ppxscal/embedding_network huggingface dataset:
Automatic prediction of misconceptions in multilingual computer-mediated communication
Authors: Naomi Yamashita, Toru Ishida
Venue: Proceedings of the 11th international conference on Intelligent user interfaces (2006)

Multilingual communities using machine translation to overcome language barriers are showing up with increasing frequency. However, when a large number of translation errors get mixed into conversations, users have difficulty completely understanding each other. In this paper, we focus on misconceptions found in high volume in actual online conversations using machine translation. We first examine the response patterns in machine translation-mediated communication and associate them with misconceptions. Analysis results indicate that response messages to include misconceptions posted via machine translation tend to be incoherent, often focusing on short phrases of the original message. Next, based on the analysis results, we propose a method that automatically predicts the occurrence of misconceptions in each dialogue. The proposed method assesses the tendency of each dialogue including misconceptions by calculating the gaps between the regular discussion thread (syntactic thread) and the discussion thread based on lexical cohesion (semantic thread). Verification results show significant positive correlation between actual misconception frequency and gaps between syntactic and semantic threads, which indicate the validity of the method.
Using Occurrence Properties of Defect Report Data to Improve Requirements
Authors: Kimberly S. Wasson, Kendra N. Schmid, Robyn R. Lutz, John C. Knight
Venue: Proceedings of the 13th IEEE International Conference on Requirements Engineering (2005)

Defect reports generated for faults found during testing provide a rich source of information regarding problematic phrases used in requirements documents. These reports indicate that faults often derive from instances of ambiguous, incorrect or otherwise deficient language. In this paper, we report on a method combining elements of linguistic theory and information retrieval to guide the discovery of problematic phrases throughout a requirements specification, using defect reports and correction requests generated during testing to seed our detection process. We found that phrases known from these materials to be problematic have occurrence properties in requirements documents that both allow the direction of resources to prioritize their correction, and generate insights characterizing more general locations of difficulty within the requirements. Our findings lead to some recommendations for more efficiently and effectively managing certain natural language issues in the creation and maintenance of requirements specifications.
Self-organizing semantic maps and its application to word alignment in Japanese-Chinese parallel corpora
Authors: Qing Ma, Kyoko Kanzaki, Yujie Zhang, Masaki Murata, Hitoshi Isahara
Venue: Neural Networks (2004)

This paper presents a method involving self-organizing monolingual semantic maps that are visible and continuous representations where Chinese or Japanese words with similar meanings are placed at the same or neighboring points so that the distance between them represents the semantic similarity. We used the self-organizing map, SOM, as a self-organizing device. The words to be self-organized are defined by sets of co-occurring words collected from Chinese or Japanese newspapers, according to their grammatical relationships. The words are then coded into vectors to be forwarded to the SOM, taking into account the semantic correlation between them, which is established using a form of word-similarity computation. The self-organized monolingual semantic maps are assessed by numerical evaluations of accuracy, recall, and the F-measure, as well as by intuition, and by the comparisons with a clustering method and with multivariate statistical analysis. This paper further discusses the possibility that the method we propose can be extended to constructing Japanese--Chinese bilingual semantic maps, with the aim of providing a semantics-based approach to word alignment in Japanese--Chinese parallel corpora. We also show the effectiveness of this extended method through small-scale comparative experiments with a baseline method, where the alignment of Japanese and Chinese words is directly determined through the Euclidean distance of vectors representing the words, with a clustering method, and with multivariate statistical analysis.
An Area and Configuration-Bit Optimized CLB Architecture and Timing-Driven Packing for FPGAs
Authors: Vivek Garg, Vikram Chandrasekhar, M. Sashikanth, V. Kamakoti
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

This paper proposes a function-generation based area-aware Configurable Logic Block (CLB) architecture and an associated packing technique, for SRAM-based FPGAs. The new CLB architecture provides the same logic functionality, but occupies 38% less area, consumes 38.37% less power and requires 50% less configuration-bits per CLB when compared to the standard 4-LUT CLB architecture. The proposed packing technique is timing-driven and is shown to produce designs with almost same routing cost and performance overhead as that produced by the T-VPack algorithm on standard benchmark circuits.
TCSOM: Clustering Transactions Using Self-Organizing Map
Authors: Zengyou He, Xiaofei Xu, Shengchun Deng
Venue: Neural Processing Letters (2005)

