ppxscal/embedding_network huggingface dataset:
Experimental Assessment of Accuracy of Automated Knowledge Capture
Authors: Susan M. Stevens, J. Chris Forsythe, Robert G. Abbott, Charles J. Gieseler
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

The U.S. armed services are widely adopting simulation-based training, largely to reduce costs associated with live training. However simulation-based training still requires a high instructor-to-student ratio which is expensive. Intelligent tutoring systems target this need, but they are often associated with high costs for knowledge engineering and implementation. To reduce these costs, we are investigating the use of machine learning to produce models of expert behavior for automated student assessment. A key concern about the expert modeling approach is whether it can provide accurate assessments on complex tasks of real-world interest. This study evaluates of the accuracy of model-based assessments on a complex task. We trained employees at Sandia National Laboratories on a Navy simulator and then compared their simulation performance to the performance of experts using both automated and manual assessment. Results show that automated assessments were comparable to the manual assessments on three metrics.
LinguaStream: an integrated environment for computational linguistics experimentation
Authors: Frédérik Bilhaut, Antoine Widlöcher
Venue: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations (2006)

By presenting the LinguaStream platform, we introduce different methodological principles and analysis models, which make it possible to build hybrid experimental NLP systems by articulating corpus processing tasks.
Providing Interference-Aware Quality of Service Support for ODMRP
Authors: Yao Yu, Yu Zhou, Sidan Du
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

Quality of Service (QoS) is a desirable feature for Mobile Ad Hoc Networks (MANETs) due to the growth of multimedia applications. However, due to the nature of MANETs, it imposes tight constraints on providing QoS assurance for multicast protocol in such networks. In this paper, we investigate the QoS and bandwidth consumption in On Demand Multicast Routing Protocol (ODMRP) under 2-hops interference model. A practical and effective extension of ODMRP, named ODMRP-IQoS, is proposed to provide interference-aware QoS support for ODMRP, which evaluates the available bandwidth and build the routes with sufficient bandwidth guaranteed. The simulation results suggest that ODMRP-IQoS outperforms ODMRP in terms of packet delivery ratio especially in the scenarios with heavy traffic load.
A method for unsupervised broad-coverage lexical error detection and correction
Authors: Nai-Lung Tsao, David Wible
Venue: Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications (2009)

We describe and motivate an unsupervised lexical error detection and correction algorithm and its application in a tool called Lexbar appearing as a query box on the Web browser toolbar or as a search engine interface. Lexbar accepts as user input candidate strings of English to be checked for acceptability and, where errors are detected, offers corrections. We introduce the notion of hybrid n-gram and extract these from BNC as the knowledgebase against which to compare user input. An extended notion of edit distance is used to identify most likely candidates for correcting detected errors. Results are illustrated with four types of errors.
An Evolutionary Based Wavelet Network for Business Failure Prediction
Authors: Dong Jingrong, Chen Jun
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

Forecasting business failure is an important and challenging task for both academic researchers and business practitioners. A large number of methods like discriminant analysis, log it analysis, neural networks,etc., have been used in the past for the prediction of business failure. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt firms, they suffer from some limitations, often due to the unrealistic assumption of statistical hypotheses or due to the learning problems of poor convergence in the training process. In this paper, an evolutionary based wavelet network is presented to discriminate between healthy and failing firms in order to predict business failure.Financial characteristics of a large sample of 256Chinese firms are used to train the proposed network and to evaluate its prediction ability. The results are very encouraging, compared with those of multiple discriminant analysis, log it regression and pure neural network, and prove the usefulness of the proposed method for business failure prediction.
On the Influence of Region Mismatch at Training and Testing in Region-Related Concept Detection
Authors: Zan Gao, Zhicheng Zhao, Tao Liu, Xiaoming Nan, Anni Cai
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

