability evaluation of two innovative prototypes of a small display touch screen device, have been used to perform a multi-level assessment of the questionnaires used within the trial. The use of different validation methods is depicted and discussed concerning their advantages and disadvantages. The conclusions from the validation study are depicted, revealing that the usage of the ISOmetrics for testing uncommon prototypes may result in insufficient validity of the instrument.
The Design and Application of Enterprise Comprehensive Strength Evaluation Model based on Artificial Neural Network
Authors: Jin Zheng, Yubin Zhong
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

In this paper, we combine research the "Forbes" Top500 selection criteria and the indexes data of Real Estate Public Companies of China in 2005 and 2006, set up an indicators system, and proposed an enterprise’s comprehensive strength evaluation model based on neural network. Then we evaluate the comprehensive strength of Real Estate Public Companies of China in 2007. Finally, we compare the evaluate result with “Top 10 Real Estate Public Companies of China” issue by Top 10 Comprehensive Strength of Real Estate Public Companies Evaluation Research Group. The compare result show the business’s comprehensive strength evaluation model is effective and has certain value of theoretical and practical application.
The Pushdown Attack on AES
Authors: Mohamed Abo El-Fotouh, Klaus Diepold
Venue: Proceedings of the 2009 Third International Conference on Emerging Security Information, Systems and Technologies (2009)

We present a new idea on chosen plaintext cryptanalysis, where we can bypass some of the cipher's encryption rounds at its beginning. To illustrate this idea, we developed the Pushdown attack. This attack can increase the strength of some chosen plaintext attacks. We applied the Pushdown attack on AES and was able to achieve a 6-round attack that requires only 2$^{11}$ chosen plaintexts, this reduces the chosen plaintexts needed by the Square attack with a factor of 2$^{21}$.
Adaptive Security Dialogs for Improved Security Behavior of Users
Authors: Frederik Keukelaere, Sachiko Yoshihama, Scott Trent, Yu Zhang, Lin Luo, Mary Ellen Zurko
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

Despite the increasing awareness of the importance of security for daily computer users, we see that many users still fail to behave securely when confronted with a security-related decision. In this paper, we introduce a new approach to security-related dialogs called Adaptive Security Dialogs (ASD). This approach is a combination of a new architecture and a new way of interacting with users to provide them with appropriate and effective security dialogs. ASD realizes this goal by matching the complexity and intrusiveness of security-related dialogs to the risk associated with the decision the user is making. This results in an architecture in which users can focus on their tasks, get (immediate) feedback on their decisions, and interact with dialogs with an appropriate complexity and appearance for the decision's associated risk. This paper makes the following three contributions. First, we introduce a general architecture for handling security-related decisions. Second, through an empirical user study using a web-based e-mail client, we show significant improvement in the care exercised by our participants without sacrificing usability. Third, we describe how the different pieces of existing research fit into the bigger picture of improving users' behavior.
An English Vocabulary Learning System Based on Fuzzy Theory and Memory Cycle
Authors: Tzone I Wang, Ti Kai Chiu, Liang Jun Huang, Ru Xuan Fu, Tung-Cheng Hsieh
Venue: Proceedings of the 8th International Conference on Advances in Web Based Learning (2009)

This paper proposes an English Vocabulary Learning System based on the Fuzzy Theory and the Memory Cycle Theory to help a learner to memorize vocabularies easily. By using fuzzy inferences and personal memory cycles, it is possible to find an article that best suits a learner. After reading an article, a quiz is provided for the learner to improve his/her memory of the vocabulary in the article. Early researches use just explicit response (ex. quiz exam) to update memory cycles of newly learned vocabulary; apart from that approach, this paper proposes a methodology that also modify implicitly the memory cycles of learned word. By intensive reading of articles recommended by our approach, a learner learns new words quickly and reviews learned words implicitly as well, and by which the vocabulary ability of the learner improves efficiently.
A Game-Theoretic Model for Analyzing Fair Exchange Protocols
Authors: Yonggen Gu, Zhangguo Shen, Deqian Xue
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Fair exchange turns out to be an increasingly important topic due to the rapid growth of electronic commerce in daily life. In this paper, a novel model based on game theory is proposed in order to analyze fair exchange protocols. The formal description of fair exchange protocols is given, and two important properties --- non-repudiation and fairness --- are defined in this model. As an illustrating example, we analyze a certified email protocol, namely MD scheme.
Gradient clock synchronization in wireless sensor networks
Authors: Philipp Sommer, Roger Wattenhofer
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

