ppxscal/embedding_network huggingface dataset:
Work in Progress: Visualizing a Semantic Search in a Room-Based Knowledge Space
Authors: Nadine Ludwig
Venue: Proceedings of the 2009 First International Conference on Advances in Multimedia (2009)

A semantic network acts as an expedient foundation to search for objects in a cooperative room-based knowledge space. But to make the search results useable and give users an intuitive instrument the search interface has to stick to several principles of usability and the search results have to be visualized in an appropriate way. The paper proposed is dealing with the problems related to the visualization of semantic networks and provides a concept for this field of research. This concept includes the analysis of different navigation designs as well as a comparison of different alternative presentations of search results.
WWW traffic measure and its properties
Authors: Marcus R. Keogh-Brown, Barbara Bogacka
Venue: Intelligent Data Analysis (2007)

We present a method to extract a time series (Number of Active Requests (NAR)) from web cache logs which serves as a transport level measurement of internet traffic. This series also reflects the performance or Quality of Service of a web cache. It has long-memory properties but is not self-similar and does not have a heavy-tailed distribution. However, the long-memory and autocorrelation structure of NAR are preserved through aggregation, that is the aggregated series has similar statistical properties to the original one. We call this property aggregation similarity. Aggregation similarity is a very useful property, which makes management of large data sets easier and speeds up the asymptotic properties of time series.
Modeling Emotional Expressions as Sequences of Behaviors
Authors: Radosław Niewiadomski, Sylwia Hyniewska, Catherine Pelachaud
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

In this paper we present a system which allows a virtual character to display multimodal sequential expressions i.e. expressions that are composed of different signals partially ordered in time and belonging to different nonverbal communicative channels. It is composed of a language for the description of such expressions from real data and of an algorithm that uses this description to automatically generate emotional displays. We explain in detail the process of creating multimodal sequential expressions, from the annotation to the synthesis of the behavior.
Activity analysis enabling real-time video communication on mobile phones for deaf users
Authors: Neva Cherniavsky, Jaehong Chon, Jacob O. Wobbrock, Richard E. Ladner, Eve A. Riskin
Venue: Proceedings of the 22nd annual ACM symposium on User interface software and technology (2009)

We describe our system called MobileASL for real-time video communication on the current U.S. mobile phone network. The goal of MobileASL is to enable Deaf people to communicate with Sign Language over mobile phones by compressing and transmitting sign language video in real-time on an off-the-shelf mobile phone, which has a weak processor, uses limited bandwidth, and has little battery capacity. We develop several H.264-compliant algorithms to save system resources while maintaining ASL intelligibility by focusing on the important segments of the video. We employ a dynamic skin-based region-of-interest (ROI) that encodes the skin at higher quality at the expense of the rest of the video. We also automatically recognize periods of signing versus not signing and raise and lower the frame rate accordingly, a technique we call variable frame rate (VFR). We show that our variable frame rate technique results in a 47% gain in battery life on the phone, corresponding to an extra 68 minutes of talk time. We also evaluate our system in a user study. Participants fluent in ASL engage in unconstrained conversations over mobile phones in a laboratory setting. We find that the ROI increases intelligibility and decreases guessing. VFR increases the need for signs to be repeated and the number of conversational breakdowns, but does not affect the users' perception of adopting the technology. These results show that our sign language sensitive algorithms can save considerable resources without sacrificing intelligibility.
Analysis of the Possibilities to Adapt the Foreign Language Speech Recognition Engines for the Lithuanian Spoken Commands Recognition
Authors: Rytis Maskeliunas, Algimantas Rudzionis, Vytautas Rudzionis
Venue: Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions: COST Action 2102 International Conference Prague, Czech Republic, October 15-18, 2008 Revised Selected and Invited Papers (2009)

This paper presents our activities trying to adapt the foreign language based speech recognition engine for the recognition of the Lithuanian speech commands. The speakers of less popular languages (such as the Lithuanian) have several choices: to develop own speech recognition engines or to try adapting the speech recognition models developed and trained for the foreign languages to the task of recognition of their native spoken language. The first approach is expensive in time, financial and human resources sense. The second approach can lead to the faster implementation of the Lithuanian speech recognition modules into some practical tasks but the proper adaptation and optimization procedures should be found and investigated. This paper presents some of our efforts trying to adapt the foreign language oriented speech recognition engines for the recognition of the Lithuanian speech commands for the speaker-independent applications. The experimental investigation shows that the promising results could be achieved with relatively modest investments.
Evaluation for Adjustment Method of Vehicle's Location by Recognizing Crosswalks
Authors: Yoshihisa Yamaguchi, Takashi Nakagawa, Hirokazu Kato, Shogo Nishida
Venue: Proceedings of the Symposium on Human Interface 2009 on ConferenceUniversal Access in Human-Computer Interaction. Part I: Held as Part of HCI International 2009 (2009)

