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检索条件"主题词=computational notebooks"

共 72 条记录，以下是11-20 订阅

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TunePad Playbooks Designing computational notebooks for Creative Music Coding 22

TunePad Playbooks Designing Computational Notebooks for Crea...

引用

CHI Conference on Human Factors in Computing Systems (CHI)

作者： Horn, Michael S. Banerjee, Amartya Brucker, Matthew P. Northwestern Univ Comp Sci & Learning Sci Evanston IL 60208 USA

ISBN: (纸本)9781450391573

This paper describes the design of an online learning platform that empowers musical creation and performance with Python code. For this platform we have developed an innovative computational notebook paradigm that we call TunePad playbooks. While playbooks borrow ideas from popular computational notebooks like Jupyter, we have designed them from the ground up to support creative musical expression including live performances. After discussing our design principles and features, we share findings from a series of artifact-centered interviews conducted with experienced TunePad users. Our results show how systems like ours might flexibly support a variety of creative workflows, while suggesting opportunities for future work in this area.

关键词： computational literacy computational notebooks music design playbooks

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Managing Messes in computational notebooks 19

Managing Messes in Computational Notebooks

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CHI Conference on Human Factors in Computing Systems (CHI)

作者： Head, Andrew Hohman, Fred Barik, Titus Drucker, Steven M. DeLine, Robert Univ Calif Berkeley Berkeley CA 94720 USA Georgia Inst Technol Atlanta GA 30332 USA Microsoft Redmond WA USA Microsoft Res Redmond WA USA

ISBN: (纸本)9781450359702

Data analysts use computational notebooks to write code for analyzing and visualizing data. notebooks help analysts iteratively write analysis code by letting them interleave code with output, and selectively execute cells. However, as analysis progresses, analysts leave behind old code and outputs, and overwrite important code, producing cluttered and inconsistent notebooks. This paper introduces code gathering tools, extensions to computational notebooks that help analysts find, clean, recover, and compare versions of code in cluttered, inconsistent notebooks. The tools archive all versions of code outputs, allowing analysts to review these versions and recover the subsets of code that produced them. These subsets can serve as succinct summaries of analysis activity or starting points for new analyses. In a qualitative usability study, 12 professional analysts found the tools useful for cleaning notebooks and writing analysis code, and discovered new ways to use them, like generating personal documentation and lightweight versioning.

关键词： computational notebooks messes clutter inconsistency exploratory programming code history program slicing

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Human-Notebook Interactions: The CHI of computational notebooks

Human-Notebook Interactions: The CHI of Computational Notebo...

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ACM CHI Conference on Human Factors in Computing Sytems (CHI)

作者： Harden, Jesse Wang, April Faust, Rebecca Issacs, Katherine E. Kirshenbaum, Nurit Wenskovitch, John Zhao, Jian North, Chris Virginia Tech Blacksburg VA 24061 USA Swiss Fed Inst Technol Zurich Switzerland Univ Utah Salt Lake City UT USA Univ Hawaii Manoa Honolulu HI USA Pacific Northwest Natl Lab Richland WA USA Univ Waterloo Waterloo ON Canada

ISBN: (纸本)9798400703317

The overall goal of this workshop is to bring together researchers from across the CHI community to share their knowledge and build collaborations at the intersection of computational notebook and HCI research, focusing on both the effective design and effective use of interfaces and interactions within computational notebook environments. This includes innovating upon the computational notebook metaphor, designing new tools, interfaces, and interactions for use with computational notebooks, and more. We aim to pull expertise from across all fields of CHI to deliver novel research and generate open discussion about the current state of computational notebooks, how it can be improved from an HCI standpoint, and how these potential improvements can direct future research. To achieve this goal, we propose a full-day, hybrid workshop with discussions of challenges and opportunities, paper and demo presentations, lightning talks, and a keynote. Participants in this workshop will exchange ideas and help define a roadmap for future research at the intersection of HCI and computational notebook design.

关键词： computational notebooks Human-Computer Interaction Interface Design Interaction Design computational Narratives Data Science Data Analysis

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Weedle: Composable Dashboard for Data-Centric NLP in computational notebooks

Weedle: Composable Dashboard for Data-Centric NLP in Computa...

