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Fast, visual and Interactive Semi-supervised Dimensionality Reduction 15th

Fast, Visual and Interactive Semi-supervised Dimensionality ...

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15th European conference on Computer Vision (ECCV)

作者： Spathis, Dimitris Passalis, Nikolaos Tefas, Anastasios Aristotle Univ Thessaloniki Thessaloniki Greece Univ Cambridge Cambridge England

ISBN: (纸本)9783030110185;9783030110178

Recent advances in machine learning allow us to analyze and describe the content of high-dimensional data ranging from images and video to text and audio data. In order to visualize that data in 2D or 3D, usually Dimensionality Reduction (DR) techniques are employed. Most of these techniques produce static projections without taking into account corrections from humans or other data exploration scenarios. In this work, we propose a novel interactive DR framework that is able to learn the optimal projection by exploiting the user interactions with the projected data. We evaluate the proposed method under a widely used interaction scenario in multidimensional projection literature, i.e., project a subset of the data, rearrange them better in classes, and then project the rest of the dataset, and we show that it greatly outperforms competitive baseline and state-of-the-art techniques, while also being able to readily adapt to the computational requirements of different applications.

关键词： Interactive dimensionality reduction Similarity-embeddings

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ProcessExplorer: Intelligent Process Mining Guidance 17th

ProcessExplorer: Intelligent Process Mining Guidance

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Blockchain Forum / Central and Eastern Europe Forum (CEE Forum) / 17th International conference on Business Process Management (BPM)

作者： Seeliger, Alexander Guinea, Alejandro Sanchez Nolle, Timo Muehlhaeuser, Max Tech Univ Darmstadt Telecooperat Lab Darmstadt Germany

ISBN: (纸本)9783030266189;9783030266196

Large amount of data is collected in event logs from information systems, reflecting the actual execution of business processes. Due to the highly competitive pressure in the market, organizations are particularly interested in optimizing their processes. Process mining enables the extraction of valuable knowledge from event logs, such as deviations, bottlenecks, and anomalies. Due to the increase of process complexity in flexible environments, visual exploration is increasingly becoming more challenging. In this paper, we propose ProcessExplorer, an interactive process mining approach to enable fast data analysis and exploration. ProcessExplorer takes an event log as input to automatically suggest subsets of similar process behavior, evaluate each subset, generate interesting insights, and suggest the subsets with the most interesting characteristics. We implemented our approach into an interactive visual exploration system, which we use as part of a user study conducted to evaluate our approach. Our results show that ProcessExplorer can be successfully applied to analyze and explore real-life data sets efficiently.

关键词： Process mining Interactive data exploration data analytics Business intelligence Recommender system

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visualizing Transformers for NLP: A Brief Survey

Visualizing Transformers for NLP: A Brief Survey

引用

International conference on Information visualisation (iv)

作者： Adrian M. P. Braşoveanu Răzvan Andonie MODUL Technology GmbH Vienna Austria Transilvania University Braşov Romania Central Washington University Ellensburg WA USA

ISBN: (数字)9781728191348

ISBN: (纸本)9781728191355

The introduction of Transformer neural networks has changed the landscape of Natural Language Processing during the last three years. While models inspired by it have managed to lead the boards for a variety of tasks, some of the mechanisms through which these performances were achieved are not necessarily well-understood. Our survey is focused mostly on explaining Transformer architectures through visualizations. Since visualization enables some degree of explainability, we have examined the various Transformer facets that can be explored through visual analytics. The field is still at a nascent stage and is expected to witness dynamic growth in the near future, since the results are already interesting and promising. Currently, some of the visualizations are relatively close to their original models, whereas others are model-agnostic. The visualizations designed to explore the Transformer architectures enable some additional features, like exploration of all neuronal cells or attention maps, therefore providing an advantage for this particular task. We conclude by proposing a set of requirements for future Transformer visualization frameworks.

关键词： visualization visual analytics Semantics Natural language processing Task analysis Speech processing Biological neural networks

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Multimodal Dialog for Browsing Large visual Catalogs using exploration-Exploitation Paradigm in a Joint Embedding Space 19

Multimodal Dialog for Browsing Large Visual Catalogs using E...

