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ExploreDB'17: Proceedings of the ExploreDB'17
ACM2017 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
SIGMOD/PODS'17: International Conference on Management of Data Chicago IL USA May 14 - 19, 2017
ISBN:
978-1-4503-4674-0
Published:
14 May 2017
Sponsors:
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Abstract

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short-paper
Enabling Change Exploration: Vision Paper
Article No.: 1, Pages 1–3https://doi.org/10.1145/3077331.3077340

Data and metadata suffer many different kinds of change: values are inserted, deleted or updated; entities appear and disappear; properties are added or re-purposed, etc. Explicitly recognizing, exploring, and evaluating such change can alert to changes ...

research-article
Interactive Exploration of Correlated Time Series
Article No.: 2, Pages 1–6https://doi.org/10.1145/3077331.3077335

The rapid growth of monitoring applications has led to unprecedented amounts of generated time series data. Data analysts typically explore such large volumes of time series data looking for valuable insights. One such insight is finding pairs of time ...

research-article
Integration and Exploration of Connected Personal Digital Traces
Article No.: 3, Pages 1–6https://doi.org/10.1145/3077331.3077337

A large number of personal digital traces is constantly generated or available online from a variety of sources, such as social media, calendars, purchase history, etc. These personal data traces are fragmented and highly heterogeneous, raising the need ...

research-article
On Achieving Diversity in Recommender Systems
Article No.: 4, Pages 1–6https://doi.org/10.1145/3077331.3077341

Throughout our digital lives, we are getting recommendations for about almost everything we do, buy or consume. In that way, the field of recommender systems has been evolving vastly to match the increasing user needs accordingly. News, products, ideas ...

research-article
Structural Query Expansion via motifs from Wikipedia
Article No.: 5, Pages 1–6https://doi.org/10.1145/3077331.3077342

The search for relevant information can be very frustrating for users who, unintentionally, use inappropriate keywords to express their needs. Expansion techniques aim at transforming the users' queries by adding new terms, called expansion features, ...

research-article
Public Access
Supporting Dynamic Quantization for High-Dimensional Data Analytics
Article No.: 6, Pages 1–6https://doi.org/10.1145/3077331.3077336

Similarity searches are at the heart of exploratory data analysis tasks. Distance metrics are typically used to characterize the similarity between data objects represented as feature vectors. However, when the dimensionality of the data increases and ...

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Acceptance Rates

Overall Acceptance Rate 11 of 21 submissions, 52%
YearSubmittedAcceptedRate
ExploreDB '1611545%
ExploreDB '1510660%
Overall211152%