ppxscal/embedding_network huggingface dataset:
Clustering and classifying person names by origin
Authors: Fei Huang, Stephan Vogel, Alex Waibel
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

In natural language processing, information about a person's geographical origin is an important feature for name entity transliteration and question answering. We propose a language-independent name origin clustering and classification framework. Provided with a small amount of bilingual name translation pairs with labeled origins, we measure origin similarities based on the perplexities of name character language and translation models. We group similar origins into clusters, then train a Bayesian classifier with different features. It achieves 84% classification accuracy with source names only, and 91% with both source and target name pairs. We apply the origin clustering and classification technique to a name transliteration task. The cluster-specific transliteration model dramatically improves the transliteration accuracy from 3.8% to 55%, reducing the transliteration character error rate from 50.3 to 13.5. Adding more unlabeled name pairs to the cluster-specific name transliteration model further improves the transliteration accuracy.
Improved Inapproximability Results for Maximum k-Colorable Subgraph
Authors: Venkatesan Guruswami, Ali Kemal Sinop
Venue: Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (2009)

We study the maximization version of the fundamental graph coloring problem. Here the goal is to color the vertices of a k-colorable graph with k colors so that a maximum fraction of edges are properly colored (i.e. their endpoints receive different colors). A random k-coloring properly colors an expected fraction $1-\frac{1}{k}$ of edges. We prove that given a graph promised to be k-colorable, it is NP-hard to find a k-coloring that properly colors more than a fraction of edges. Previously, only a hardness factor of $1- O\bigl(\frac{1}{k^2}\bigr)$ was known. Our result pins down the correct asymptotic dependence of the approximation factor on k. Along the way, we prove that approximating the Maximum 3-colorable subgraph problem within a factor greater than $\frac{32}{33}$ is NP-hard.Using semidefinite programming, it is known that one can do better than a random coloring and properly color a fraction $1-\frac{1}{k} +\frac{2 \ln k}{k^2}$ of edges in polynomial time. We show that, assuming the 2-to-1 conjecture, it is hard to properly color (using k colors) more than a fraction $1-\frac{1}{k} + O\left(\frac{\ln k}{k^2}\right)$ of edges of a k-colorable graph.
Efficient Parsing Using Recursive Transition Networks with Output
Authors: Javier M. Sastre-Martínez, Mikel L. Forcada
Venue: Human Language Technology. Challenges of the Information Society: Third Language and Technology Conference, LTC 2007, Poznan, Poland, October 5-7, 2007, Revised Selected Papers (2009)

We describe here two efficient parsing algorithms for natural language texts based on an extension of recursive transition networks (RTN) called recursive transition networks with string output (RTNSO). RTNSO-based grammars can be semiautomatically built from samples of a manually built syntactic lexicon. Efficient parsing algorithms are needed to minimize the temporal cost associated to the size of the resulting networks. We focus our algorithms on the RTNSO formalism due to its simplicity which facilitates the manual construction and maintenance of RTNSO-based linguistic data as well as their exploitation.
Can reinforcement learning explain the development of causal inference in multisensory integration?
Authors: Thomas H. Weisswange, Constantin A. Rothkopf, Tobias Rodemann, Jochen Triesch
Venue: Proceedings of the 2009 IEEE 8th International Conference on Development and Learning (2009)

Bayesian inference techniques have been used to understand the performance of human subjects on a large number of sensory tasks. Particularly, it has been shown that humans integrate sensory inputs from multiple cues in an optimal way in many conditions. Recently it has also been proposed that causal inference [1] can well describe the way humans select the most plausible model for a given input. It is still unclear how those problems are solved in the brain. Also, considering that infants do not yet behave as ideal observers [2]–[4], it is interesting to ask how the related abilities can develop. We present a reinforcement learning approach to this problem. An orienting task is used in which we reward the model for a correct movement to the origin of noisy audio visual signals. We show that the model learns to do cue-integration and model selection, in this case inferring the number of objects. Its behaviour also includes differences in reliability between the two modalities. All of that comes without any prior knowledge by simple interaction with the environment.
Legal docket-entry classification: where machine learning stumbles
Authors: Ramesh Nallapati, Christopher D. Manning
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