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32nd World Wide Web Conference (WWW)

作者： Kwon, Nahyun Kim, Hannah Rahman, Sajjadur Zhang, Dan Hruschka, Estevam Texas A&M Univ College Stn TX 77834 USA Megagon Labs Mountain View CA USA

ISBN: (纸本)9781450394161

Data-centric NLP is a highly iterative process requiring careful exploration of text data throughout entire model development life-cycle. Unfortunately, existing data exploration tools are not suitable to support data-centric NLP because of workfow discontinuity and lack of support for unstructured text. In response, we propose Weedle, a seamless and customizable exploratory text analysis system for data-centric NLP. Weedle is equipped with built-in text transformation operations and a suite of visual analysis features. With its widget, users can compose customizable dashboards interactively and programmatically in computational notebooks.

关键词： exploratory data analysis computational notebooks

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Beyond Syntax: Unleashing the Power of computational notebooks Code Metrics in Documentation Generation 24

Beyond Syntax: Unleashing the Power of Computational Noteboo...

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IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI (CAIN)

作者： Ghahfarokhi, Mojtaba Mostafavi Khademian, Ashkan Kianiangolafshani, Sepehr Asadi, Alireza Jahantigh, Hamed Heydarnoori, Abbas Sharif Univ Technol Dept Comp Engn Tehran Iran Bowling Green State Univ Dept Comp Sci Bowling Green OH USA

ISBN: (纸本)9798400705915

computational notebooks, like Kaggle notebooks, offer an integrated platform for coding and documentation, yet the latter's quality often falls short as scientists may neglect this crucial aspect. This paper addresses the need for improved and efficient code documentation generation in computational notebooks. As recent literature emphasizes integrating code's inherent structure into documentation generation models, our research explores unutilized structural characteristics, incorporating metrics from code sequences to enable better code documentation suggestions. Evidenced by the improved BLEU scores, our proposed method significantly outperforms the conventional model in a preliminary 10-fold cross-validation experiment and further provides a flexible foundation for integrating source code metrics into diverse code documentation generation models.

关键词： Code Metrics computational notebooks Markdown Generation

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NBSearch: Semantic Search and Visual Exploration of computational notebooks 21

NBSearch: Semantic Search and Visual Exploration of Computat...

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CHI Conference on Human Factors in Computing Systems

作者： Li, Xingjun Wang, Yuanxin Wang, Hong Wang, Yang Zhao, Jian Univ Waterloo Waterloo ON Canada Uber Technol San Francisco CA USA

ISBN: (纸本)9781450380966

Code search is an important and frequent activity for developers using computational notebooks (e.g., Jupyter). The fexibility of notebooks brings challenges for efective code search, where classic search interfaces for traditional software code may be limited. In this paper, we propose, NBSearch, a novel system that supports semantic code search in notebook collections and interactive visual exploration of search results. NBSearch leverages advanced machine learning models to enable natural language search queries and intuitive visualizations to present complicated intra- and inter-notebook relationships in the returned results. We developed NBSearch through an iterative participatory design process with two experts from a large software company. We evaluated the models with a series of experiments and the whole system with a controlled user study. The results indicate the feasibility of our analytical pipeline and the efectiveness of NBSearch to support code search in large notebook collections.

关键词： Semantic code search search result visualization computational notebooks document and text analysis

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mage: Fluid Moves Between Code and Graphical Work in computational notebooks 20

mage: Fluid Moves Between Code and Graphical Work in Computa...

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33rd Annual ACM Symposium on User Interface Software and Technology (UIST)

作者： Kery, Mary Beth Ren, Donghao Hohman, Fred Moritz, Dominik Wongsuphasawat, Kanit Patel, Kayur Carnegie Mellon Univ Pittsburgh PA 15213 USA Apple Inc Cupertino CA 95014 USA Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781450375146

We aim to increase the fexibility at which a data worker can choose the right tool for the job, regardless of whether the tool is a code library or an interactive graphical user interface (GUI). To achieve this fexibility, we extend computational notebooks with a new API mage, which supports tools that can represent themselves as both code and GUI as needed. We discuss the design of mage as well as design opportunities in the space of fexible code/GUI tools for data work. To understand tooling needs, we conduct a study with nine professional practitioners and elicit their feedback on mage and potential areas for fexible code/GUI tooling. We then implement six client tools for mage that illustrate the main themes of our study fndings. Finally, we discuss open challenges in providing fexible code/GUI interactions for data workers.

