ppxscal/embedding_network huggingface dataset:
Notational effects on use of collaboratively constructed representations during individual essay writing
Authors: Ravi Vatrapu, Daniel Suthers, Richard Medina
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

Prior analyses of collaboration through different notational systems (e.g., threaded discussions and evidence maps) have documented differential influences of notations on collaborative processes as well as ways in which groups appropriate these notations for their work. These prior analyses have focused on collaborative interaction, yet for instrumental purposes in educational practice, the individual is the unit of analysis. Hence it is relevant to ask how individuals use the products of collaborative interaction as documented in a given notational system. This paper reports on an analysis of data from a prior study to uncover how participants went about writing individual essays, drawing on the products of interactionally prior joint problem solving. The analysis first documented parameters of the human-computer interactions through which individual participants accessed and appropriated the record of prior work. Parameters included focus shifts, use of copy/paste, and access to records of data and hypotheses considered. The analysis then compared three experimental conditions and two post-hoc groups on the selected parameters. Profiles plots reveal consistent differences between the use of the notational systems that are indicative of differences in engagement with the materials.
H-DPOP: using hard constraints for search space pruning in DCOP
Authors: Akshat Kumar, Adrian Petcu, Boi Faltings
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

In distributed constraint optimization problems, dynamic programming methods have been recently proposed (e.g. DPOP). In dynamic programming many valuations are grouped together in fewer messages, which produce much less networking overhead than search. Nevertheless, these messages are exponential in size. The basic DPOP always communicates all possible assignments, even when some of them may be inconsistent due to hard constraints. Many real problems contain hard constraints that significantly reduce the space of feasible assignments. This paper introduces H-DPOP, a hybrid algorithm that is based on DPOP, which uses Constraint Decision Diagrams (CDD) to rule out infeasible assignments, and thus compactly represent UTIL messages. Experimental results show that H-DPOP requires several orders of magnitude less memory than DPOP, especially for dense and tightly-constrained problems.
Possibilistic Similarity Estimation and Visualization
Authors: Anas Dahabiah, John Puentes, Basel Solaiman
Venue: Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory (2009)

In this paper, we present a very general and powerful approach to represent and to visualize the similarity between the objects that contain heterogeneous, imperfect and missing attributes in order to easily achieve efficient analysis and retrieval of information by organizing and gathering these objects into meaningful groups. Our method is essentially based on possibility theory to estimate the similarity and on the spatial, the graphical, and the clustering-based representational models to visualize and represent its structure. Our approach will be applied to a real digestive image database (http://i3se009d.univ-brest.fr/ password view2006 [4]). Without any a priori medical knowledge concerning the key attributes of the pathologies, and without any complicated preprocessing of the imperfect data, results show that we are capable to visualize and to organize the different categories of the digestive pathologies. These results were validated by the doctor.
Agent-Enriched Data Mining Using an Extendable Framework
Authors: Kamal Ali Albashiri, Frans Coenen
Venue: Agents and Data Mining Interaction: 4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15,2009, Revised Selected Papers (2009)

This paper commences with a discussion of the advantages that Multi-Agent Systems (MAS) can bring to the domain of Knowledge Discovery in Data (KDD), and presents a rational for Agent-Enriched Data Mining (AEDM). A particular challenge of any generic, general purpose, AEDM system is the extensive scope of KDD. To address this challenge the authors suggest that any truly generic AEDM must be readily extendable and propose EMADS, The Extendable Multi-Agent Data mining System. A complete overview of the architecture and agent interaction models of EMADS is presented. The system's operation is described and illustrated in terms of two KDD scenarios: meta association rule mining and classifier generation. In conclusion the authors suggest that EMADS provides a sound foundation for both KDD research and application based AEDM.
The role of academic motivation in Computer-Supported Collaborative Learning
Authors: Bart Rienties, Dirk Tempelaar, Piet Van den Bossche, Wim Gijselaers, Mien Segers
Venue: Computers in Human Behavior (2009)