A great deal of region-related concept detection algorithms have been proposed so far, but there are few of them concerning about the problem of mismatched regions at training and testing stages. In order to investigate the mismatch problem in region-related concept detection, we introduce three kinds of methods to annotate the datasets, and then conduct experiments on differently annotated training and testing datasets. We find from these experiments that the detection performance is the best when the regions of a region-related concept are well defined and matched during training and testing, or the detection performance will be decreased. Based on these observations, we propose a fusion scheme to combine the results of classifiers trained with datasets which are annotated by different methods. Experiments on Trecvid-2007 test corpus show that the proposed fusion scheme can obtain performance improvement up to 6~12%.
Multi-HDP: a non parametric Bayesian model for tensor factorization
Authors: Ian Porteous, Evgeniy Bart, Max Welling
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Matrix factorization algorithms are frequently used in the machine leaming community to find low dimensional representations of data. We introduce a novel generative Bayesian probabilistic model for unsupervised matrix and tensor factorization. The model consists of several interacting LDA models, one for each modality. We describe an efficient collapsed Gibbs sampler for inference. We also derive the non-parametric form of the model where interacting LDA models are replaced with interacting HDP models. Experiments demonstrate that the model is useful for prediction of missing data with two or more modalities as well as learning the latent structure in the data.
HDB-Subdue: A Scalable Approach to Graph Mining
Authors: Srihari Padmanabhan, Sharma Chakravarthy
Venue: Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery (2009)

Transactional data mining (association rules, decision trees etc.) has been effectively used to find non-trivial patterns in categorical and unstructured data. For applications that have an inherent structure (e.g., social networks, proteins), graph mining is useful since mapping the structured data into a transactional representation will lead to loss of information. Graph mining is used for identifying interesting or frequent subgraphs. Database mining uses SQL and relational representation to overcome limitations of main memory algorithms and to achieve scalability.This paper presents a scalable, SQL-based approach to graph mining --- specifically, interesting substructure discovery. The most general form of graphs including directed edges, multiple edges between nodes, and cycles are handled by our approach. Our primary goal in this work has been to address scalability, and map difficult and computationally expensive problems such as pseudo duplicate elimination, canonical labeling, and isomorphism checking into SQL-based counterparts. The notion of minimum description length (MDL) has been cast into corresponding metric for relational representation. Our experimental analysis shows that graphs with Millions of nodes and edges can be handled by the algorithm and the approach presented in this paper.
Locally Distributed Predicates: A Programming Facility for Distributed State Detection
Authors: Michael Rosa
Venue: Proceedings of the 25th International Conference on Logic Programming (2009)

The rise of high-performance computing and internet-scale applications has spurred a renewed interest in distributed computing. Such distributed applications can range from multi-hop routing algorithms used in wireless mesh networks [1] to volunteer-driven parallel data analysis efforts [2][3]. The property of distributed systems that makes them both powerful and challenging is that they are composed of multiple autonomous, interconnected entities. Managing the interactions between these entities is the primary challenge of distributed application development. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Constraints in language processing: do grammars count?
Authors: Marieke van der Feen, Petra Hendriks, John Hoeks
Venue: Proceedings of the Third Workshop on Constraints and Language Processing (2006)

One of the central assumptions of Optimality Theory is the hypothesis of strict domination among constraints. A few studies have suggested that this hypothesis is too strong and should be abandoned in favor of a weaker cumulativity hypothesis. If this suggestion is correct, we should be able to find evidence for cumulativity in the comprehension of Gapping sentences, which lack explicit syntactic clues in the form of the presence of a finite verb. On the basis of a comparison between several computational models of constraint evaluation, we conclude that the comprehension of Gapping sentences does not yield compelling evidence against the strict domination hypothesis.
A generalized gelfond-lifschitz transformation for logic programs with abstract constraints
Authors: Yi-Dong Shen, Jia-Huai You
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

We present a generalized Gelfond-Lifschitz transformation in order to define stable models for a logic program with arbitrary abstract constraints on sets (c-atoms). The generalization is based on a formal semantics and a novel abstract representation of c-atoms, as opposed to the commonly used power set form representation. In many cases, the abstract representation of a c-atom results in a substantial reduction of size from its power set form representation. We show that any c-atom A = (Ad, Ac) in the body of a clause can be characterized using its satisfiable sets, so that given an interpretation I the c-atom can be handled simply by introducing a special atom θA together with a new clause θA ← A1, ..., An for each satisfiable set {A1, ..., An} of A. We also prove that the latest fixpoint approach presented by Son et al. and our approach using the generalized Gelfond-Lifschitz transformation are semantically equivalent in the sense that they define the same set of stable models.
Probabilistic Planning with Imperfect Sensing Actions Using Hybrid Probabilistic Logic Programs
Authors: Emad Saad
Venue: Proceedings of the 3rd International Conference on Scalable Uncertainty Management (2009)