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ACM International conference on Multimedia Retrieval (ICMR)

作者： Bhattacharya, Indrani Chowdhury, Arkabandhu Raykar, Vikas C. Rensselaer Polytech Inst Troy NY 12180 USA Rice Univ Houston TX USA IBM Res Bangalore Karnataka India

ISBN: (纸本)9781450367653

We present a multimodal dialog (MMD) system to assist online customers in visually browsing through large catalogs. visual browsing allows customers to explore products beyond exact search results. We focus on a slightly asymmetric version of a complete MMD system, in that our agent can understand both text and image queries, but responds only in images. We formulate our problem of lshowing the k best images to a userz, based on the dialog context so far, as sampling from a Gaussian Mixture Model (GMM) in a high dimensional joint multimodal embedding space. The joint embedding space is learned by Common Representation Learning and embeds both the text and the image queries. Our system remembers the context of the dialog, and uses an exploration-exploitation paradigm to assist in visual browsing. We train and evaluate the system on an MMD dataset that we synthesize from large catalog data. Our experiments and preliminary human evaluation show that the system is capable of learning and displaying relevant products with an average cosine similarity of 0.85 to the ground truth results, and is capable of engaging human users.

关键词： Multimodal dialog visual browsing common representation learning interactive AI agent multimodal content analysis and retrieval online human-computer interaction

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visualization of similarity queries with trajectory estimation in complex data

Visualization of similarity queries with trajectory estimati...

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International conference on Information visualisation (iv)

作者： Claudio Eduardo Paiva Roseval Donisete Malaquias Renato Bueno São Paulo State Technological College Franca SP Brazil Federal University of São Carlos São Carlos SP Brazil

ISBN: (数字)9781728191348

ISBN: (纸本)9781728191355

The information in a database can change over time and requires specific support for operations that process the temporal characteristics of the data. New instances of objects present in the database are inserted frequently, requiring management methods capable of handling temporal information. This paper aims to extend the delimitation techniques for visualization of similarity queries of images using estimates of their trajectories. The study of temporal evolution in complex data can benefit several areas of knowledge, such as agriculture, medicine, civil engineering and others. The use of visualization to understand data changes over time improves the knowledge of the distribution of the dataset, enables the recognition of data patterns more quickly and favors the acquisition of new useful information. In this sense, the visualization of queries with trajectory estimation in a three-dimensional space allows to study how the data are organized in the estimated regions. To perform this visual analysis, we use images at different time points of the same object in the database to estimate what an image of that object would look like at a different time.

关键词： visualization Three-dimensional displays data visualization Estimation Fractals Trajectory visual databases

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Characteristics of Palynological Assemblage and Paleoclimate analysis of the Miocene Formation in the Eastern Bohai Bay Basin 8th

Characteristics of Palynological Assemblage and Paleoclimate...

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8th International Field exploration and Development conference, IFEDC 2019

作者： Wang, Shu Yin, Taiju Yangtze University WuhanHubei430100 China

ISBN: (纸本)9789811524844

Through the sporopollen and algal data of 13 wells selected throughout the area, more than 50 generas of plants are found. Angiosperms are abundant and the most common are juglandaceae;gymnosperms are mainly pinaceae, with the common being keteleeria, abies and hemlock;ferns are mostly aquatic ferns, especially magnastriatites;algae are all freshwater algae, including plicatidium, pediastrum and chaetosphaeridium. Detailed analysis of PL7-6-1 well in Bodong low uplift and PL14-3-1 well in Miaoxi Sag shows that the evolution of arborescent stratum in sporopollen composition can be roughly divided into two stages: Early Guantao Formation (sporopollen assemblage zone III, iv) – Coniferous dominated mixed forests, Late Guantao Formation (sporopollen assemblage zone I, II) – Deciduous forests contain many subtropical elements. The composition of under forest is single, mainly herbaceous, shrubs and terrestrial ferns are rare. In the herb, piceaepollenites are developed, the aquatic sporotrapoidites and graminidites are also common. Different plants adapt to different temperatures and humidity. Statistics show that the humid plants of the entire Guantao Formation in the work area are significantly more than the dryophytes, and the philotherm plants are significantly more than the thermophilic plants, which have typical characteristics of subtropical monsoon climate. With the passage of time, the characteristics of subtropical monsoon climate are more and more remarkable. The T/A, H/A, S/A and E-T parameters calculated from tall trees, herbs, tropical elements, ephedra sporopollen and aquatic plants can better describe the climate change among the sample points, which proves that the climate fluctuates frequently during Guantao Formation, and the overall trend of change is consistent with the previous statistical analysis. Generally speaking, the period of Guantao Formation belongs to subtropical monsoon climate, and has the characteristics of numerous lakes and marshes, t

关键词： Lakes

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A visual Interactive Analytics Interface for Complex Event Processing and Machine Learning Processing of Financial Market data

A Visual Interactive Analytics Interface for Complex Event P...

引用

International conference on Information visualisation (iv)

作者： Nhan Nathan Tri Luong Zoran Milosevic Andrew Berry Fethi Rabhi Deontik Brisbane Australia School of Computer Science and Engineering University of New South Wales Sydney Australia

ISBN: (数字)9781728191348

ISBN: (纸本)9781728191355

Applying machine learning techniques over streaming data is notoriously difficult as it involves the interplay of several technologies that need to be judiciously put together by IT experts. This has motivated the need to provide intuitive and easy to use interactive interfaces for financial experts to be able to leverage both Complex Event Processing (CEP) and Machine Learning (ML) technologies. The solution proposed in this paper is based on an open architecture that uses CEP engines as a pre-processing function for downstream ML training and prediction computations. We demonstrate this approach using a few scenarios involving the analysis of financial market data streams.