In recent years, increasing attention has been devoted to virtual learning. In the last decade, a large number of studies in Computer-Supported Collaborative Learning (CSCL) have assessed how social interaction, learning processes and outcomes in virtual settings are intertwined. Although recent research findings indicate that learners differ with respect to the amount and type of discourse contributed in virtual settings, little is known about the causes of these differences. The research presented here looks into the effects of motivation of learners on their contribution to discourse using the Deci and Ryan framework of (intrinsic/extrinsic) motivation. This study of 100 participants who were randomly distributed in six groups of 14 members collaborated in a virtual setting to remediate deficiencies in economics indicates that individuals differed with respect to the amount of discourse activity. Furthermore, an integrated multi-method approach (Content Analysis, Social Network Analysis and Academic Motivation Scale) was used in order to examine the impact of academic motivation on the type of discourse activity contributed and on the position of the learner in the social network. The results indicate that highly intrinsically motivated learners become central and prominent contributors to cognitive discourse. In contrast, extrinsically motivated learners contribute on average and are positioned throughout the social network. The research results reveal that differences in academic motivation influences the type of contributions to discourse as well as the position a learner takes within the social network.
Multi-speaker language modeling
Authors: Gang Ji, Jeff Bilmes
Venue: Proceedings of HLT-NAACL 2004: Short Papers on XX (2004)

In conventional language modeling, the words from only one speaker at a time are represented, even for conversational tasks such as meetings and telephone calls. In a conversational or meeting setting, however, speakers can have significant influence on each other. To recover such un-modeled inter-speaker information, we introduce an approach for conversational language modeling that considers words from other speakers when predicting words from the current one. By augmenting a normal trigram context, our new multi-speaker language model (MSLM) improves on both Switchboard and ICSI Meeting Recorder corpora. Using an MSLM and a conditional mutual information based word clustering algorithm, we achieve a 8.9% perplexity reduction on Switchboard and a 12.2% reduction on the ICSI Meeting Recorder data.
Parallel Volume Image Segmentation with Watershed Transformation
Authors: Björn Wagner, Andreas Dinges, Paul Müller, Gundolf Haase
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

We present a novel approach to parallel image segmentation of volume images on shared memory computer systems with watershed transformation by immersion. We use the domain decomposition method to break the sequential algorithm in multiple threads for parallel computation. The use of a chromatic ordering allows us to gain a correct segmentation without an examination of adjacent domains or a final relabeling. We will briefly discuss our approach and display results and speedup measurements of our implementation.
An Active Approach to Automatic Case Generation
Authors: Michael W. Floyd, Babak Esfandiari
Venue: Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2009)

When learning by observing an expert, cases can be automatically generated in an inexpensive manner. However, since this is a passive method of learning the observer has no control over which problems are solved and this can result in case bases that do not contain a representative distribution of the problem space. In order to overcome this we present a method to incorporate active learning with learning by observation. Problems that are not covered by the current case base are automatically detected, during runtime or by examining secondary case bases, and presented to an expert to be solved. However, we show that these problems can not be presented to the expert individually but need to be part of a sequence of problems. Creating this sequence of cases is non-trivial, and an approach to creating such sequences is described. Experimental results, in the domain of simulated soccer, show our approach to be useful not only for increasing the problem coverage of the case base but also in creating cases with rare solutions.
On Mining and Social Role Discovery in Internet Forums
Authors: Mikolaj Morzy
Venue: Proceedings of the 2009 International Workshop on Social Informatics (2009)

Internet forums have recently become the leading form of peer communication in the Internet. An Internet forum is a Web application for publishing user-generated content under the form of a discussion. Discussions considering particular subjects are called topics or threads. Internet forums are sometimes called Web forums, discussion boards, message boards, discussion groups, or bulletin boards. The most important feature of Internet forums is their social aspect. Many forums are active for a long period of time and attract a group of dedicated users, who build a tight social community around a forum. With great abundance of forums devoted to every possible aspect of human activity, such as politics, religion, sports, technology, entertainment, economy, fashion, and many more, users are able to find a forum that perfectly suits their needs and interests. In this paper we present a data mining model for social role discovery and attribution in Internet forum data.
Productive Love: A New Proposal for Designing Affective Technology
Authors: Ramon Solves Pujol, Hiroyuki Umemuro
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

Love highly present in peoples talks and all cultural spheres, its importance suggests the need to understand what role technology plays in relation to it and the roles it could play in the future. We review studies related to love in HCI and we identify a lack of consideration of philosophy as a background for love understanding. Based on literature review, we offer a proposal of guidelines for designing technology that aims to improve loving relationships. Besides, we examine principles of engagement with technology that may be important when designing love-promoting technology. Finally we present a Productive Love promoting system, which evaluation indicated that the participant found it useful to improve their Productive Love.
Dynamic Load Balancing Strategies for Hierarchical p-FEM Solvers
Authors: Ralf-Peter Mundani, Alexander Düster, Jovana Knežević, Andreas Niggl, Ernst Rank
Venue: Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2009)

