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检索条件"任意字段=Conference on Visual Data Exploration and Analysis IV"

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Prediction and analysis of Amazon User Behavior Based on Long Short-Term Memory and Manual Feature

Prediction and Analysis of Amazon User Behavior Based on Lon...

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2021 International conference on Artificial Intelligence, Big data and Algorithms, CAIBDA 2021

作者： Li, Mingyi Mao, Huimin Hu, Jiayu Li, Bin Northwest University School of Information Science and Technology Xian China

ISBN: (纸本)9781665424905

The user preference information implicits that the user behavior sequence has an important impact on the click-through rate estimation. Current research on click-through rate estimation mostly designs models from the perspective of low- order and high-order interactions of modeling features, which is difficult to fully explore and utilize user preference information implied in the user's historical behavior sequence. This article reviews and summarizes the results of previous research and exploration on the click-through rate estimation problem. On this basis, this article proposes a click-through rate prediction model based on user preference networks, modeling user preferences. Two Experiments on the two click-through rate prediction models proposed in this paper based on user preference networks are conducted based on the international public data set. The final experimental results show that the model proposed in this paper can fully mine user preference information hidden in user behavior sequences and, as a result, obtain more effective results. User preference indicates that compared to other comparative click-through rate estimation models, it has achieved better performance in the relative improvement of AUC and models. © 2021 IEEE.

关键词： Forecasting

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exploration of the Anomalies in HVAC data Using Image Similarity Assessment 9

Exploration of the Anomalies in HVAC Data Using Image Simila...

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9th Mediterranean conference on Embedded Computing (MECO)

作者： Novikova, Evgenia Bestuzhev, Mikhail St Petersburg Electrotech Univ LETI Dept Comp Sci & Engn St Petersburg Russia

ISBN: (纸本)9781728169491

The usage of the smart IoT devices has introduced the appearance of new hazardous scenarios of disruption, including possible attacks on heating, ventilation and conditioning (HVAC) systems. The visualization-driven approaches may greatly facilitate the work of analyst when revealing anomalies in dataset especially when there is no or little prior information about the HVAC system functioning. The paper presents an approach to the HVAC data analysis that enables automated search of the days with similar HVAC functioning patterns based on image similarity analysis. The core idea of the approach is to form graphical presentation of the HVAC data for each day and then assess their similarity by calculating structural similarity index for each generated image. Days characterized by high level of dissimilarity can be considered as anomalous ones requiring particular attention of an analyst. To test the approach proposed, we used the VAST MiniChallenge-2 2016 data set that contains logs from the HVAC system.

关键词： HVAC anomaly detection visual analytics search-by-pattern density map RadViz structural similarity index

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Overview of the ImageCLEF 2021: Multimedia Retrieval in Medical, Nature, Internet and Social Media Applications 12th

Overview of the ImageCLEF 2021: Multimedia Retrieval in Medi...

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12th International conference of the CLEF Association (CLEF)

作者： Ionescu, Bogdan Muller, Henning Peteri, Renaud Ben Abacha, Asma Sarrouti, Mourad Demner-Fushman, Dina Hasan, Sadid A. Kozlovski, Serge Liauchuk, Vitali Cid, Yashin Dicente Kovalev, Vassili Pelka, Obioma de Herrera, Alba Garcia Seco Jacutprakart, Janadhip Friedrich, Christoph M. Berari, Raul Tauteanu, Andrei Fichou, Dimitri Brie, Paul Dogariu, Mihai Stefan, Liviu Daniel Constantin, Mihai Gabriel Chamberlain, Jon Campello, Antonio Clark, Adrian Oliver, Thomas A. Moustahfid, Hassan Popescu, Adrian Deshayes-Chossart, Jerome Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Delemont Switzerland Univ La Rochelle La Rochelle France Natl Lib Med Bethesda MD USA CVS Hlth Wellesley MA USA United Inst Informat Problems Minsk BELARUS Univ Warwick Coventry W Midlands England Univ Appl Sci & Arts Dortmund Dortmund Germany Univ Essex Colchester Essex England TeleportHQ Cluj Napoca Romania Wellcome Trust Res Labs London England Pacific Isl Fisheries Sci Ctr Silver Spring MD USA Univ Paris Saclay List CEA Palaiseau France

ISBN: (纸本)9783030852504;9783030852511

This paper presents an overview of the ImageCLEF 2021 lab that was organized as part of the conference and Labs of the Evaluation Forum - CLEF Labs 2021. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2021, the 19th edition of ImageCLEF runs four main tasks: (i) a medical task that groups three previous tasks, i.e., caption analysis, tuberculosis prediction, and medical visual question answering and question generation, (ii) a nature coral task about segmenting and labeling collections of coral reef images, (iii) an Internet task addressing the problems of identifying hand-drawn and digital user interface components, and (iv) a new social media aware task on estimating potential real-life effects of online image sharing. Despite the current pandemic situation, the benchmark campaign received a strong participation with over 38 groups submitting more than 250 runs.