We investigate the problem of binary text classification in the domain of legal docket entries. This work presents an illustrative instance of a domain-specific problem where the state-of-the-art Machine Learning (ML) classifiers such as SVMs are inadequate. Our investigation into the reasons for the failure of these classifiers revealed two types of prominent errors which we call conjunctive and disjunctive errors. We developed simple heuristics to address one of these error types and improve the performance of the SVMs. Based on the intuition gained from our experiments, we also developed a simple propositional logic based classifier using hand-labeled features, that addresses both types of errors simultaneously. We show that this new, but simple, approach outperforms all existing state-of-the-art ML models, with statistically significant gains. We hope this work serves as a motivating example of the need to build more expressive classifiers beyond the standard model classes, and to address text classification problems in such non-traditional domains.
Guiding a Driver's Visual Attention Using Graphical and Auditory Animations
Authors: Tony Poitschke, Florian Laquai, Gerhard Rigoll
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

This contribution presents our work towards a system that autonomously guides the user's visual attention on important information (e.g., traffic situation or in-car system status signal, etc.) in error prone situations while driving a car. Therefore we use a highly accurate head-mounted eye-tracking system to estimate the driver's current focus of visual attention. Based on this data, we present our strategies to guide the driver's attention to where he should focus his attention. These strategies use both graphical animations in form of a guiding point on the Graphical User Interface as well as auditory animation that are present via headphones using a Virtual Acoustics system. In the end of this contribution, we present the results from a usability study.
Studying Reactive, Risky, Complex, Long-Spanning, and Collaborative Work: The Case of IT Service Delivery
Authors: Eser Kandogan, Eben M. Haber, John H. Bailey, Paul P. Maglio
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part IV: Interacting in Various Application Domains (2009)

IT service delivery is challenging to study. It is characterized by interacting systems of technology, people, and organizations. The work is sometimes reactive, sometimes carefully planned, often risky, and always complex and collaborative. In this paper we describe how we've learned about IT work, using a variety of methods including naturalistic observations, contextual interviews, surveys, and diary studies. We provide examples of our study results, showing what we've learned with the different methods. We argue that to effectively study such systems, a variety of methods may be needed to complement insights and validate findings. We found that naturalistic observations were extremely time and labor intensive, yet offered us the time and space to observe unplanned events and long-lasting tasks, bringing out the full complexity and risks involved in real work. Contextual interviews and diary studies provided fewer details, yet gave a broader context to individual's work. Surveys provided an even broader picture, going beyond individual differences, yet they were limited by details and issues of sampling.
Metacognition in understanding multimedia presentations
Authors: Alessandro Antonietti, Barbara Colombo, Wolfgang Schnotz, Roxana Moreno, Scott Marley, John Helak, Stephen M. Fiore, Haydee M. Cuevas, Sandro Scielzo
Venue: Proceedings of the 8th international conference on International conference for the learning sciences - Volume 3 (2008)

The symposium is aimed at highlighting the role that the awareness about the mental processes which are activated and the control over such processes play in comprehending and memorizing notions presented through texts and pictures. The attempt is to support the notion that promoting metacognition could improve the effectiveness of multimedia tools. In fact, metacognition should bring students to develop adequate strategies to learn from text-picture combinations. The contributions included in the symposium present a set of different ways of interpreting the links between metacognition and multimedia learning and show a series of experimental approaches that can be followed to investigate such links.
LTH: semantic structure extraction using nonprojective dependency trees
Authors: Richard Johansson, Pierre Nugues
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

We describe our contribution to the SemEval task on Frame-Semantic Structure Extraction. Unlike most previous systems described in literature, ours is based on dependency syntax. We also describe a fully automatic method to add words to the FrameNet lexical database, which gives an improvement in the recall of frame detection.
Landscape Restoration Regionalization for Resource-Exhausted Coal Mine Areas Based on GIS
Authors: Linlin Wang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Ecological restoration has been coming to be an important task in China, especially in resource-exhausted areas. Landscape restoration regionalization is a necessary part of it. This paper discussed the aim and meaning of landscape restoration regionalization firstly, ascertained the process for it. Then taking the abandoned mining areas of Mentougou District (MTG) of Beijing as an example, the author partitioned the landscape restoration regions of MTG based on GIS. The suitable function of each unit was confirmed, and the landscape units and structure which need to be restored was found. In this paper, 16 landscape restoration regions were partitioned, and the restoration orientation and restoration manner were also confirmed.
Study on Software and Hardware Control of High-Precision Measurement Platform for Optical Aspheric Surface
Authors: Xiaolong Ke, Yinbiao Guo, Longxing Guo
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