Equation systems resulting from a p-version FEM discretisation typically require a special treatment as iterative solvers are not very efficient here. Applying hierarchical concepts based on a nested dissection approach allow for both the design of sophisticated solvers as well as for advanced parallelisation strategies. To fully exploit the underlying computing power of parallel systems, dynamic load balancing strategies become an essential component.
An Agile MDA Approach for Service-Oriented Components
Authors: Simona Motogna, I. Lazăr, B. Pârv, I. Czibula
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Two important principles that drive the agile MDA processes are immediate execution and test first development. This paper presents a component model, called iComponent, that allows the development of executable models based on agile principles and service orientation. In order to ensure simple and fast definition of component operations, we use a concrete syntax for UML structured activities and a corresponding UML profile. The study also includes a mapping of iComponent to some existing service-oriented component frameworks (iPOJO, OSGi, SCA). The proposed platform-independent component model is part of a framework for component definition, validation and composition.
Virtual-coordinate-based delivery-guaranteed routing protocol in wireless sensor networks
Authors: Ming-Jer Tsai, Hong-Yen Yang, Bing-Hong Liu, Wen-Qian Huang
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

In this paper, we first propose a method, ABVCap, to construct a virtual coordinate system in a wireless sensor network. ABVCap assigns each node multiple 5-tuple virtual coordinates. Subsequently, we introduce a protocol, ABVCap routing, to route packets based on the ABVCap virtual coordinate system. ABVCap routing guarantees packet delivery without the computation and storage of the global topological features. Finally, we demonstrate an approach, ABVCap maintenance, to reconstruct an ABVCap virtual coordinate system in a network with node failures. Simulations show ABVCap routing ensures moderate routing path length, as compared to virtual-coordinate-based routing, GLIDER, Hop ID, GLDR, and VCap.
Possibilistic risk aversion
Authors: Irina Georgescu
Venue: Fuzzy Sets and Systems (2009)

Risk theory is usually developed within probability theory. The aim of this paper is to propose an approach of the risk aversion by possibility theory, initiated by Zadeh in 1978. The main notion studied in this paper is the possibilistic risk premium associated with a fuzzy number A and a utility function u. Under the hypothesis that the utility function u verifies certain hypotheses, one proves a formula to evaluate the possibilistic risk premium in terms of u and of some possibilistic indicators.
Meteorological Drought Forecasting Using Markov Chain Model
Authors: Xiaofan Liu, Liliang Ren, Fei Yuan, Bang Yang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

The objective of this study is to introduce an early warning system to forecast drought using palmer drought severity index (PDSI) and Markov chain model. Based on DEM, time series of monthly PDSI of all pixels within the Laohahe Catchment from 1960 to 2005 were calculated. It is found that continuity of drought in the study area was very strong, durations of which were almost more than 2 years. There is an increasing tendency in the frequency of drought occurring in the Laohahe Catchment, which may be the result of temperature increase. Based on PDSI, the drought states of 12 months in 2000 year were forecasted using Markov chain model with different steps. The results show that Markov chain model has some capability of forecasting drought, especially for the states of normal and slight drought. The prediction performance of Markov chain model is related with the forecasting steps, little steps always getting good performance. As a result, the Markov chain model is able to work for the early warning.
Synchronization Schedule and Date Sharing of Activity Multi-Instance Based on Workflow
Authors: Liu Lin-lan, Ma Min, Shu Jian, Yang Fengyu, Zhong Wei
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Multi-instance activity can express the scenario, in which many people conduct the same task. Supporting multiple instances of one activity can enable workflow management system to be flexible on handling workflow process. But some problems emerge, such as synchronizing schedule of multi-instance and conflict of data share. The paper proposes a scheme of “Group-Categorization”, which solves the synchronization among multi-instance in one activity, when workflow is executed. It starts activity multi-instance with groups, which is synchronized by categorization in one group, so that there is no need to extend the standard workflow model. Furthermore, it has the capability of workflow language expression. Pointer strategy solves the conflict, when activity multi-instance access same data. According to the unique of process instances AID, it can share read-only data and can copy writing data without extra data attributes. It is available for standard workflow model.
A* search via approximate factoring
Authors: Aria Haghighi, John DeNero, Dan Klein
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

We present a novel method for creating A* estimates for structured search problems originally described in Haghighi, DeNero, & Klein (2007). In our approach, we project a complex model onto multiple simpler models for which exact inference is efficient. We use an optimization framework to estimate parameters for these projections in a way which bounds the true costs. Similar to Klein & Manning (2003), we then combine completion estimates from the simpler models to guide search in the original complex model. We apply our approach to bitext parsing and demonstrate its effectiveness.
Robotic Mapping and Exploration, 1st edition
Authors: Cyrill Stachniss
Venue: Springer Tracts In Advanced Robotics (2009)

