ppxscal/embedding_network huggingface dataset:
Tempus Fugit
Authors: Uta Lösch, Sebastian Rudolph, Denny Vrandečić, Rudi Studer
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

Ontologies are used to formally describe domains of interest. As domains change over time, the ontologies have to be updated accordingly. We advocate the introduction of an Ontology Update Language that captures frequent domain changes and hence facilitates regular updates to be made in ontologies. We thoroughly discuss the general design choices for defining such a language and a corresponding update framework. Moreover, we propose a concrete language proposal based on SPARQL Update and provide a reference implementation of the framework.
BIOSMILE: adapting semantic role labeling for biomedical verbs: an exponential model coupled with automatically generated template features
Authors: Richard Tzong-Han Tsai, Wen-Chi Chou, Yu-Chun Lin, Cheng-Lung Sung, Wei Ku, Ying-Shan Su, Ting-Yi Sung, Wen-Lian Hsu
Venue: Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis (2006)

In this paper, we construct a biomedical semantic role labeling (SRL) system that can be used to facilitate relation extraction. First, we construct a proposition bank on top of the popular biomedical GENIA treebank following the PropBank annotation scheme. We only annotate the predicate-argument structures (PAS's) of thirty frequently used biomedical predicates and their corresponding arguments. Second, we use our proposition bank to train a biomedical SRL system, which uses a maximum entropy (ME) model. Thirdly, we automatically generate argument-type templates which can be used to improve classification of biomedical argument types. Our experimental results show that a newswire SRL system that achieves an F-score of 86.29% in the newswire domain can maintain an F-score of 64.64% when ported to the biomedical domain. By using our annotated biomedical corpus, we can increase that F-score by 22.9%. Adding automatically generated template features further increases overall F-score by 0.47% and adjunct arguments (AM) F-score by 1.57%, respectively.
Evaluation of knowledge bases by means of multi-dimensional OWA operators
Authors: Isabel Aguiló, Javier Martín, Gaspar Mayor, Jaume Suòer
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

In this paper we present the evaluation of the quality of knowledge bases by means of multi-dimensional aggregation operators. The knowledge bases to be evaluated are rule bases of the type antecedent-consequent, where we assign to each base a list of the relevance factors corresponding to the rules. This relevance factor is obtained by measuring certain considered qualitative or quantitative characteristics. The quality coefficient of the base is then obtained by aggregation of the list of relevance factors. Since each knowledge base has a different number of rules, these lists of relevance factors have different lengths. Thus, the use of multi-dimensional aggregation functions to obtain the quality coefficient allows us to compare the rule bases. The analysis of the properties that the aggregation function should satisfy leads to the use of multi-dimensional OWA operators.
Preserving User Preferences in Automated Document-Category Management: An Evolution-Based Approach
Authors: Chih-Ping Wei, Paul Hu, Yen-Hsien Lee
Venue: Journal of Management Information Systems (2009)

Analysis of prevalent document management practices shows the popular use of categories (e.g., folders) to organize documents for subsequent searches and retrievals. The coherence and distinction of an existing document category can diminish considerably as influxes of new documents arrive over time. The complexity of and effort requirements for document-category management favor an automated approach that can be supported by appropriate document-clustering techniques. A review of the extant literature shows a predominant focus on document content analysis in automated document-category management, which cannot preserve the user's document-grouping preferences. This research develops two advanced evolution-based techniques for preserving user preferences in their management of document categories. The first technique (CE2), which supports the automated evolution of a set of flat (i.e., nonhierarchical) document categories, extends a promising evolution-based technique (category evolution, CE) by addressing its fundamental limitations inherent to the use of holistic measures. The second technique, category hierarchy evolution (CHE), is developed on the basis of CE2 to support scenarios where document categories are organized with a hierarchical structure. Empirical evaluations of the effectiveness of each technique in various category evolution scenarios created using two different document corpora (i.e., news documents from Reuters and research articles from the ACM digital library), as compared with those of associated salient techniques for benchmark purposes, show that CE2 and CHE outperform their respective benchmark techniques. Their performance is reasonably robust and appears more effective when the quality (coherence) of the previously created categories does not deteriorate excessively. According to our results, the evolution-based approach is viable, appealing, and capable of preserving user preferences in automatic reorganizations of document categories.
Fault-tolerant aggregator election and data aggregation in wireless sensor networks
Authors: Mikel Larrea, Cristian Martin, Jose Javier Astrain
Venue: International Journal of Communication Networks and Distributed Systems (2009)

