Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXVIII: Special Issue on Database- and Expert-Systems Applications

Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXVIII: Special Issue on Database- and Expert-Systems Applications

ISBN-10:
3662583836
ISBN-13:
9783662583838
Pub. Date:
11/22/2018
Publisher:
Springer Berlin Heidelberg
ISBN-10:
3662583836
ISBN-13:
9783662583838
Pub. Date:
11/22/2018
Publisher:
Springer Berlin Heidelberg
Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXVIII: Special Issue on Database- and Expert-Systems Applications

Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXVIII: Special Issue on Database- and Expert-Systems Applications

$54.99
Current price is , Original price is $54.99. You
$54.99 
  • SHIP THIS ITEM
    In stock. Ships in 1-2 days.
  • PICK UP IN STORE

    Your local store may have stock of this item.


Overview

This, the 38th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of six papers selected from the 68 contributions presented at the 27th International Conference on Database and Expert Systems Applications, DEXA 2016, held in Porto, Portugal, in September 2016. Topics covered include query personalization in databases, data anonymization, similarity search, computational methods for entity resolution, array-based computations in big data analysis, and pattern mining.

Product Details

ISBN-13: 9783662583838
Publisher: Springer Berlin Heidelberg
Publication date: 11/22/2018
Series: Lecture Notes in Computer Science , #11250
Edition description: 1st ed. 2018
Pages: 173
Product dimensions: 6.10(w) x 9.25(h) x (d)

Table of Contents

Bound-and-Filter Framework for Aggregate Reverse Rank Queries.- Syntactic Anonymisation of Shared Datasets in Resource Constrained Environments.- Towards Faster Similarity Search by Dynamic Reordering of Streamed Queries.- SjClust: A Framework for Incorporating Clustering into Set Similarity Join Algorithms.- A Query Processing Framework for Large-Scale Scientific Data Analysis.- Discovering Periodic-Correlated Patterns in Temporal Databases.

From the B&N Reads Blog

Customer Reviews