ppxscal/embedding_network huggingface dataset:
The max K-armed bandit: a new model of exploration applied to search heuristic selection
Authors: Vincent A. Cicirello, Stephen F. Smith
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

The multiarmed bandit is often used as an analogy for the tradeoff between exploration and exploitation in search problems. The classic problem involves allocating trials to the arms of a multiarmed slot machine to maximize the expected sum of rewards. We pose a new variation of the multiarmed bandit--the Max K-Armed Bandit--in which trials must be allocated among the arms to maximize the expected best single sample reward of the series of trials. Motivation for the Max K-Armed Bandit is the allocation of restarts among a set of multistart stochastic search algorithms. We present an analysis of this Max K-Armed Bandit showing under certain assumptions that the optimal strategy allocates trials to the observed best arm at a rate increasing double exponentially relative to the other arms. This motivates an exploration strategy that follows a Boltzmann distribution with an exponentially decaying temperature parameter. We compare this exploration policy to policies that allocate trials to the observed best arm at rates faster (and slower) than double exponentially. The results confirm, for two scheduling domains, that the double exponential increase in the rate of allocations to the observed best heuristic outperfonns the other approaches.
4th Workshop on Software and Usability Engineering Cross-Pollination: Usability Evaluation of Advanced Interfaces
Authors: Regina Bernhaupt, Peter Forbrig, Jan Gulliksen, Janet Wesson
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

The usability evaluation of advanced interfaces such as intelligent, adaptive and context-aware interfaces presents several challenges. These interfaces need to be evaluated over an extended time period and used in their actual context of use, rather than in a laboratory setting. Usability evaluation methods for traditional interactive systems have been extensively researched and are well understood. These methods include heuristic evaluation, usability testing and field studies. The goal of this workshop is to bring together people who are engaged in the design and evaluation of advanced interfaces across different disciplines. The objective is to exchange ideas and techniques relevant to the usability evaluation of advanced interfaces and to establish guidelines for the evaluation of such interfaces that cross-pollinate the different disciplines.
Eliciting subjectivity and polarity judgements on word senses
Authors: Fangzhong Su, Katja Markert
Venue: Proceedings of the Workshop on Human Judgements in Computational Linguistics (2008)

There has been extensive work on eliciting human judgements on the sentiment of words and the resulting annotated word lists have frequently been used for opinion mining applications in Natural Language Processing (NLP). However, this word-based approach does not take different senses of a word into account, which might differ in whether and what kind of sentiment they evoke. In this paper, we therefore introduce a human annotation scheme for judging both the subjectivity and polarity of word senses. We show that the scheme is overall reliable, making this a well-defined task for automatic processing. We also discuss three issues that surfaced during annotation: the role of annotation bias, hierarchical annotation (or underspecification) and bias in the sense inventory used.
The BP Network Study of the Time Series Overrolling Model for Forecasting the Oilfield Output
Authors: Hui-zhen Liang, Jun Xie, Jiang-tao Yu, Ning-ning Meng
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

Based on analyzing fundamental principle of Back Propagation Network Model, in view of the limitations of BP algorism, this paper proposed the homologous improved-algorism from the two aspects of quickening the BP learning speed and raising the degree of convergence. In the course of the complex water flood development, the paper, considering the adaptability feature of the different random factors affecting the wells yield, built the BP time series overrolling model for forecasting the oilfield output, and predicted the wells output using the model, the result indicate that the model have better predicted-accuracy, and fitting to predict the oil production rate and water production rate for different development phase.
Pre-processing closed captions for machine translation
Authors: Davide Turcato, Fred Popowich, Paul McFetridge, Devlan Nicholson, Janine Toole
Venue: ANLP-NAACL 2000 Workshop: Embedded Machine Translation Systems (2000)

We describe an approach to Machine Translation of transcribed speech, as found in closed captions. We discuss how the colloquial nature and input format peculiarities of closed captions are dealt with in a pre-processing pipeline that prepares the input for effective processing by a core MT system. In particular, we describe components for proper name recognition and input segmentation. We evaluate the contribution of such modules to the system performance. The described methods have been implemented on an MT system for translating English closed captions to Spanish and Portuguese.
Improving nonparameteric Bayesian inference: experiments on unsupervised word segmentation with adaptor grammars
Authors: Mark Johnson, Sharon Goldwater
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