Self-Organizing Map (SOM) networks have been successfully applied as a clustering method to numeric datasets. However, it is not feasible to directly apply SOM for clustering transactional data. This paper proposes the Transactions Clustering using SOM (TCSOM) algorithm for clustering binary transactional data. In the TCSOM algorithm, a normalized Dot Product norm based dissimilarity measure is utilized for measuring the distance between input vector and output neuron. And a modified weight adaptation function is employed for adjusting weights of the winner and its neighbors. More importantly, TCSOM is a one-pass algorithm, which is extremely suitable for data mining applications. Experimental results on real datasets show that TCSOM algorithm is superior to those state-of-the-art transactional data clustering algorithms with respect to clustering accuracy.
Fast maximum margin matrix factorization for collaborative prediction
Authors: Jasson D. M. Rennie, Nathan Srebro
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

Maximum Margin Matrix Factorization (MMMF) was recently suggested (Srebro et al., 2005) as a convex, infinite dimensional alternative to low-rank approximations and standard factor models. MMMF can be formulated as a semi-definite programming (SDP) and learned using standard SDP solvers. However, current SDP solvers can only handle MMMF problems on matrices of dimensionality up to a few hundred. Here, we investigate a direct gradient-based optimization method for MMMF and demonstrate it on large collaborative prediction problems. We compare against results obtained by Marlin (2004) and find that MMMF substantially outperforms all nine methods he tested.
XTreeNet: Scalable Overlay Networks for XML Content Dissemination and Querying (Synopsis)
Authors: William Fenner, Michael Rabinovich, K. K. Ramakrishnan, Divesh Srivastava, Yin Zhang
Venue: Proceedings of the 10th International Workshop on Web Content Caching and Distribution (2005)

XML is becoming a ubiquitous format for information exchange on the Internet. To alleviate the problems of "whom to ask" and "whom to tell" when connecting XML information producers with consumers over the network, content-based querying and dissemination of information have been investigated in the literature. Our XTreeNet project unifies the publish/subscribe and query/response models with a single common XML aware overlay network for XML-based information producers and consumers. This integrated framework lends itself to a variety of applications.
NP Datalog: A Logic Language for NP Search and Optimization Queries
Authors: Sergio Greco, Irina Trubitsyna, Ester Zumpano
Venue: Proceedings of the 9th International Database Engineering & Application Symposium (2005)

This paper presents a logic language, called NP Datalog for NP search and optimization problems. The ¿search¿ language extends stratified Datalog with constraints and partition rules defining (nondeterministically) partition of relations. NP optimization problems are then formulated by adding a max(or min) construct to select the solution (stable model) which maximizes (resp., minimizes) the result of a polynomial function applied to the answer relation. We show that NP Datalog queries can be easily evaluated by translating them into ILOG programs which are next solved by means of the ILOG OPL Studio suite. To prove the effectiveness of our proposal, we have implemented a module, written in Sicstus Prolog, which takes in input a NP Datalog query and outputs an equivalent ILOG program. Several experiments comparing the computation of queries by different logic systems have been also performed.
We Are Sorry to Inform You ...
Authors: Simone Santini
Venue: Computer (2005)

The author ponders how much damage could occur when a reviewer has a bad day.
Store Memory-Level Parallelism Optimizations for Commercial Applications
Authors: Yuan Chou, Lawrence Spracklen, Santosh G. Abraham
Venue: Proceedings of the 38th annual IEEE/ACM International Symposium on Microarchitecture (2005)

This paper studies the impact of off-chip store misses on processor performance for modern commercial applications. The performance impact of off-chip store misses is largely determined by the extent of their overlap with other off-chip cache misses. The epoch MLP model is used to explain and quantify how these overlaps are affected by various store handling optimizations and by the memory consistency model implemented by the processor. The extent of these overlaps are then translated to off-chip CPI. Experimental results show that store handling optimizations are crucial for mitigating the substantial performance impact of stores in commercial applications. While some previously proposed optimizations, such as store prefetching, are highly effective, they are unable to fully mitigate the performance impact of off-chip store misses and they also leave a performance gap between the stronger and weaker memory consistency models. New optimizations, such as the Store Miss Accelerator, an optimization of Hardware Scout and a new application of Speculative Lock Elision, are demonstrated to virtually eliminate the impact of off-chip store misses.
The impact of team and work characteristics on team functioning: Research Articles
Authors: Eric Molleman, Jannes Slomp
Venue: Human Factors in Ergonomics Manufacturing (2006)

