SPIRE 2020 : International Symposium on String Processing and Information Retrieval

  in Conferences   Posted on June 5, 2020

Conference Information

Submission Deadline Wednesday 27 May 2020 Proceedings indexed by :
Conference Dates Oct 13, 2020 - Oct 15, 2020
Conference Address Orlando, United States
Conference & Submission Link https://www.cs.ucf.edu/spire2020/
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

G2R Score 0.99
#Contributing Top Scientists 4
#Papers published by Top Scientists 11
Google Scholar H5-index 3
Number of Editions: 27 (Since 1993)
Guide2Research Overall Ranking: 837
Category Rankings
Databases & Information Systems 137
Machine Learning & Artificial Intelligence 186
Proceedings https://link.springer.com/conference/spire
DBLP Page https://dblp.uni-trier.de/db/conf/spire

Conference Call for Papers

All aspects of string processing, information retrieval, computational biology, and related
applications are covered. Typical topics of interest include (but are not limited to):

String Processing: ​ string pattern matching, text indexing, data structures for string processing, text compression, compressed data structures, compressed string processing, text mining, 2D pattern matching, automata based string processing.
Information Retrieval (IR): ​ retrieval models, indexing, evaluation, algorithms and data structures for IR, efficient implementation of IR systems, interface design, text classification and clustering, text analysis and mining, collaborative and content-based filtering, topic modeling for IR, search tasks (Web search, enterprise search, desktop search, legal search, cross-lingual retrieval, federated search, (micro) blog search, XML retrieval, multimedia retrieval), digital libraries.
Computational Biology: high-throughput DNA sequencing (assembly, read alignment, read error correction, metagenomics, transcriptomics, proteomics), evolution and phylogenetics, gene and regulatory element recognition, motif finding, protein structure prediction.

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