关键词： visual question answering and generation Medical image classification Coral image segmentation and classification Recognition of website user interface components Prediction of effects of online image sharing ImageCLEF lab

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The Use of Embedded Interaction Mechanisms for Low-Level analysis Tasks 53

The Use of Embedded Interaction Mechanisms for Low-Level Ana...

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53rd Annual Hawaii International conference on System Sciences (HICSS)

作者： Sandouka, Kari Noteboom, Cherie Dakota State Univ Madison SD 57042 USA

ISBN: (纸本)9780998133133

The use of information visualization is a strategy to reduce information overload and cognitive efforts. Interaction mechanisms aid the exploration of data when it is not practical to display all data points in one visual display. This study reports the results of a pilot study. The purpose of the study is to determine what interactive mechanisms are used and how they support a task or set of tasks.

关键词： Information use

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Towards an Understanding of Augmented Reality Extensions for Existing 3D data analysis Tools 20

Towards an Understanding of Augmented Reality Extensions for...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Wang, Xiyao Besancon, Lonni Rousseau, David Sereno, Mickael Ammi, Mehdi Isenberg, Tobias Univ Paris Saclay CNRS INRIA LRI Orsay France Linkoping Univ Norrkoping Sweden Univ Paris Saclay CNRS IJCLab Orsay France Univ Paris 08 Paris France

ISBN: (纸本)9781450367080

We present an observational study with domain experts to understand how augmented reality (AR) extensions to traditional PC-based data analysis tools can help particle physicists to explore and understand 3D data. Our goal is to allow researchers to integrate stereoscopic AR-based visual representations and interaction techniques into their tools, and thus ultimately to increase the adoption of modern immersive analytics techniques in existing data analysis workflows. We use Microsoft's HoloLens as a lightweight and easily maintainable AR headset and replicate existing visualization and interaction capabilities on both the PC and the AR view. We treat the AR headset as a second yet stereoscopic screen, allowing researchers to study their data in a connected multi-view manner. Our results indicate that our collaborating physicists appreciate a hybrid data exploration setup with an interactive AR extension to improve their understanding of particle collision events.

关键词： Immersive analytics 3D visualization User interface Hybrid visualization system

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Intelligent Blockage Recognition using Cellular mmWave Beamforming data: Feasibility Study

Intelligent Blockage Recognition using Cellular mmWave Beamf...

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GLOBECOM 2022 - 2022 IEEE Global Communications conference

作者： Bram van Berlo Yang Miao Rizqi Hersyandika Nirvana Meratnia Tanir Ozcelebi Andre Kokkeler Sofie Pollin Mathematics and Computer Science Eindhoven University of Technology the Netherlands Radio Systems University of Twente the Netherlands Networked Systems Katholieke Universiteit Leuven Belgium

ISBN: (纸本)9781665435413

Joint Communication and Sensing (JCAS) is envisioned for 6G cellular networks, where sensing the operation environment, especially in presence of humans, is as important as the high-speed wireless connectivity. Sensing, and subsequently recognizing blockage types, is an initial step towards signal blockage avoidance. In this context, we investigate the feasibility of using human motion recognition as a surrogate task for blockage type recognition through a set of hypothesis validation experiments using both qualitative and quantitative analysis (visual inspection and hyperparameter tuning of deep learning (DL) models, respectively). A surrogate task is useful for DL model testing and/or pre-training, thereby requiring a low amount of data to be collected from the eventual JCAS environment. Therefore, we collect and use a small dataset from a 26 GHz cellular multi-user communication device with hybrid beamforming. The data is converted into Doppler Frequency Spectrum (DFS) and used for hypothesis validations. Our research shows that (i) the presence of domain shift between data used for learning and inference requires use of DL models that can successfully handle it, (ii) DFS input data dilution to increase dataset volume should be avoided, (iii) a small volume of input data is not enough for reasonable inference performance, (iv) higher sensing resolution, causing lower sensitivity, should be handled by doing more activities/gestures per frame and lowering sampling rate, and (v) a higher reported sampling rate to STFT during pre-processing may increase performance, but should always be tested on a per learning task basis.