One of the reasons nonparametric Bayesian inference is attracting attention in computational linguistics is because it provides a principled way of learning the units of generalization together with their probabilities. Adaptor grammars are a framework for defining a variety of hierarchical nonparametric Bayesian models. This paper investigates some of the choices that arise in formulating adaptor grammars and associated inference procedures, and shows that they can have a dramatic impact on performance in an unsupervised word segmentation task. With appropriate adaptor grammars and inference procedures we achieve an 87% word token f-score on the standard Brent version of the Bernstein-Ratner corpus, which is an error reduction of over 35% over the best previously reported results for this corpus.
"A term is known by the company it keeps": On Selecting a Good Expansion Set in Pseudo-Relevance Feedback
Authors: Raghavendra Udupa, Abhijit Bhole, Pushpak Bhattacharyya
Venue: Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory (2009)

It is well known that pseudo-relevance feedback (PRF) improves the retrieval performance of Information Retrieval (IR) systems in general. However, a recent study by Cao et al [3] has shown that a non-negligible fraction of expansion terms used by PRF algorithms are harmful to the retrieval. In other words, a PRF algorithm would be better off if it were to use only a subset of the feedback terms. The challenge then is to find a good expansion set from the set of all candidate expansion terms. A natural approach to solve the problem is to make term independence assumption and use one or more term selection criteria or a statistical classifier to identify good expansion terms independent of each other. In this work, we challenge this approach and show empirically that a feedback term is neither good nor bad in itself in general; the behavior of a term depends very much on other expansion terms. Our finding implies that a good expansion set can not be found by making term independence assumption in general. As a principled solution to the problem, we propose spectral partitioning of expansion terms using a specific term-term interaction matrix. We demonstrate on several test collections that expansion terms can be partitioned into two sets and the best of the two sets gives substantial improvements in retrieval performance over model-based feedback.
Graphical Annotation of Suspicious Behaviors
Authors: Wang Qiang, Pang Jianmin, Fu Wen, Yue Feng
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

SVG (Scalable Vector Graphics) is a kind of vector image which based on XML. It has many advantages such as high quality of image, flexibility of file format, less occupation of resource and supporting dynamic interaction. SVG is compatible with XML, HTML4, XHTML languages and it accords with the criterions including CSS, XSL and DOM. In this paper we first use decompile technology to analyze suspicious code and detect suspicious behavior. The adopt SVG for annotating suspicious behavior, finally the result is presented in graphical format. The relevant experiment shows that our method is easy to be understand and effective.
BC(eye): Combining Eye-Gaze Input with Brain-Computer Interaction
Authors: Roman Vilimek, Thorsten O. Zander
Venue: Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments (2009)

Gaze-based interfaces gained increasing importance in multimodal human-computer interaction research with the improvement of tracking technologies over the last few years. The activation of selected objects in most eye-controlled applications is based on dwell times. This interaction technique can easily lead to errors if the users do not pay very close attention to where they are looking. We developed a multimodal interface involving eye movements to determine the object of interest and a Brain-Computer Interface to simulate the mouse click. Experimental results show, that although a combined BCI/eye-gaze interface is somewhat slower it reliably leads to less errors in comparison to standard dwell time eye-gaze interfaces.
Taking into account the differences between actively and passively acquired data: the case of active learning with support vector machines for imbalanced datasets
Authors: Michael Bloodgood, K. Vijay-Shanker
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

Actively sampled data can have very different characteristics than passively sampled data. Therefore, it's promising to investigate using different inference procedures during AL than are used during passive learning (PL). This general idea is explored in detail for the focused case of AL with cost-weighted SVMs for imbalanced data, a situation that arises for many HLT tasks. The key idea behind the proposed InitPA method for addressing imbalance is to base cost models during AL on an estimate of overall corpus imbalance computed via a small unbiased sample rather than the imbalance in the labeled training data, which is the leading method used during PL.
Research on Flow-Burst Component Model Based on Reconfiguration Router Unit
Authors: Liu Qiang, Wang Binqiang, Wang Jing, Wang Xianhui
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