This paper presents three algorithms for aggregator election and data aggregation in wireless sensor networks where sensors can crash and recover. The network is divided in several regions. The algorithms ensure the election of a common data aggregator sensor within each region, in charge of the collection of local data and the election of a unique super-aggregator sensor, in charge of the collection of global data, among all the aggregators. Both elections are achieved by implementing the Omega failure detector, which provides a self-organising and fault-tolerant leader election service. Each algorithm is based on a different connectivity assumption. The first algorithm assumes that every pair of sensors in a region can communicate directly. The second algorithm only requires some correct sensor to communicate directly with the rest of sensors. Finally, the third algorithm only requires the existence of a multi-hop bidirectional path from some correct sensor to the rest of sensors. We also introduce a battery depletion threshold to enhance the quality of service of the wireless sensor network.
Approximate topological matching of quad meshes
Authors: David Eppstein, Michael T. Goodrich, Ethan Kim, Rasmus Tamstorf
Venue: The Visual Computer: International Journal of Computer Graphics (2009)

In this paper, we study the problem of approximate topological matching for quadrilateral meshes, that is, the problem of finding as large a set as possible of matching portions of two quadrilateral meshes. This study is motivated by applications in graphics that involve the modeling of different shapes that have results needing to be merged in order to produce a final unified representation of an object. We show that the problem of producing a maximum approximate topological match of two quad meshes is NP-hard and that its decision version is NP-complete. Given these results, which make an exact solution extremely unlikely, we show that the natural greedy algorithm derived from polynomial-time graph isomorphism can produce poor results, even when it is possible to find matches with only a few nonmatching quads. Nevertheless, we provide a &#x201c;lazy-greedy&#x201d; algorithm that is guaranteed to find good matches when mismatching portions of mesh are localized. Finally, we provide empirical evidence that this approach produces good matches between similar quad meshes.
Environmental robustness in multi-agent teams
Authors: Terence Soule, Robert B. Heckendorn
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

Evolution has proven to be an effective method of training heterogeneous multi-agent teams of autonomous agents to explore unknown environments. Autonomous, heterogeneous agents are able to go places where humans are unable to go and perform tasks that would be otherwise dangerous or impossible to complete. However, a serious problem for practical applications of multi-agent teams is how to move from training environments to real-world environments. In particular, if the training environment cannot be made identical to the real-world environment how much will performance suffer? In this research we investigate how differences in training and testing environments affect performance. We find that while in general performance degrades from training to testing, for difficult training environments performance improves in the test environment. Further, we find distinct differences between the performance of different training algorithms with Orthogonal Evolution of Teams (OET) producing the best overall performance.
A novel Middleware for the Mobility Management Over the Internet
Authors: Lei Zhang, Patrick Senac, Emmanuel Lochin, Michel Diaz
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

The features of mobility, which enormously impact on how communication is evolving into the future, represent a particular challenge in today’s wireless networking research. After an identification and evaluation of the gap between the discontinuities of the communication service inherent to the physical layer of mobile networks and the continuity requirements issue from the stream centric multimedia applications, we propose a novel middleware 3MOI (Middleware for the Mobility Management Over the Internet) which can support efficient and context-aware mobility management and satisfy new mobility requirements such as dynamical location management, fast handover, and continuous connection support.
Automatic part-of-speech tagging for Bengali: an approach for morphologically rich languages in a poor resource scenario
Authors: Sandipan Dandapat, Sudeshna Sarkar, Anupam Basu
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

This paper describes our work on building Part-of-Speech (POS) tagger for Bengali. We have use Hidden Markov Model (HMM) and Maximum Entropy (ME) based stochastic taggers. Bengali is a morphologically rich language and our taggers make use of morphological and contextual information of the words. Since only a small labeled training set is available (45,000 words), simple stochastic approach does not yield very good results. In this work, we have studied the effect of using a morphological analyzer to improve the performance of the tagger. We find that the use of morphology helps improve the accuracy of the tagger especially when less amount of tagged corpora are available.
Finding shortest paths on real road networks: the case for A*
Authors: W. Zeng, R. L. Church
Venue: International Journal of Geographical Information Science (2009)

The problem of identifying the shortest path along a road network is a fundamental problem in network analysis, ranging from route guidance in a navigation system to solving spatial allocation problems. Since this type of problem is solved so frequently, it is important to craft an approach that is as efficient as possible. Based upon past research, it is generally accepted that several efficient implementations of the Dijkstra algorithm are the fastest at optimally solving the 'one-to-one' shortest path problem (Cherkassky et al. 1996). We show that the most efficient state-of-the-art implementations of Dijkstra can be improved by taking advantage of network properties associated with GIS-sourced data. The results of this paper, derived from tests of different algorithmic approaches on real road networks, will be extremely valuable for application developers and researchers in the GIS community.
Quantitative Aspects of Speed-Up and Gap Phenomena
Authors: Klaus Ambos-Spies, Thorsten Kräling
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