关键词： Wireless communication Wireless sensor networks visualization Array signal processing Statistical analysis data models Sensors

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visual analysis of Tissue Images at Cellular Level

Visual Analysis of Tissue Images at Cellular Level

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23rd Eurographics conference on visualization, EuroVis 2021

作者： Somarakis, A. Ijsselsteijn, Marieke E. Kenkhuis, Boyd van Unen, Vincent Luk, Sietse J. Koning, Frits van der Weerd, Louise de Miranda, Noel F.C.C. Lelieveldt, Boudewijn P.F. Höllt, T. Radiology Department Leiden University Medical Center Leiden Netherlands Pathology Department Leiden University Medical Center Leiden Netherlands Human Genetics Department Leiden University Medical Center Leiden Netherlands School of Medicine Stanford University StanfordCA United States Hematology Department Leiden University Medical Center Leiden Netherlands Immunology Department Leiden University Medical Center Leiden Netherlands Computer Graphics and Visualization Department TU Delft Delft Netherlands

ISBN: (纸本)9783038681472

The detailed analysis of tissue composition is crucial for the understanding of tissue functionality. For example, the location of immune cells related to a tumour area is highly correlated with the effectiveness of immunotherapy. Therefore, experts are interested in presence of cells with specific characteristics as well as the spatial patterns they form. Recent advances in single-cell imaging modalities, producing high-dimensional, high-resolution images enable the analysis of both of these features. However, extracting useful insight on tissue functionality from these high-dimensional images poses serious and diverse challenges to data analysis. We have developed an interactive, data-driven pipeline covering the main analysis challenges experts face, from the pre-processing of images via the exploration of tissue samples to the comparison of cohorts of samples. All parts of our pipeline have been developed in close collaboration with domain experts and are already a vital part in their daily analysis routine. © 2021 The Author(s) Eurographics Proceedings © 2021 The Eurographics Association.

关键词： Pipelines

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2020 24th International conference Information visualisation, iv 2020

2020 24th International Conference Information Visualisation...

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24th International conference Information visualisation, iv 2020

ISBN: (纸本)9781728191348

The proceedings contain 123 papers. The topics discussed include: VarCopy: a visual exploratory data analysis platform for copy number variation studies;visualizing transformers for NLP: a brief survey;visualization of correlations between places of music listening and acoustic features;the affordance of law. sliding treemaps browsing hierarchically structured data on touch devices;enhancing scatter-plots with start-plots for visualizing multi-dimensional data;systematic variation of preattentive attributes to highlight relevant data in information visualization;effects of individual difference on user-sketched layouts of vertex-weighted graphs;and time-aligned edge plots for dynamic graph visualization.

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data Virtual Machines: Simplifying data Sharing, exploration & Querying in Big data Environments

Data Virtual Machines: Simplifying Data Sharing, Exploration...

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IEEE International conference on Big data

作者： Damianos Chatziantoniou Verena Kantere Nikos Antoniou Angeliki Gantzia AUEB Greece NTUA Greece

ISBN: (纸本)9781665480468

Today’s analytics environments are characterized by a high degree of heterogeneity in terms of data systems, formats and types of analysis. Many occasions call for rapid, ad hoc, on demand construction of a data model that represents (parts of) the data infrastructure of an organization, including ML tasks. This data model is given to data scientists to play with (express reports, build ML models, explore, etc.) We present a novel graph-based conceptual model, the data Virtual Machine (DVM) representing data (persistent, transient, derived) of an organization. A DVM can be built quickly and agilely, offering schema flexibility. It is amenable to visual interfaces for schema and query management. dataframing, a frequent querying/preprocessing task in analytics applications, is usually carried out by experienced data engineers employing SQL (in the presence of a relational data warehouse) or Python/R: a procedural approach with all the known drawbacks. dataframes over DVMs are expressed declaratively - and visually, via a simple and intuitive tool. This way, non-IT experts can be involved in dataframing. In addition, query evaluation takes place within an algebraic framework with all the known benefits. I.e. a DVM enables the delegation of data engineering tasks to simpler users. We have seen analogous cases in the past, e.g. with the introduction of SQL. Finally, a DVM offers a formalism that facilitates data sharing, data portability and a single view of any entity – because a DVM’s node is an attribute and an entity at the same time. In this respect, DVMs can excellently serve as a data virtualization technique, an emerging trend in the industry. We argue that DVMs can have a significant practical impact in today’s big data environments.

关键词： visualization Query processing Organizations Big data Market research data models Virtual machining

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Immersive simulations of acoustics for building analysis: An alternative application of unreal engine as a design tool for acoustic environments 25

Immersive simulations of acoustics for building analysis: An...

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25th International conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020

作者： Yeow, Michael Tracy, Kenneth Yogiaman, Christine Singapore University of Technology and Design Singapore

ISBN: (纸本)9789887891734

This paper presents the exploration and analysis of alternative workflows in studying acoustics in architectural models, utilized in the development of the author's thesis project. Acoustic simulation software allows professionals to better understand the effects of different acoustic strategies on the overall aural experience of the space. These results are often presented as quantitative data, and auralisation programs cut back on visual representation for acoustic accuracy. The objective of this investigation is to explore the possibility of utilizing Unreal Engine as an acoustic simulation software that provides both quantitative data and an immersive understanding of the audio-visual experience of a space designed. © 2020 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.

关键词： Engines

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