We have developed AR-Navi, an in-vehicle navigation system that captures real-time video via an in-vehicle camera and overlays guidance on a video display. In this study, we conducted a driving experiment to evaluate the location-adjustment-method of AR-Navi. We also discuss the registration accuracy of the route guidance that AR-Navi gives at intersections.
Dynamics Analysis of Facial Expressions for Person Identification
Authors: Hidenori Tanaka, Hideo Saito
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

We propose a new method for analyzing the dynamics of facial expressions to identify persons using Active Appearance Models and accurate facial feature point tracking. Several methods have been proposed to identify persons using facial images. In most methods, variations in facial expressions are one trouble factor. However, the dynamics of facial expressions are one measure of personal characteristics. In the proposed method, facial feature points are automatically extracted using Active Appearance Models in the first frame of each video. They are then tracked using the Lucas-Kanade based feature point tracking method. Next, a temporal interval is extracted from the beginning time to the ending time of facial expression changes. Finally, a feature vector is obtained. In the identification phase, an input feature vector is classified by calculating the distance between the input vector and the training vectors using dynamic programming matching. We show the effectiveness of the proposed method using smile videos from the MMI Facial Expression Database.
Pseudo Relevance Feedback Using Fast XML Retrieval
Authors: Hiroki Tanioka
Venue: Advances in Focused Retrieval: 7th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2008, Dagstuhl Castle, Germany, December 15-18, 2008. Revised and Selected Papers (2009)

This paper reports the result of experimentation of our approach using the vector space model for retrieving large-scale XML data. The purposes of the experiments are to improve retrieval precision on the INitiative for the Evaluation of XML Retrieval (INEX) 2008 Adhoc Track, and to compare the retrieval time of our system to other systems on the INEX 2008 Efficiency Track. For the INEX 2007 Adhoc Track, we developed a system using a relative inverted-path (RIP) list and a Bottom-UP approach. The system achieved reasonable retrieval time for XML data. However the system has a room for improvement in terms of retrieval precision. So for INEX 2008, the system uses CAS titles and Pseudo Relevance Feedback (PRF) to improve retrieval precision. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
TIMELINESAs we may recall: four forgotten pioneers
Authors: Michael Buckland
Venue: interactions (2009)

Editor's Note: Occasionally in studying HCI history, I have stumbled upon large topics that I was unaware existed. Perhaps the most surprising has been the development of advanced information technologies, which preceded computers. In some ways, the constraints imposed by those technologies forced deeper thinking about information itself. In this column, Berkeley Professor Emeritus Michael Buckland describes the work of four dedicated creative pioneers.---Jonathan Grudin
A framework for model-based evaluation of spoken dialog systems
Authors: Sebastian Möller, Nigel G. Ward
Venue: Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue (2008)

Improvements in the quality, usability and acceptability of spoken dialog systems can be facilitated by better evaluation methods. To support early and efficient evaluation of dialog systems and their components, this paper presents a tripartite framework describing the evaluation problem. One part models the behavior of user and system during the interaction, the second one the perception and judgment processes taking place inside the user, and the third part models what matters to system designers and service providers. The paper reviews available approaches for some of the model parts, and indicates how anticipated improvements may serve not only developers and users but also researchers working on advanced dialog functions and features.
Is nonparametric learning practical in very high dimensional spaces?
Authors: Gregory Z. Grudic, Peter D. Lawrence
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