We show that, for any abstract complexity measure in the sense of Blum and for any computable function f (or computable operator F), the class of problems which are f-speedable (or F-speedable) does not have effective measure 0. On the other hand, for sufficiently fast growing f (or F), the class of the nonspeedable problems does not have effective measure 0 too. These results answer some questions raised by Calude and Zimand in [CZ96] and [Zim06]. We also give a short quantitative analysis of Borodin and Trakhtenbrot's Gap Theorem which corrects a claim in [CZ96] and [Zim06].
A Symbolic Semantics for a Calculus for Service-Oriented Computing
Authors: Rosario Pugliese, Francesco Tiezzi, Nobuko Yoshida
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

We introduce a symbolic characterisation of the operational semantics of COWS, a formal language for specifying and combining service-oriented applications, while modelling their dynamic behaviour. This alternative semantics avoids infinite representations of COWS terms due to the value-passing nature of communication in COWS and is more amenable for automatic manipulation by analytical tools, such as e.g. equivalence and model checkers. We illustrate our approach through a 'translation service' scenario.
Image Effects and Rational Inattention in Internet-Based Selling
Authors: Dongwon Lee, Robert Kauffman
Venue: International Journal of Electronic Commerce (2009)

The frequency of occurrence of certain price points in Internet-based selling is investigated in order to determine what drives the observed regularities and variations. Theories based on consumer perceptions of price and quality images, and on rational inattention to price-endings are explored by specifying and testing empirical models for price-endings using more than 1.5 million daily observations on multiple product categories sold by 90 Internet-based retailers collected over a two-year period. The results show that a firm's on-line reputation and relative price levels affect the price-endings chosen in different product categories, and that 9-ending prices increase consumer purchases. These findings support an image theory of store quality and price. The use of 9-ending prices varies across Internet selling formats in a way consistent with differences in the rational attentiveness these channels engender in consumers. This research on the role of information technology in price-setting provides insights for marketers who wish to optimize price-setting decisions in the competitive environment of Internet retailing.
Fuzzy Neural Network with a Fuzzy Learning Rule Emphasizing Data Near Decision Boundary
Authors: Yong Soo Kim
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

A fuzzy LVQ (Learning Vector Quantization), which is based on the fuzzification of LVQ, is proposed. This new fuzzy LVQ puts more emphasis on the input vector near decision boundary than on the input vector far from decision boundary. It prevents the outlier from deteriorating the decision boundary. The proposed fuzzy LVQ is used in the neural network, which has the control structure similar to that of ART(Adaptive Resonance Theory)-1 neural network. The result shows that Supervised IAFC (Integrated Adaptive Fuzzy Clustering) Neural Network 6 yielded fewer misclassifications than LVQ algorithm and backpropagation neural network.
Improving Creativity for Mathematical Problem Solving Using Web-based Multimedia Whiteboard System
Authors: Wu-Yuin Hwang, Nian-Shing Chen, Jian-Jie Dung, Yi-Lun Yang
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

The aim of this study is to explore the relationship between representation and creativity, and their influence on mathematical problem solving. As mathematical problem solving needs complex cognitive abilities and representation translations, there is a question that whether using a multimedia whiteboard system can better facilitate students to learn this type of mathematical problem solving. The result has found that students can perform well in mathematical problem solving if they can better utilize the tools supported by a multimedia whiteboard system to do multiple representations for their solutions. Our creativity analysis also found that students who can do multiple representations well for their solutions and criticisms would have higher elaboration ability in the creativity test. The finding concludes that multiple representation skills are strongly related to student's elaboration ability and are the key to mathematical problem solving.
Exploration of term dependence in sentence retrieval
Authors: Keke Cai, Jiajun Bu, Chun Chen, Kangmiao Liu
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

This paper focuses on the exploration of term dependence in the application of sentence retrieval. The adjacent terms appearing in query are assumed to be related with each other. These assumed dependences among query terms will be further validated for each sentence and sentences, which present strong syntactic relationship among query terms, are considered more relevant. Experimental results have fully demonstrated the promising of the proposed models in improving sentence retrieval effectiveness.
Computational study of beta-cyclodextrin-water system
Authors: Silvia Patachia, Catalin Croitoru
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