In this article, the authors seek to strengthen the theoretical foundation of team and cell formation through the inclusion of human factors. They distinguish three types of team characteristics: global, shared, and compositional attributes. In this last category, they also deal with diversity in teams by addressing three types of variables: demographic characteristics, skills and knowledge, and personality traits. In addition, the authors address the relevance of the structure of diversity in cells. For each of the above-mentioned groups of team characteristics, their potential impact on team functioning is worked out and discussed with simultaneous consideration of the characteristics of the team task. Three industrial examples are included to illustrate the importance of including worker, team, and work characteristics when designing manufacturing cells. &copy; 2006 Wiley Periodicals, Inc. Hum Factors Man 16: 1&ndash;15, 2006.
Multiple Temporal Consistency States for Dynamical Verification of Upper Bound Constraints in Grid Workflow Systems
Authors: Jinjun Chen, Yun Yang
Venue: Proceedings of the First International Conference on e-Science and Grid Computing (2005)

Conventional upper bound constraint verification in grid workflow systems is based on the key assumption that an upper bound constraint only has two states: consistency and inconsistency. However, due to complexity of grid workflows and dynamic availability of participating grid services, this assumption is too restrictive as there may be some intermediate states. Therefore, in this paper, we introduce four states for an upper bound constraint. Namely, we treat conventional consistency as strong consistency and divide conventional inconsistency into weak consistency, weak inconsistency and strong inconsistency. Correspondingly, we develop their verification methods. For weak consistency, we present some algorithms on how to adjust it to strong consistency without triggering exception handling as in conventional work. For weak inconsistency, we analyse why it can rely on less costly exception handling than conventional work. The final evaluation demonstrates that our four-state approach can achieve better cost-effectiveness than the conventional two-state approach.
Collage of two-dimensional words
Authors: Christian Choffrut, Berke Durak
Venue: Theoretical Computer Science (2005)

We consider a new operation on one-dimensional (resp. two-dimensional) word languages, obtained by piling up, one on top of the other, words of a given recognizable language (resp. two-dimensional recognizable language) on a previously empty one-dimensional (resp. two-dimensional) array. The resulting language is the set of words "seen from above": a position in the array is labeled by the topmost letter. We show that in the one-dimensional case, the language is always recognizable. This is no longer true in the two-dimensional case which is shown by a counter-example, and we investigate in which particular cases the result may still hold.
Methodologies and Algorithms for Testing Switch-Based NoC Interconnects
Authors: Cristian Grecu, Partha Pande, Baosheng Wang, Andre Ivanov, Res Saleh
Venue: Proceedings of the 20th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems (2005)

In this paper, we present two novel methodologies for testing the interconnect fabrics of network-on-chip (NoC) based chips. Both use the concept of recursive testing, with different degrees of parallelism in each case. Our test methodologies cover the logic switching blocks and the FIFO buffers that are the basic components of NoC fabrics. The paper concludes with test time evaluations for different NoC topologies and sizes.
A Multivalue Eigenvalue Based Circuit Partitioning Technique
Authors: Blair Schiffner, Jianhua Li, Laleh Behjat
Venue: Proceedings of the Fifth International Workshop on System-on-Chip for Real-Time Applications (2005)

VLSI circuit partitioning is an important step in the physical design of integrated circuits. In VLSI partitioning, a circuit is partitioned into smaller relatively independent sub-circuits. In this paper we present an eigenvalue based multilevel partitioning algorithm. The proposed method uses a matrix re-ordering technique to produce a minimal bandwidth matrix, relying upon matrix sparsity. The reordering technique is applied to the connectivity matrix of a clustered circuit and the matrix connectivity information is obtained. This connectivity information is used to partition the circuit. The experimental results demonstrate the technique¿s effectiveness against flat partitioning algorithms.
Improving Statechart Testing Criteria Using Data Flow Information
Authors: L. C. Briand, Y. Labiche, Q. Lin
Venue: Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (2005)

