Conference Information

BDSE 2015: International Conference on Big Data Science and Engineering

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Submission Date:
2015-04-20 Extended
Notification Date:
2015-05-31
Conference Date:
2015-08-20
Location:
Helsinki, Finland
Years:
4
Viewed: 18239   Tracked: 1   Attend: 0

Conference Partner Index (CP-I)

41.4 / 100
Ranked #4,744 of 5,687 conferences · Top 84%

#281 of 337 in Data Mining & Databases

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
43
Community attention (10%)
15
Public record completeness (15%)
25

Inputs used: Editions on record: 4 · Researchers following it here: 1 · Researchers who opened this page in the past 24 months: 2

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-25

Call For Papers

BDSE 2015 (International Conference on Big Data Science and Engineering) is an academic conference held in Helsinki, Finland on 2015-08-20. The paper submission deadline is 2015-04-20 (extended). Acceptance notifications are sent on 2015-05-31.

IEEE BDSE is an international forum for presenting and discussing emerging ideas and trends in Big Data from both the research community as well as the industry. Topics of interest include, but are not limited to: Systems, Models and Algorithms - Big Data novel theory, algorithm and applications - Big Data standards - Big Data mining and analytics - Big Data Infrastructure, MapReduce and Cloud Computing - Big Data visualization - Big Data curation and management - Big Data semantics, scientific discovery and intelligence - Big Data performance analysis and large-scale deployment - Security, privacy, trust, and legal issues to big data - Big Data vs Big Business and Big Industry - Large data stream processing on cloud - Large incremental datasets on cloud - Distributed and federated datasets - NoSQL data stores and DB scalability - Big Data placement, scheduling, and optimization - Distributed file systems for Big Data - MapReduce for Big Data processing, resource scheduling and SLA - Performance characterization, evaluation and optimization - Simulation and debugging systems and tools for MapReduce and Big Data - Volume, Velocity, Variety, Value and Veracity of Big Data - Multiple source data processing and integration with MapReduce - Storage and computation management of Big Data - Large-scale big data workflow management - Mobility and big data - Sensor network, social network and big data - Big data applications
Last updated by Dou Sun on

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