关键词： Training visualization data visualization Machine learning Computer architecture Engines

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Exploring Time-Series Through Force-Directed Timelines

Exploring Time-Series Through Force-Directed Timelines

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International conference on Information visualisation (iv)

作者： António Cruz Joel P. Arrais Penousal Machado CISUC University of Coimbra Coimbra Portugal

ISBN: (数字)9781728191348

ISBN: (纸本)9781728191355

Temporal datasets are a product of many scientific disciplines and analyzing the events that they describe may help provide valuable insight into their respective research subjects and help move towards solutions to existing problems. Time-series analysis is still an open problem which prompts new solutions, particularly the discovery of patterns across complex temporal networks. visualization has proven to be a valuable tool in the analysis of such datasets, with the emergence of new models such as Time Curves, which distorts timelines to position time points based on their similarity, creating visualizations that highlight behavior patterns. In this paper, we further explore time-series functionally and aesthetically by revising the dynamic Time Curves models in CroP, a visualization tool with coordinated multiple views. Firstly, we propose the additional of new visual elements and interactive functions, coordinated with a network visualization to help discover and understand temporal patterns across complex datasets. Secondly, we visually explore time-series through Time Paths, a parameter-based force-directed layout that can dynamically transform the original model to either highlight small data variations or reduce visual noise in favor of overall patterns.

关键词： visualization Time series analysis Layout Dynamics data visualization Transforms Tools

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iConViz: Interactive visual exploration of the Default Contagion Risk of Networked-Guarantee Loans

iConViz: Interactive Visual Exploration of the Default Conta...

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IEEE Symposium on visual Analytics Science and Technology (VAST)

作者： Zhibin Niu Runlin Li Junqi Wu Dawei Cheng Jiawan Zhang College of Intelligence and Computing Tianjin University Shanghai Jiao Tong University

ISBN: (数字)9781728180090

ISBN: (纸本)9781728180106

Groups of enterprises can serve as guarantees for one another and form complex networks when obtaining loans from commercial banks. During economic slowdowns, corporate default may spread like a virus and lead to large-scale defaults or even systemic financial crises. To help financial regulatory authorities and banks manage the risk associated with networked loans, we identified the default contagion risk, a pivotal issue in developing preventive measures, and established iConViz, an interactive visual analysis tool that facilitates the closed-loop analysis process. A novel financial metric, the contagion effect, was formulated to quantify the infectious consequences of guarantee chains in this type of network. Based on this metric, we designed and implemented a series of novel and coordinated views that address the analysis of financial problems. Experts evaluated the system using real-world financial data. The proposed approach grants practitioners the ability to avoid previous ad hoc analysis methodologies and extend coverage of the conventional Capital Accord to the banking industry.

关键词： data visualization visual analytics Risk management Banking Monitoring Tools Task analysis

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visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations

Visual Analytics for Deep Embeddings of Large Scale Molecula...

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IEEE International conference on Big data (Big data)

作者： Chae, Junghoon Bhowmik, Debsindhu Ma, Heng Ramanathan, Arvind Steed, Chad Oak Ridge Natl Lab Oak Ridge TN 37830 USA Argonne Natl Lab Lemont IL USA

ISBN: (纸本)9781728108582

Molecular Dynamics (MD) simulation have been emerging as an excellent candidate for understanding complex atomic and molecular scale mechanism of bio-molecules that control essential bio-physical phenomenon in a living organism. But this MD technique produces large-size and long-timescale data that are inherently high-dimensional and occupies many terabytes of data. Processing this immense amount of data in a meaningful way is becoming increasingly difficult. Therefore, specific dimensionality reduction algorithm using deep learning technique has been employed here to embed the high-dimensional data in a lower-dimension latent space that still preserves the inherent molecular characteristics i.e. retains biologically meaningful information. Subsequently, the results of the embedding models are visualized for model evaluation and analysis of the extracted underlying features. However, most of the existing visualizations for embeddings have limitations in evaluating the embedding models and understanding the complex simulation data. We propose an interactive visual analytics system for embeddings of MD simulations to not only evaluate and explain an embedding model but also analyze various characteristics of the simulations. Our system enables exploration and discovery of meaningful and semantic embedding results and supports the understanding and evaluation of results by the quantitatively described features of the MD simulations (even without specific labels).

关键词： visual analytics machine learning HCI molecular dynamics

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