"Robotic Mapping and Exploration" is an important contribution in the area of simultaneous localization and mapping (SLAM) for autonomous robots, which has been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the autonomous mapping learning problem. Solutions include uncertainty-driven exploration, active loop closing, coordination of multiple robots, learning and incorporating background knowledge, and dealing with dynamic environments. Results are accompanied by a rich set of experiments, revealing a promising outlook toward the application to a wide range of mobile robots and field settings, such as search and rescue, transportation tasks, or automated vacuum cleaning.
Instantiation-Based Automated Reasoning: From Theory to Practice
Authors: Konstantin Korovin
Venue: Proceedings of the 22nd International Conference on Automated Deduction (2009)

Instantiation-based automated reasoning aims at combining the efficiency of propositional SAT and SMT technologies with the expressiveness of first-order logic. Propositional SAT and SMT solvers are probably the most successful reasoners applied to real-world problems, due to extremely efficient propositional methods and optimized implementations. However, the expressiveness of first-order logic is essential in many applications ranging from formal verification of software and hardware to knowledge representation and querying. Therefore, there is a growing demand to integrate efficient propositional and more generally ground reasoning modulo theories into first-order reasoning.
Formal Verification of the Implementability of Timing Requirements
Authors: Xiayong Hu, Mark Lawford, Alan Wassyng
Venue: Formal Methods for Industrial Critical Systems: 13th International Workshop, FMICS 2008, L'Aquila, Italy, September 15-16, 2008, Revised Selected Papers (2009)

There has been relatively little work on the implementability of timing requirements. We have previously provided definitions of fundamental timing operators that explicitly considered tolerances on property durations and intersample jitter. In this work we identify three environmental assumptions and compare the implementability of a Held_For operator in each of them, formalizing this analysis in PVS. We show how to design a software component that implements the Held_For operator and then verify it in PVS. This pre-verified component is then used to guide the design of more complex components and to decompose their design verification into simple inductive proofs as demonstrated through the implementation of a timing requirement for an example application.
Adaptive User Interfaces for the Clothing Retail
Authors: Karim Khakzar, Jonas George, Rainer Blum
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

This paper presents the results of a research project that identifies the most important concepts for adaptive user interfaces in the context of e-commerce, such as online shops, and evaluates these concepts using a formalized method and standardized criteria. As a result, recommendations for the design of adaptive user interfaces are derived.
Wireless LAN load balancing with genetic algorithms
Authors: Ted Scully, Kenneth N. Brown
Venue: Knowledge-Based Systems (2009)

In recent years IEEE 802.11 wireless local area networks (WLANs) have become increasingly popular. Consequently, there has also been a surge in the number of end-users. The IEEE 802.11 standards do not provide any mechanism for load distribution and as a result user quality of service (QoS) degrades significantly in congested networks where large numbers of users tend to congregate in the same area. The objective of this paper is to provide load balancing techniques that optimise network throughput in areas of user congestion, thereby improving user QoS. Specifically, we develop micro-genetic and standard genetic algorithm approaches for the WLAN load balancing problem, and we analyse their strengths and weaknesses. We also compare the performance of these algorithms with schemes currently in use in IEEE 802.11 WLANs. The results demonstrate that the proposed genetic algorithms give a significant improvement in performance over current techniques. We also show that this improvement is achieved without penalising any class of user.
Space Efficient Multi-dimensional Range Reporting
Authors: Marek Karpinski, Yakov Nekrich
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

We present a data structure that supports three-dimensional range reporting queries in O(loglogU + (loglogn)3 + k) time and uses O(nlog1 + ¿ n) space, where U is the size of the universe, k is the number of points in the answer, and ¿ is an arbitrary constant. This result improves over the data structure of Alstrup, Brodal, and Rauhe (FOCS 2000) that uses O(nlog1 + ¿ n) space and supports queries in O(logn + k) time, the data structure of Nekrich (SoCG'07) that uses O(nlog3 n) space and supports queries in O(loglogU + (loglogn)2 + k) time, and the data structure of Afshani (ESA'08) that uses O(nlog3 n) space and also supports queries in O(loglogU + (loglogn)2 + k) time but relies on randomization during the preprocessing stage. Our result allows us to significantly reduce the space usage of the fastest previously known static and incremental d-dimensional data structures, d ¿ 3, at a cost of increasing the query time by a negligible O(loglogn) factor.