Beta-cyclodextrin is a cyclic oligosaccharide with large applications in medicine, pharmacy and food industry, due to its unique architecture which enables the formation of supramolecular aggregates with small molecular compounds. In this work, some aspects regarding the behavior of beta-cyclodextrin molecules in water at different concentrations have been simulated with specialized software and correlated with existent experimental data, in order to understand better the complexity of the BCD-water system and to define future applications.
Fusion Algorithm Based on the Intuitionistic Fuzzy Set and Multiple Neural Network
Authors: Jun Zhi, Jianyong Liu, Wei Xu, Limin Zhi
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

The paper proposes an algorithm based on the intuitionistic fuzzy set theory to fuse a lot of different neural network. Apply it to the comprehensive assessment of the target destruction effect in the battle field, confirm the weights of different neural networks, and synthesize their assessment results as the final outputting result according to the weight. Apply the algorithm to instance simulation, the result shows its validity and rationality.
Arguments, Values and Baseballs: Representation of Popov v. Hayashi
Authors: Adam Wyner, Trevor Bench-Capon, Katie Atkinson
Venue: Proceeding of the 2007 conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference (2007)

In this paper, we model a recent legal case as presented in a court of first instance using argument schemes and an argumentation framework, providing a formal analysis of the case and how the outcome was determined. The paper contributes to the body of literature that formally analyses legal cases in terms of arguments and argument schemes. It is novel in that we analyse a case in a court of first instance, so we have arguments about facts, qualifications of intermediate predicates, and the application of legal rules. We show the importance of undercutters in relating principles to the specific case.
The dynamics of personal territories on the web
Authors: Thomas Beauvisage
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

In this paper, we present a long-term study of user-centric Web traffic data collected in 2000-2002 and 2005-2006 from two large representative panels of French Internet users. Our work focuses on the dynamics of personal territories on the Web and their evolution between 2000 and 2006. At the session level, we distinguish four profiles of browsing dynamics in 2005-2006, and point out the growing dichotomy between straight routine sessions and exploratory browsing. At a global level, we observe that although each individual's corpus of visited sites is permanently growing, his browsing practices are structured around routine well-known sites which operate as links providers to new sites. We argue that this tension between the known and the unknown is constitutive of Web practices and is a fundamental property of personal Web territories.
An accelerated gradient method for trace norm minimization
Authors: Shuiwang Ji, Jieping Ye
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We consider the minimization of a smooth loss function regularized by the trace norm of the matrix variable. Such formulation finds applications in many machine learning tasks including multi-task learning, matrix classification, and matrix completion. The standard semidefinite programming formulation for this problem is computationally expensive. In addition, due to the non-smooth nature of the trace norm, the optimal first-order black-box method for solving such class of problems converges as O(1/&radic;k), where k is the iteration counter. In this paper, we exploit the special structure of the trace norm, based on which we propose an extended gradient algorithm that converges as O(1/k). We further propose an accelerated gradient algorithm, which achieves the optimal convergence rate of O(1/k2) for smooth problems. Experiments on multi-task learning problems demonstrate the efficiency of the proposed algorithms.
Order statistics from dependent, completely monotone distributions
Authors: Mark Brown
Venue: Probability in the Engineering and Informational Sciences (2009)

We consider order statistics corresponding to X1, …, Xn, where <inline-graphic mime-subtype="gif" xlink="S0269964809000278_inline1"><alt-text>$X_{i} \sim \lambda_{i}^{-1} \cal{E}$</alt-text></inline-graphic>, i = 1, …, n, ℰ1, …, ℰn are independent and identically distributed exponentials with mean 1, and λ1, …, λn are possibly dependent, possibly nonidentically distributed, positive random variables, with <inline-graphic mime-subtype="gif" xlink="S0269964809000278_inline2"><alt-text>$E\lambda_{i}^{-1} 1, …, λn, can be interpreted as random failure rates, and their dependency might be due to common environmental factors.
MediaJourney: capturing and sharing digital media from real-world and virtual journeys
Authors: Kaspar Rosengreen Nielsen, Rasmus Gude, Marianne Graves Petersen, Kaj Grønbæk
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

In this poster, we discuss a novel MediaJourney concept and infrastructure with integrated applications for capturing, annotating, and automatically tagging captured media objects during physical journeys as well as virtual journeys on the web or in media collections. The main objective of MediaJourney is to radically reduce overhead in collecting and organizing captured digital media for planned or ad-hoc sharing with family and friends, e.g. in a home setting. This is supported with a mix of automatic tagging and manual selection or keyword tagging of journeys at the time of capture. The idea is to provide automatic and simple mechanisms for structuring while capturing.