Taking high generality and efficiency into account, this paper presents a measurement and control means based on high-precision measurement platform including high-precision linear motors, contacting and non-contacting measurement sensor of 0.1um resolution and a new developed of measuring software. This platform aims to achieve high-precision measurement for all kinds of optical aspheric workpieces for the detection accuracy of 2um/200*200mm. In this paper, a measurement platform which consist of granite gantry framework, 3 axes linear motors, circle grating rotary encoder, grating linear scales, 4 axes motion control card, linear motion ball guide, contacting and non-contacting measurement sensor and so on, is designed and implemented. Through finite element stress analysis, it can find that the framework well fulfills the accuracy demand. After designed the hardware of measurement platform, the related control software is developed. Finally, the experiments for this purpose are done to validate the measurement platform accuracy.
Learning with compositional semantics as structural inference for subsentential sentiment analysis
Authors: Yejin Choi, Claire Cardie
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Determining the polarity of a sentiment-bearing expression requires more than a simple bag-of-words approach. In particular, words or constituents within the expression can interact with each other to yield a particular overall polarity. In this paper, we view such subsentential interactions in light of compositional semantics, and present a novel learning-based approach that incorporates structural inference motivated by compositional semantics into the learning procedure. Our experiments show that (1) simple heuristics based on compositional semantics can perform better than learning-based methods that do not incorporate compositional semantics (accuracy of 89.7% vs. 89.1%), but (2) a method that integrates compositional semantics into learning performs better than all other alternatives (90.7%). We also find that "content-word negators", not widely employed in previous work, play an important role in determining expression-level polarity. Finally, in contrast to conventional wisdom, we find that expression-level classification accuracy uniformly decreases as additional, potentially disambiguating, context is considered.
Neural Network Smoothing of Geonavigation Data on the Basis of Multilevel Regularization Algorithm
Authors: Vladimir Vasilyev, Ildar Nugaev
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

The problem of increasing the accuracy of geonavigation data being used for the control of the drilling oil-gas well trajectory is considered. The approach to solving the problem based on the distortion and measurement noise filtration with the use of the smoothing neural network is proposed. The generalized algorithm of the smoothing neural network design on the basis of the multilevel regularization is discussed. The peculiarities of the algorithm realization with the use of the offered vector regularization criterion of network parameters ranking is considered. The example of smoothing the geonavigation data on the basis of designed RBF network is considered.
Brief paper: Supervisory fault tolerant control for a class of uncertain nonlinear systems
Authors: Hao Yang, Bin Jiang, Marcel Staroswiecki
Venue: Automatica (Journal of IFAC) (2009)

This paper focuses on the design of a unique scheme that simultaneously performs fault isolation and fault tolerant control for a class of uncertain nonlinear systems with faults ranging over a finite cover. The proposed framework relies on a supervisory switching among a family of pre-computed candidate controllers without any additional model or filter. The states are ensured to be bounded during the switching delay, which ends when the correct stabilizing controller has been selected. Simulation results about a flexible joint robotic example illustrate the efficiency of the proposed method.
Explorations on Object-Oriented Classification for Ground Targets from High-Resolution Image
Authors: Luo Lingjun, Hu Yan
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Under the constant advancement of remote sensing technology, more and more high spatial resolution data are becoming available, the developments not only greatly increased our capability and accuracy in information extraction but also opened new application opportunities. Existing research activities have focused on how to increase the utilization efficiency of high resolution data, particularly in a wide range of applications such as urban environment, urban-planning, precision agriculture, forest inventory and risk assessment, however, the overall level of automation is still low. The paper adopted the multi-feature information of high-resolution images, objected-oriented image analysis approaches and multi-scale image segmentation technology, established a corresponding relevant knowledge base to extract information. Also the results show the new approach provided a satisfying solution to improve the level of autoimmunization and intelligentization of high-resolution remote sensing data process and application
Efficient Traceable Signatures in the Standard Model
Authors: Benoît Libert, Moti Yung
Venue: Proceedings of the 3rd International Conference Palo Alto on Pairing-Based Cryptography (2009)

Traceable signatures (TS), suggested by Kiayias, Tsiounis and Yung, extend group signatures to address various basic traceability issues beyond merely identifying the anonymous signer of a rogue signature. Namely, they enable the efficient tracing of all signatures produced by a misbehaving party without opening the identity of other parties. They also allow users to provably claim ownership of a previously signed anonymous signature. To date, known TS systems all rely on the random oracle model. In this work we present the first realization of the primitive that avoids resorting to the random oracle methodology in its security proofs. Furthermore, our realization's efficiency is comparable to that of nowadays' fastest and shortest standard model group signatures.
Independent Global Constraints Web Service Composition Optimization Based on Color Petri Net
Authors: Liu Xiangwei, Xu Zhicai
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