Accurately synchronized clocks are crucial for many applications in sensor networks. Existing time synchronization algorithms provide on average good synchronization between arbitrary nodes, however, as we show in this paper, close-by nodes in a network may be synchronized poorly. We propose the Gradient Time Synchronization Protocol (GTSP) which is designed to provide accurately synchronized clocks between neighbors. GTSP works in a completely decentralized fashion: Every node periodically broadcasts its time information. Synchronization messages received from direct neighbors are used to calibrate the logical clock. The algorithm requires neither a tree topology nor a reference node, which makes it robust against link and node failures. The protocol is implemented on the Mica2 platform using TinyOS. We present an evaluation of GTSP on a 20-node testbed setup and simulations on larger network topologies.
A Collaborative Filtering Recommendation Algorithm Based on Item Genre and Rating Similarity
Authors: Ye Zhang, Wei Song
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

Aiming at the disadvantages of user-based collaborative filtering algorithm and item-based collaborative filtering algorithm on the instance of user’s rating data’s extreme sparseness, introducing the similarity of item genre and rating and improving on it. The high ratings of users group can also affect similarity when calculating the similarities of item genre and ratings. Through the experiment the improved algorithm can play down user’s mean absolute error and improve the quality of recommendation.
Research on the Changes in Lake Wetland in Hubei Province
Authors: Zhang Yi, Deng Hongbing, Hsiang-te Kung, Li Wenjie, Li Jintao
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

This paper analyzes the space-time change characteristics of the Hubei lake wetland in the past 100 years by means of GIS/RS technology and landscape ecology methods. We may safely draw a conclusion that the trend of Lake Wetland in Hubei province is dying out, the main lake which is the prompt core and carrier of the lake area wetland reduced rapidly, lakelet increases by unceasingly.
Handbook of Research on Business Process Modeling
Authors: Jorge Cardoso, Wil Van Der Aalst
Venue:  (2009)

Business managers are striving to move toward process-centric organizations, but the challenge remains in ensuring adoption of a business process culture. The Handbook of Research on Business Process Modeling aids managers in the transformation of organizations into world-class competitors through business process applications. A useful resource for business leaders, field researchers, and academicians in management, this reference book contains a repository to the most relevant and up-to-date information on business process modeling.
Towards the Complexity of Recognizing Pseudo-intents
Authors: Barış Sertkaya
Venue: Proceedings of the 17th International Conference on Conceptual Structures: Conceptual Structures: Leveraging Semantic Technologies (2009)

Pseudo-intents play a key rôle in Formal Concept Analysis. They are the premises of the implications in the Duquenne-Guigues Base, which is a minimum cardinality base for the set of implications that hold in a formal context. It has been shown that checking whether a set is a pseudo-intent is in conp. However, it is still open whether this problem is conp-hard, or it is solvable in polynomial time. In the current work we prove a first lower bound for this problem by showing that it is at least as hard as transversal hypergraph, which is the problem of identifying the minimal transversals of a given hypergraph. This is a prominent open problem in hypergraph theory that is conjectured to form a complexity class properly contained between p and conp. Our result explains why the attempts to find a polynomial algorithm for recognizing pseudo-intents have failed until now. We also formulate a decision problem, namely first pseudo-intent, and show that if this problem is not polynomial, then, unless p = np, pseudo-intents cannot be enumerated with polynomial delay in a specified lexicographic order.
Chain of circles for matching and recognition of planar shapes
Authors: Jae-Moon Chung, Noboru Ohnishi
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

Based on a resulting medial axis configuration of planar shapes, a new shape descriptor called the chain of circles (CoCs) is defined herein. The CoCs representation is directly extracted along the boundary contour of silhouette images, and can be controlled in a hierarchical manner which appeals to intuition. The coarsetofine hierarchy makes matching of shapes possible with less computational complexity and greater robustness to noise, spatial quantization and local deformation of shapes. The dissimilarity vector calculated in the matching, which is executed via the dynamic programming technique, may be used to facilitate the searching process in the digital library. The capability of the proposed method is shown by matching several complex shapes such as map images.
Distributional equation for Laguerre-Hahn functionals on the unit circle
Authors: A. Branquinho, M. N. Rebocho
Venue: Journal of Computational and Applied Mathematics (2009)

Let u be a Hermitian linear functional defined in the linear space of Laurent polynomials and F its corresponding Caratheodory function. We establish the equivalence between a Riccati differential equation with polynomial coefficients for F, zAF^'=BF^2+CF+D, and a distributional equation for u, D(Au)=B@?u^2+C@?u+H@?L, where L is the Lebesgue functional, and the polynomials B@?,C@?,H@? are defined in terms of the polynomials A,B,C,D.