In recent years, the research on the routers has paid more attention to open, programmable and high-reconfigurable field. According to this trend, we design the reconfiguration router unit. This paper gave the design principle of the reconfiguration router unit. And based on the principle the paper gave algorithm 1 and 2 to construct the component chain and flow-burst component model, and accomplish the model. In order to design the reconfiguration router unit, configurations are written in XML language that supports user-defined abstractions .This language is both readable by humans and easily manipulated by tools. Due to the model and language, we implement the reconfiguration router unit.
Combining global relevance information with local contextual clues for event-oriented information extraction
Authors: Siddharth Patwardhan
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Existing IE systems tend to focus on a tight window of context surrounding the desired information to be extracted. This research addresses shortcomings of these systems by introducing a two-phase approach to IE that incorporates global relevance information with local contextual evidence, to effectively extract information from free text.
Integrality Property in Preemptive Parallel Machine Scheduling
Authors: Philippe Baptiste, Jacques Carlier, Alexander Kononov, Maurice Queyranne, Sergey Sevastyanov, Maxim Sviridenko
Venue: Proceedings of the Fourth International Computer Science Symposium in Russia on Computer Science - Theory and Applications (2009)

We consider parallel machine scheduling problems with identical machines and preemption allowed. It is shown that every such problem with chain precedence constraints and release dates and an integer-concave objective function satisfies the following integrality property: for any problem instance with integral data there exists an optimal schedule where all interruptions occur at integral dates. As a straightforward consequence of this result, for a wide class of scheduling problems with unit processing times a so-called preemption redundancy property is valid. This means that every such preemptive scheduling problem is equivalent to its non-preemptive counterpart from the viewpoint of both its optimum value and the problem complexity. The equivalence provides new and simpler proofs for some known complexity results and closes a few open questions.
Study and Practice of Highway Network Toll to Anti-defraud of Vehicle That Exchanged the IC Card and Nested the Plate
Authors: Zhijun Huang, Chuangwen Xia
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

In highway network toll collection，defraud of vehicle that exchanged the IC card and nested the plate is the main Evasion charges. and it all the while puzzled the toll collect check-man. This paper simply introduced management method of highway toll collect nowadays, and analysed those two kind of defraud, find there two notability character, one is that there are at least 2 vehicles that have the same vehicle plate compare information in the same highway network at the same time, and those 2 vehicle will be met in the two-line. The other is those vehicle will be overtime at the exit of the highway. So to check those 2 kinds of vehicles, for the highway toll check-man need to find the vehicles that have the same vehicle plate compare information in the same network in the same period of time, as a suspicious vehicle, check it in a variety of ways, if it is the defraud vehicle, write the vehicle information in blacklist; for the toll collector at the exit, need to find if there are other vehicle in the network that have the same vehicle plate compare information with the vehicle that wait to toll, if it is and it is run overtime, may be toll in specious incident program. But In highway, there are so many fee station, that the amount of data calculation is very large, can’t meet the timeliness requirements demand for check-man to anti-defraud and the collector to find if it is shadiness before toll collect. Through careful analysis, we find need to using a fixed method to average cluster all the vehicle plate compare information, so that When we to check, we can compare the same cluster data. This paper introduced the Average Clustering of Discrete Data Based on probability, and introduced it’s application and it’s strongpoint and the shortcoming. For the moment, judge the vehicle if it is overtime basically over as if it’s speed low than 30km./hr, this paper introduce this method’s shortcoming, and put forward a new and useful way todetermine the time-out. At last the paper described this method used for anti-defraud in the northern part of highway network in Guangdong Province and the advantages and disadvantages are analyzed.
Sign Language Online with Signlink Studio 2.0
Authors: Deborah I. Fels, Martin Gerdzhev, Ellen Hibbard, Abby Goodrum, Jan Richards, Jim Hardman, Norma Thompson
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

Recent advances in web technologies and services have expanded the possibility of having a truly multimedia, interactive web experience for many users. It also means that video based content is not just possible but affordable. Online video-based sign language content is now much more prolific. However, most of the interactive functions remain text-based. We describe a tool, Signlink Studio, that allows hyperlinking functionality within video content, called signlinking, sign language-based form elements, and a sign language forum and content management system. We also present three methodologies specifically oriented towards creating sign language video materials for Signlink Studio or other video-based web applications. As a result of this focus on web functionality that is culturally and linguistically relevant, we suggest that a more equitable and inclusive web will evolve.
Quantification of Accessibility: Guidance for More Objective Access Guidelines
Authors: Gregg C Vanderheiden
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Addressing Diversity. Part I: Held as Part of HCI International 2009 (2009)