关键词： Data Science Programming Machine Learning Programming Handoff computational notebooks

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Notable: On-the-fly Assistant for Data Storytelling in computational notebooks 23

Notable: On-the-fly Assistant for Data Storytelling in Compu...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Li, Haotian Ying, Lu Zhang, Haidong Wu, Yingcai Qu, Huamin Wang, Yun Hong Kong Univ Sci & Technol Hong Kong Peoples R China Microsoft Res Asia Beijing Peoples R China Zhejiang Univ Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781450394215

computational notebooks are widely used for data analysis. Their interleaved displays of code and execution results (e.g., visualizations) are welcomed since they enable iterative analysis and preserve the exploration process. However, the communication of data fndings remains challenging in computational notebooks. Users have to carefully identify useful fndings from useless ones, document them with texts and visual embellishments, and then organize them in diferent tools. Such workfow greatly increases their workload, according to our interviews with practitioners. To address the challenge, we designed Notable to offer on-the-fy assistance for data storytelling in computational notebooks. It provides intelligent support to minimize the work of documenting and organizing data fndings and diminishes the cost of switching between data exploration and storytelling. To evaluate Notable, we conducted a user study with 12 data workers. The feedback from user study participants verifes its efectiveness and usability.

关键词： data visualization data storytelling computational notebooks

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Assessing the Quality of computational notebooks for a Frictionless Transition from Exploration to Production 22

Assessing the Quality of Computational Notebooks for a Frict...

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44th ACM/IEEE International Conference on Software Engineering - New Ideas and Emerging Results (ICSE-NIER)

作者： Quaranta, Luigi Univ Bari Bari Italy

ISBN: (纸本)9781665495981

The massive trend of integrating data-driven AI capabilities into traditional software systems is rising new intriguing challenges. One of such challenges is achieving a smooth transition from the explorative phase of Machine Learning projects - in which data scientists build prototypical models in the lab - to their production phase in which software engineers translate prototypes into production-ready AI components. To narrow down the gap between these two phases, tools and practices adopted by data scientists might be improved by incorporating consolidated software engineering solutions. In particular, computational notebooks have a prominent role in determining the quality of data science prototypes. In my research project, I address this challenge by studying the best practices for collaboration with computational notebooks and proposing proof-of-concept tools to foster guidelines compliance.

关键词： Software Engineering Artificial Intelligence Data Science Machine Learning computational notebooks static analysis tools linters

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B2: Bridging Code and Interactive Visualization in computational notebooks 20

B2: Bridging Code and Interactive Visualization in Computati...

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33rd Annual ACM Symposium on User Interface Software and Technology (UIST)

作者： Wu, Yifan Hellerstein, Joseph M. Satyanarayan, Arvind Univ Calif Berkeley Berkeley CA 94720 USA MIT CSAIL Cambridge MA 02139 USA

ISBN: (纸本)9781450375146

Data scientists have embraced computational notebooks to author analysis code and accompanying visualizations within a single document. Currently, although these media may be interleaved, they remain siloed: interactive visualizations must be manually specified as they are divorced from the analysis provenance expressed via dataframes, while code cells have no access to users' interactions with visualizations, and hence no way to operate on the results of interaction. To bridge this divide, we present B2, a set of techniques grounded in treating data queries as a shared representation between the code and interactive visualizations. B2 instruments data frames to track the queries expressed in code and synthesize corresponding visualizations. These visualizations are displayed in a dashboard to facilitate interactive analysis. When an interaction occurs, B2 reifies it as a data query and generates a history log in a new code cell. Subsequent cells can use this log to further analyze interaction results and, when marked as reactive, to ensure that code is automatically recomputed when new interaction occurs. In an evaluative study with data scientists, we find that B2 promotes a tighter feedback loop between coding and interacting with visualizations. All participants frequently moved from code to visualization and vice-versa, which facilitated their exploratory data analysis in the notebook.

关键词： Data science computational notebooks exploratory programming interactive visualizations

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