NDLI: Proceedings of the Workshop on Human-In-the-Loop Data Analytics (HILDA '16)

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Visual exploration of machine learning results using data cube analysis

Have a chat with clustine, conversational engine to query large tables

Bridging the gap between user intention and model parameters for human-in-the-loop data analytics

Towards a general-purpose query language for visualization recommendation

VisTrees: fast indexes for interactive data exploration

Clustering provenance facilitating provenance exploration through data abstraction

The exception that improves the rule

Interactive online learning for clinical entity recognition

Towards reliable interactive data cleaning: a user survey and recommendations

PFunk-H: approximate query processing using perceptual models

The case for interactive data exploration accelerators (IDEAs)

TrendQuery: a system for interactive exploration of trends

Data programming with DDLite: putting humans in a different part of the loop

ModelDB: a system for machine learning model management

A DeVIL-ish approach to inconsistency in interactive visualizations

Big data exploration requires collaboration between visualization and data infrastructures

Proceedings of the Workshop on Human-In-the-Loop Data Analytics (HILDA '16)

Content Provider	ACM Digital Library
Editor	Fekete, Alan Binnig, Carsten Nandi, Arnab
Copyright Year	2016
Abstract	We are delighted to present the papers from the first HILDA Workshop on Human-in-the-Loop Data Analytics, which took place on 26 June, 2016 co-located with the ACM SIGMOD conference in San Francisco, California, USA. An often overlooked component when designing a data management system is the set of users interacting with it { the human-in-the-loop. A major bottleneck in data analytics today is to efficiently leverage the human capabilities to formulate questions and understand answers of data analytics systems. In the database community the first vision papers towards that direction discussed topics such as interactive data exploration or querying data management systems with more intuitive user interfaces. Recent technology trends (such as touch screens, motion detection, and voice recognition) are widening the possibilities for users to interact with data, and data-driven industries are shifting to personalized processing to better target their services to the users' needs. We created HILDA to broaden the scope of how data analytics can be done with the awareness of people. A major goal of HILDA was to bring together researchers and practitioners from the database community with various other communities such as the HCI community or the Information Visualization community. We sought papers that propose innovations to improve the way people can work with data management systems, and also work that studies how humans work with existing systems. We explicitly asked for submissions that present initial ideas and visions, just as much as reports on early results, or reflections on completed projects.
ISBN	9781450342070
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-06-26
Access Restriction	Subscribed
Content Type	Text
Resource Type	Conference Proceedings

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