Accessibility guidelines first began as recommendations or advice to designers interested in creating products that were more accessible to users with disabilities. Over the past two decades, societies have found that relying on voluntary efforts by industry was insufficient and began creating laws and regulations regarding accessibility. However these new regulations were based on the earlier voluntary recommendations, which were often qualitative in nature. For those guidelines where there were no clear objective criteria, it has created problems both for companies trying to conform and by those trying to evaluate conformance. Described here are several efforts to create more useful and objective measures to replace previous general recommendations in the areas of photosensitive seizure disorders, contrast, and provisions relating to low vision.
Improving Probabilistic Interpretation of Medical Diagnoses with Multi-resolution Image Parameterization: A Case Study
Authors: Matjaž Kukar, Luka Šajn
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

Clinicians strive to improve established diagnostic procedures, especially those that allow them to reach reliable early diagnoses. Diagnostics is frequently performed in a stepwise manner which consists of several consecutive tests (steps). The ultimate step in this process is often the "gold standard" reference method. In stepwise testing, results of each diagnostic test can be interpreted in a probabilistic manner by using prior (pre-test) probability and test characteristics (sensitivity and specificity). By using Bayes' formula on these quantities, the posterior (post-test) probability is calculated. If the post-test probability is sufficiently high (or low) to confirm (or exclude) the presence of a disease, diagnostic process is stopped. Otherwise, it proceeds to the next step in sequence. Our case study focuses on improving probabilistic interpretation of scintigraphic images obtained from the penultimate step in coronary artery disease diagnostics. We use automatic image parameterization on multiple resolutions, based on texture description with specialized association rules. Extracted image parameters are combined into more informative composite parameters by means of principle component analysis, and finally used to build automatic classifiers with machine learning methods. Experiments show that the proposed approach significantly increases the number of reliable diagnoses as compared to clinical results in terms.
External-memory pattern databases using structured duplicate detection
Authors: Rong Zhou, Eric A. Hansen
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

A pattern database is a lookup table that stores an exact evaluation function for a relaxed search problem, which provides an admissible heuristic for the original search problem. In general, the larger the pattern database, the more accurate the heuristic function. We consider how to build large pattern databases that are stored in external memory, such as disk, and how to use an external-memory pattern database efficiently in heuristic search. To limit the number of slow disk I/O operations needed to construct and query an external-memory pattern data-base, we adapt an approach to external-memory graph search called structured duplicate detection that localizes memory references by leveraging an abstraction of the state space. We present results that show this approach increases the scalability of heuristic search by allowing larger and more accurate pattern database heuristics.
An Investigation of Function Based Design Considering Affordances in Conceptual Design of Mechanical Movement
Authors: Ying-Chieh Liu, Su-Ju Lu
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

Using the concept of affordances could lead the designer to consider the user's possible actions during design activities, which is increasingly important in many design cases. This paper proposes a model that attempts to incorporate the concept of affordances to function based design in conceptual design of mechanical movement. The role of affordances in the initial design process considers the user's possible actions to the solution in the environment. A simple example of door latch design is demonstrated to see how affordances can support in the divergent and convergent design activities.
Coherency Hub Design for Multisocket Sun Servers with CoolThreads Technology
Authors: John Feehrer, Paul Rotker, Milton Shih, Paul Gingras, Peter Yakutis, Stephen Phillips, John Heath
Venue: IEEE Micro (2009)

CoHub, a coherency hub ASIC, provides a cost-effective way to extend a glueless two-node chip-multithreading system to a four-node system without changes to the processor. The four-node, 256-thread system achieves near-linear scaling of performance with thread count on transaction-processing workloads. Time-to-market pressure, 800-MHz operation, and a six-stage pipeline were among the constraints that shaped CoHub's design.
Study on Rotor Speed Identification of DTC System Based on PSO Algorithms of BP Neural Network
Authors: Chengzhi Cao, Yuanyuan Lu, Fang Wang, Haiying Zheng
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

To solve the strong randomicity and slow convergence of the Particle Swarm Optimization(PSO) algorithms, two new particle’s position renewal formulas were analyzed on the basis of extrapolation in mathematics. A new modified PSO algorithms (called Leading PSO algorithms) was put forward. The Direct Torque Control(DTC) System was built in the environment of Matlab(Simulink). The weight and threshold values of BP Neural Network were trained using the modified PSO algorithms. Some disadvantages such as slow convergence speed and easily plunging into the local solution were avoided effectively. The simulation result shows that the system works well, and the rotor speed identifier has great static and dynamic performance.