Effective planning in uncertain environment is important to agents and multi-agents systems. In this paper, we introduce a new logic based approach to probabilistic contingent planning (probabilistic planning with imperfect sensing actions), by relating probabilistic contingent planning to normal hybrid probabilistic logic programs with probabilistic answer set semantics [24]. We show that any probabilistic contingent planning problem can be encoded as a normal hybrid probabilistic logic program. We formally prove the correctness of our approach. Moreover, we show that the complexity of finding a probabilistic contingent plan in our approach is NP-complete. In addition, we show that any probabilistic contingent planning problem, $\cal PP$, can be encoded as a classical normal logic program with answer set semantics, whose answer sets corresponds to valid trajectories in $\cal PP$. We show that probabilistic contingent planning problems can be encoded as SAT problems. We present a new high level probabilistic action description language that allows the representation of sensing actions with probabilistic outcomes.
Mobile educational game: adventure anywhere
Authors: Milovanović Miloš, Minović Miroslav, Lazović Miroslav, Starčević Dušan
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

Main topic of this work is development of educational games that can be used on mobile devices. Paper describes a novel approach to educational game defining and interpretation. Idea is based on extracting knowledge, game rules and scenarios outside the program thus enabling reusability. On the other hand by applying a layered approach to educational game interpretation we enable use of the same educational game on different devices and platforms. Purpose of this is to take learning outside classrooms and homes and provide a fun and interesting way of learning anytime, anywhere. Paper shows an example adventure game that is created following this methodology.
Trial of Formulating Affordance Features for Product Design
Authors: Tamotsu Murakami, Mariko Higuchi, Hideyoshi Yanagisawa
Venue: Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009 (2009)

The aim of this research is to formulate relationships between the geometrical attributes of objects and affordance for operations as affordance features. If affordance features are well formulated, then they will allow designers to strengthen intended affordances for higher usability of products or to systematically examine and achieve product or interface shapes with both high usability and aestheticity or novelty. In this paper we show some affordance features and their relationships with quantitative conditions obtained from an analysis of user tests involving sample objects of various shapes.
Bootstrapping distributional feature vector quality
Authors: Maayan Zhitomirsky-Geffet, Ido Dagan
Venue: Computational Linguistics (2009)

This article presents a novel bootstrapping approach for improving the quality of feature vector weighting in distributional word similarity. The method was motivated by attempts to utilize distributional similarity for identifying the concrete semantic relationship of lexical entailment. Our analysis revealed that a major reason for the rather loose semantic similarity obtained by distributional similarity methods is insufficient quality of the word feature vectors, caused by deficient feature weighting. This observation led to the definition of a bootstrapping scheme which yields improved feature weights, and hence higher quality feature vectors. The underlying idea of our approach is that features which are common to similar words are also most characteristic for their meanings, and thus should be promoted. This idea is realized via a bootstrapping step applied to an initial standard approximation of the similarity space. The superior performance of the bootstrapping method was assessed in two different experiments, one based on direct human gold-standard annotation and the other based on an automatically created disambiguation dataset. These results are further supported by applying a novel quantitative measurement of the quality of feature weighting functions. Improved feature weighting also allows massive feature reduction, which indicates that the most characteristic features for a word are indeed concentrated at the top ranks of its vector. Finally, experiments with three prominent similarity measures and two feature weighting functions showed that the bootstrapping scheme is robust and is independent of the original functions over which it is applied.
Combined GKLT Feature Tracking and Reconstruction for Next Best View Planning
Authors: Michael Trummer, Christoph Munkelt, Joachim Denzler
Venue: Proceedings of the 31st DAGM Symposium on Pattern Recognition (2009)

Guided Kanade-Lucas-Tomasi (GKLT) tracking is a suitable way to incorporate knowledge about camera parameters into the standard KLT tracking approach for feature tracking in rigid scenes. By this means, feature tracking can benefit from additional knowledge about camera parameters as given by a controlled environment within a next-best-view (NBV) planning approach for three-dimensional (3D) reconstruction. We extend the GKLT tracking procedure for controlled environments by establishing a method for combined 2D tracking and robust 3D reconstruction. Thus we explicitly use the knowledge about the current 3D estimation of the tracked point within the tracking process. We incorporate robust 3D estimation, initialization of lost features, and an efficient detection of tracking steps not fitting the 3D model. Our experimental evaluation on real data provides a comparison of our extended GKLT tracking method, the former GKLT, and standard KLT tracking. We perform 3D reconstruction from predefined image sequences as well as within an information-theoretic approach for NBV planning. The results show that the reconstruction error using our extended GKLT tracking method can be reduced up to 71% compared to standard KLT and up to 39% compared to the former GKLT tracker.
Operational Semantics Based on Frame of Extended Seal Calculus Language
Authors: Zhang Li-cui
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