Many of the challenges faced by the field of Computational Intelligence in building intelligent agents, involve determining mappings between numerous and varied sensor inputs and complex and flexible action sequences. In applying nonparametric learning techniques to such problems we must therefore ask: "Is nonparametric learning practical in very high dimensional spaces?" Contemporary wisdom states that variable selection and a "greedy" choice of appropriate functional structures are essential ingredients for nonparametric learning algorithms. However, neither of these strategies is practical when learning problems have thousands of input variables, and tens of thousands of learning examples. We conclude that such nonparametric learning is practical by using a methodology which does not use either of these techniques. We propose a simple nonparametric learning algorithm to support our conclusion. The algorithm is evaluated first on 10 well known regression data sets, where it is shown to produce regression functions which are as good or better than published results on 9 of these data sets. The algorithm is further evaluated on 15 large, very high dimensional data sets (40,000 learning examples of 100, 200, 400, 800 and 1600 dimensional data) and is shown to construct effective regression functions despite the presence of noise in both inputs and outputs.
Finite Element Analysis and Shape Optimization of Automotive Crash-Box Subjected to Low Velocity Impact
Authors: Qing-fen Li, Yan-jie Liu, Hai-dou Wang, Sheng-yuan Yan
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Abstract—Crash-box equipped at the front end of a car, is one of the most important automotive parts for crash energy absorption. In case of frontal crash accident, it is expected to be collapsed with absorbing crash energy prior to other body parts so that the damage of the main cabin frame is minimized and passengers may be saved. In the present work, energy absorption characters of automobile crash-box at low-velocity impact are studied by using Finite Element Method and shape optimization design for thin-walled tubes has been successfully proposed through choosing proper cross section and adopting appropriate grooves. Six types of thin-walled tubes with different cross section were studied and different grooves on the tubes were adopted and compared. Results show that the energy absorption characters improved obviously for square cross section thin-walled tube with double concave and bulgy grooves.
The Understanding between Two Agent Crawlers based on Domain Ontology
Authors: Yingyu Wang, Yajun Du, Shaoming Chen
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

Ontology is widely used in the computer domain to structure concepts that represent a view of world. In this paper, we present the coordination between two Agent Crawlers based on ontology and try to measure the understanding between them relying on Formal Concept Analysis instead of comparing terms only. Here we propose a novel method on concept similarity for computing the Concept-Concept similarity, the Concept-Ontology similarity and the Ontology-Ontology similarity, and at last we can deduce the understanding between two Agent Crawlers. Finally, we can guide the crawlers effectively in our Search Engine.
Automated Test Case Generation and Its Optimization for Path Testing Using Genetic Algorithm and Sampling
Authors: Debasis Mohapatra, Prachet Bhuyan, Durga P. Mohapatra
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Software testing is an important activity of the software development process, and automated test case generation contributes to reduce cost and time efforts. In this paper, we have used genetic algorithm to optimize the test cases that are generated using the category-partition and test harness patterns. In order to investigate the effectiveness of the approach, a graph is derived using category-partition and genetic algorithm is used to optimize the test cases to cover the entire possible path. The optimal test suites are devised by the method of sampling statistics.
Modelling Flexible Processes with Business Objects
Authors: Guy Redding, Marlon Dumas, Arthur H. M. ter Hofstede, Adrian Iordachescu
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

Mainstream business process modelling techniques promote a design paradigm wherein the activities that may be performed within a case, together with their usual execution order, form the backbone on top of which other aspects are anchored. This Fordist paradigm, while effective in standardised and production-oriented domains, breaks when confronted with processes in which case-by-case variations and exceptions are the norm. We contend that the effective design of flexible processes calls for a substantially different modelling paradigm: one where processes are organized as interacting business objects rather than as chains of activities. This paper presents a meta-model for business process modelling based on business objects. The paper also presents a real-life case study in which a number of human service delivery processes were designed using the presented meta-model. The case study demonstrates that the meta-model addresses three key flexibility requirements encountered in this domain.
Skill reconstruction as induction of LQ controllers with subgoals
Authors: Dorian Suc, Ivan Bratko
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

Controlling a complex dynamic system, such as a plane or a crane, usually requires a skilled operator. Such a control skill is typically hard to reconstruct through introspection. Therefore an attractive approach to the reconstruction of control skill involves machine learning from operators' control traces, also known as behavioural cloning. In the most common approach to behavioural cloning, a controller is induced in the form of a rule set or a decision or regression tree that maps system states to actions. Unfortunately, induced controllers usually suffer from lack of robustness and lack typical elements of human control strategies, such as subgoals and substages of the control plan. In this paper we present a new approach to behavioural cloning which involves the induction of a model of the controlled system and enables the identification of subgoals that the operator is pursuing at various stages of the execution trace. The underlying formal basis for the present approach to behavioural cloning is the theory of LQ controllers. Experimental results show that this approach greatly improves the robustness of the induced controllers and also offers a new way of understanding the operator's subcognitive skill.
Correcting a PoS-tagged corpus using three complementary methods
Authors: Hrafn Loftsson
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