Under the service-oriented circumstances, developers can rapidly create applications through Web service composition, but the wholly intellectualized automatic composition is a very complicated process. So, many applications and research about composite services emphasize on semi-automatic mode. This paper presents independent global constrains-aware Web service composition method based on Color Petri net (CPN) and genetic algorithm (GA). Firstly, a CPN modeling methods which can describe multi-attribute multi-constraint relations and associate relation between component services is proposed. Secondly, combining with the properties of CPN, GA is used to search a legal firing sequence in the CPN model, and the composite service corresponding to the legal firing sequence. Using legal firing sequences of the Petri net makes the service composition locating space based on GA shrink greatly. Theoretical analysis and experimental results indicate that this method owns both lower computation cost and higher success ratio of service composition.
Shaping the Future with Users --- Futures Research Methods as Tools for User-Centered Concept Development
Authors: Mikael Runonen, Petri Mannonen
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

We have identified four problems when developing futuristic concepts. Technologies cannot be used as boundaries for concept creation, there is a lot of room for surprises, user knowledge is bound to present day, and futuristic concepts are not easily communicable. We propose three methods from Futures Studies to tackle these problems, with the emphasis in developing futuristic product and service concepts in a business-to-business context. In this paper, we introduce the methods and discuss the possible benefits gained from their use.
Automatic essay grading with probabilistic latent semantic analysis
Authors: Tuomo Kakkonen, Niko Myller, Jari Timonen, Erkki Sutinen
Venue: Proceedings of the second workshop on Building Educational Applications Using NLP (2005)

Probabilistic Latent Semantic Analysis (PLSA) is an information retrieval technique proposed to improve the problems found in Latent Semantic Analysis (LSA). We have applied both LSA and PLSA in our system for grading essays written in Finnish, called Automatic Essay Assessor (AEA). We report the results comparing PLSA and LSA with three essay sets from various subjects. The methods were found to be almost equal in the accuracy measured by Spearman correlation between the grades given by the system and a human. Furthermore, we propose methods for improving the usage of PLSA in essay grading.
Research on 3D Interactive Simulation System for Li/MnO2 Coin Cell Production Line Based on Virtual Reality
Authors: Xiaoming Chen, Shuzhong Lin
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

A novel 3D interactive simulation system for Li/MnO2 coin cell production line was presented in this paper. In order to solve the shortcomings of using traditional solid model for static simulation, the 3D visualization of the model and interactive motion simulation for Li/MnO2 coin cell production line was realized by AutoCAD/3dsmax/VR-Platform interaction through the external software interface. The 3D assembling model was built by AutoCAD software and exported into the 3ds max environment by DWG format for rendering, and then channeled into VR-Platform software for creating virtual environment, human-computer interface and database connection inquiry for interactive simulation. Based on these techniques, the simulation system is achieved and provides an adequate interactive simulation interface for Li/MnO2 coin cell production line manufacturing process simulation, perfect information inquiries for designer and manager. Therefore the research of 3D interactive simulation system for Li/MnO2 coin cell production line has important research value and application prospect.
Pauses as an indicator of psycholinguistically valid multi-word expressions (MWEs)?
Authors: Irina Dahlmann, Svenja Adolphs
Venue: Proceedings of the Workshop on a Broader Perspective on Multiword Expressions (2007)

In this paper we investigate the role of the placement of pauses in automatically extracted multi-word expression (MWE) candidates from a learner corpus. The aim is to explore whether the analysis of pauses might be useful in the validation of these candidates as MWEs. The study is based on the assumption advanced in the area of psycholinguistics that MWEs are stored holistically in the mental lexicon and are therefore produced without pauses in naturally occurring discourse. Automatic MWE extraction methods are unable to capture the criterion of holistic storage and instead rely on statistics and raw frequency in the identification of MWE candidates. In this study we explore the possibility of a combination of the two approaches. We report on a study in which we analyse the placement of pauses in various instances of two very frequent automatically extracted MWE candidates from a learner corpus, i.e. the n-grams I don't know and I think I. Intuitively, they are judged differently in terms of holistic storage. Our study explores whether pause analysis can be used as an objective empirical criterion to support this intuition. A corpus of interview data of language learners of English forms the basis of this study.