An extended seal calculus language, ExtSealL, and its syntax is introduced in this paper. A frame structure is proposed for ExtSeal. A construction method for translating a seal definition into the frame definition is proposed and a transformation function is given based on the method. An operating semantics is developed basing on the frame structure, an example of a frame and its execution are given.
A Real Stock Market Simulation Based on Modified ASM
Authors: Haijun Yang, Xiaodi Zhu
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

This paper presented results from an experimental computer simulated stock market. Some modifications were done to SF-ASM for making agents more "real".Furthermore, agents were divided to different learning speeds, strategy-sizes, utility functions, in order to produce statistics of data more "real" according to Chinese market. The results really performed better than original model.
Microorganism-Plant Combined Bioremediation on Heavy Metal Contaminated Soil In the Industrial District
Authors: Zhou Guo Ying, Li Lin, Li He, He Yuanhao
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

Heavy metal contaminated soil problem has already become the global focus. With the increasing attention to the environment protection, scientist began to search new methods for remediation of contaminated soil. This paper mainly studied the effect of microorganism-plant combined bioremediation on contaminated soil in the industrial district, hoping to provide an effective bioremediation technique for heavy metal contaminated soil. In this research, 5 strains which were screened from rhizosphere resistance microorganism combined with Ligustrum quihoui Carr. were used for pot experiments, the results showed that 5 strains all had promotion effect on seedling growth in heavy metal contaminated soil, and high, root, and fresh weight were all higher than that of the control seedling groups. The microorganism-plant combined bioremediation system improved the plant remediation effect to heavy metal Zn, Cd, especially when 5 strains were coexisted and co-actived showed the obvious remediation effect. For Zn, its absorption coefficient was 0.51 and transmission coefficient was 1.55 and for Cd its absorption coefficient was 0.41 and its transmission coefficient was 0.48 when it was under the Zn, Cd combined pollution soil. So it has a good effect of microorganism-plant combined remediation.
Potential Limitations of Multi-touch Gesture Vocabulary: Differentiation, Adoption, Fatigue
Authors: Wendy Yee
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques (2009)

The majority of gestural interactions in consumer electronics currently represent "direct" gestures related to the direct manipulation of onscreen objects. As gestural interactions extend beyond consumer electronics and become more prevalent in productivity applications, these gestures will need to address more abstract or "indirect" actions. This paper addresses some of the usability concerns associated with indirect gestures and their potential limitations for the typical end-user. In addition, it outlines a number of considerations for the integration of abstract gestures with productivity workspaces.
Weight Balanced Linear Programming SVM on Skewed Distribution and its Evaluation
Authors: Yuxiang Mao, Daming Wei
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Support Vector Machines (SVM) have been shown to have strong classification capability and good generalization results. Among SVM's, linear-programming SVM's (LPSVM) have been shown to have better ability to adapt to large data sets with more efficiency. However, there have been several variations of LPSVM's, and their ability to tackle with skewed distributions are not investigated yet. In this research, we compared 4 LPSVM formulations and suggested one of them as the candidate for classifying skewed distributions. We also suggested a novel formula for evaluation of correctness of classification results, which is more suitable in multicategory cases. We also introduced a new concept of output balancing, which can be useful in recovering lost classes in k-SVM applications. Through the experiments, we showed that weight balancing approach is effective in multicategory classification.
Static analysis of active XML systems
Authors: Serge Abiteboul, Luc Segoufin, Victor Vianu
Venue: ACM Transactions on Database Systems (TODS) (2009)

Active XML is a high-level specification language tailored to data-intensive, distributed, dynamic Web services. Active XML is based on XML documents with embedded function calls. The state of a document evolves depending on the result of internal function calls (local computations) or external ones (interactions with users or other services). Function calls return documents that may be active, and so may activate new subtasks. The focus of this article is on the verification of temporal properties of runs of Active XML systems, specified in a tree-pattern-based temporal logic, Tree-LTL, which allows expressing a rich class of semantic properties of the application. The main results establish the boundary of decidability and the complexity of automatic verification of Tree-LTL properties.