The quality of the part-of-speech (PoS) annotation in a corpus is crucial for the development of PoS taggers. In this paper, we experiment with three complementary methods for automatically detecting errors in the PoS annotation for the Icelandic Frequency Dictionary corpus. The first two methods are language independent and we argue that the third method can be adapted to other morphologically complex languages. Once possible errors have been detected, we examine each error candidate and hand-correct the corresponding PoS tag if necessary. Overall, based on the three methods, we hand-correct the PoS tagging of 1,334 tokens (0.23% of the tokens) in the corpus. Furthermore, we re-evaluate existing state-of-the-art PoS taggers on Icelandic text using the corrected corpus.
Beautiful Teams: Inspiring and Cautionary Tales from Veteran Team Leaders, 1st edition
Authors: Andrew Stellman, Jennifer Greene
Venue:  (2009)

What's it like to work on a great software development team facing an impossible problem? How do you build an effective team? Can a group of people who don't get along still build good software? How does a team leader keep everyone on track when the stakes are high and the schedule is tight? Beautiful Teams takes you behind the scenes with some of the most interesting teams in software engineering history. You'll learn from veteran team leaders' successes and failures, told through a series of engaging personal stories -- and interviews -- by leading programmers, architects, project managers, and thought leaders. This book includes contributions from: Tim O'Reilly Scott Berkun Mark Healey Bill DiPierre Andy Lester Keoki Andrus Tom Tarka Auke Jilderda Grady Booch Jennifer Greene Mike Cohn Cory Doctorow Neil Siegel Trevor Field James Grenning Steve McConnell Barry Boehm and Maria H. Penedo Peter Gluck Karl E. Wiegers Alex Martelli Karl Fogel Michael Collins Karl Rehmer Andrew Stellman Ned Robinson Scott Ambler Johanna Rothman Mark Denovich and Eric Renkey Patricia Ensworth Andy Oram Tony Visconti Beautiful Teams is edited by Andrew Stellman and Jennifer Greene, veteran software engineers and project managers who have been writing bestselling books for O'Reilly since 2005, including Applied Software Project Management, Head First PMP, and Head First C#.
New approaches to optimization and utility elicitation in autonomic computing
Authors: Relu Patrascu, Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

Autonomic (self-managing) computing systems face the critical problem of resource allocation to different computing elements. Adopting a recent model, we view the problem of provisioning resources as involving utility elicitation and optimization to allocate resources given imprecise utility information. In this paper, we propose a new algorithm for regret-based optimization that performs significantly faster than that proposed in earlier work. We also explore new regret-based elicitation heuristics that are able to find near-optimal allocations while requiring a very small amount of utility information from the distributed computing elements. Since regret-computation is intensive, we compare these to the more tractable Nelder-Mead optimization technique w.r.t. amount of utility information required.
A web-based demonstrator of a multi-lingual phrase-based translation system
Authors: Roldano Cattoni, Nicola Bertoldi, Mauro Cettolo, Boxing Chen, Marcello Federico
Venue: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations (2006)

This paper describes a multi-lingual phrase-based Statistical Machine Translation system accessible by means of a Web page. The user can issue translation requests from Arabic, Chinese or Spanish into English. The same phrase-based statistical technology is employed to realize the three supported language-pairs. New language-pairs can be easily added to the demonstrator. The Web-based interface allows the use of the translation system to any computer connected to the Internet.
Teamtalk: a platform for multi-human-robot dialog research in coherent real and virtual spaces
Authors: Thomas K. Harris, Alexander I. Rudnicky
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Performing experiments with human-robot interfaces often requires the allocation of expensive and complex hardware and large physical spaces. Those costs constrain development and research to the currently affordable resources, and they retard the testing-and-redevelopment cycle. In order to explore research free from mundane allocation constraints and speed-up our platform development cycle, we have developed a platform for research of multi-human-robot spoken dialog in coherent real and virtual spaces. We describe the system, and speculate on how it will further research in this domain.
Skinner-Pigeon Experiment Simulated Based on Probabilistic Automata
Authors: Xiaogang Ruan, Jianxian Cai
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

This paper constructs a learning probabilistic automata (PA) model with response of operant conditioning (OC) behavior, which used for simulating skinner-pigeon experiment. The PA model with OC is a form of animal learning in that it allows an agent to adapt its actions to gain maximally from the environment while only being rewarded for correct performance. The learning mechanism achieved by design probability of action selection, which is updated by the information of reward and punishment form the environment, and then the agent select an action random according to the probability of action selection. We apply our model to skinner-pigeon experiment, the peck button task. The pigeon learn this task in stages. In simulation, our model also acquires the task in a similar manner.