Empirical studies have shown there is wide variation in cost (e.g., of devising and executing test cases) and effectiveness (at finding faults) across existing state-based coverage criteria. As these criteria can be considered as executing the control flow structure of the statechart, we are attempting to investigate how data flow information can be used to improve their cost-effectiveness. This article presents a comprehensive methodology to perform data flow analysis of UML statecharts, applies it to the round-trip path (transition tree) coverage criterion and reports on two case studies. The results of the case studies show that data flow information can be used to select the best cost-effective transition tree when more than one satisfies the transition tree criterion. We further propose a more optimal strategy for the transition tree criterion, in terms of cost and effectiveness. The improved tree strategy is evaluated through the two case studies and the results suggest that it is a cost-effective strategy that would fit into many practical situations.
Maintaining privacy on derived objects
Authors: Nicola Zannone, Sushil Jajodia, Fabio Massacci, Duminda Wijesekera
Venue: Proceedings of the 2005 ACM workshop on Privacy in the electronic society (2005)

Protecting privacy means to ensure users that access to their personal data complies with their preferences. However, information can be manipulated in order to derive new objects that may disclose part of the original information. Therefore, control of information flow is necessary for guaranteeing privacy protection since users should know and control not only who access their personal data, but also who access information derived from their data. Actually, current approaches for access control do not provide support for managing propagation of information and for representing user preferences.This paper proposes to extend the Flexible Authorization Framework (FAF) in order to automatically verify whether a subject is entitled to process personal data and derive the authorizations associated with the outcome of data processing. In order to control information flow, users may specify the range of authorizations that can be associated with objects derived from their data. The framework guarantees that every "valid" derived object does not disclose more information than users want and preserves the permissions that users want to maintain. To make the discussion more concrete, we illustrate the proposal with a bank case study.
Clustering through ranking on manifolds
Authors: Markus Breitenbach, Gregory Z. Grudic
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-supervised learning technique with the property of learning very smooth functions with respect to the intrinsic structure revealed by the data. Other methods, e.g. Spectral Clustering, obtain good results on data that reveals such a structure. However, unlike Spectral Clustering, our algorithm effectively detects both global and within-class outliers, and the most representative examples in each class. Furthermore, we specify an optimization framework that estimates all learning parameters, including the number of clusters, directly from data. Finally, we show that the learned cluster-models can be used to add previously unseen points to clusters without re-learning the original cluster model. Encouraging experimental results are obtained on a number of real world problems.
Simulation models in regional planning
Authors: Neal A. Irwin, R. Andrew McNally
Venue: ACM SIGSIM Simulation Digest (1973)

Because of the increasing complexity of the activities which shape and influence regional development, and the myriad interaction between these activities, the regional planner is relying more and more on mathematical techniques to understand those processes that describe the "regional system." Moreover, the same mathematical techniques can be employed to test the impact of policy decisions on the appropriate set of primary and secondary activities. For example, a proposal to create a major highdensity center of employment and residential development, could generate traffic demands far in excess of the road network capacity within and adjacent to the center. This can be considered a primary impact. The road congestion, in turn, can cause a shift in the modal split (that is, the percentage of total trips by auto and transit), causing more people to travel to the center by public transit. This can be considered as a secondary impact.
Specifying electronic voting protocols in typed MSR
Authors: Theodoros Balopoulos, Stefanos Gritzalis, Sokratis K. Katsikas
Venue: Proceedings of the 2005 ACM workshop on Privacy in the electronic society (2005)

Electronic voting, as well as other privacy-preserving protocols, use special cryptographic primitives and techniques that are not widely used in other types of protocols, e.g. in authentication protocols. These include blind signatures, commitments, zero-knowledge proofs, mixes and homomorphic encryption. Furthermore, typical formalizations of the Dolev-Yao intruder's capabilities do not take into account these primitives and techniques, nor do they consider some types of attacks that e-voting as well as other types of protocols are designed to protect against, such as privacy attacks due to undesired linkability of protocol executions. This work aims to extend Typed MSR so that it is able to support the specification of privacy-preserving protocols, as well as the capabilities of a Dolev-Yao intruder designed to attack such protocols.
Internet Pricing With Multiple Demands for Quality of Service Option
Authors: Geng Zhang, Zhenyu Liu
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

Price and quality differentiation are valuable tools that can provide higher revenues and increase utilization of a network. This paper discuses the pricing strategy in internet with different demands for quality service option. We provide a pricing model based on profit maximal problem of internet service provider (ISP). Compared with flat-rate pricing, the result of an example shows that ISP would receive more surpluses of consumers from differential pricing strategy.