By Stanislaw Kozielski, Dariusz Mrozek, Pawel Kasprowski, Bożena Malysiak-Mrozek, Daniel Kostrzewa

This publication constitutes the refereed lawsuits of the tenth IEEE foreign convention past Databases, Architectures, and constructions, BDAS 2014, held in Ustron, Poland, in may well 2014. This e-book comprises fifty six rigorously revised chosen papers which are assigned to eleven thematic teams: question languages, transactions and question optimization; facts warehousing and massive info; ontologies and semantic net; computational intelligence and information mining; collective intelligence, scheduling, and parallel processing; bioinformatics and organic facts research; picture research and multimedia mining; safety of database structures; spatial information research; purposes of database structures; internet and XML in database systems.

Show description

Read Online or Download Beyond Databases, Architectures, and Structures: 10th International Conference, BDAS 2014, Ustron, Poland, May 27-30, 2014. Proceedings PDF

Similar data mining books

Knowledge-Based Intelligent Information and Engineering Systems: 11th International Conference, KES 2007, Vietri sul Mare, Italy, September 12-14,

The 3 quantity set LNAI 4692, LNAI 4693, and LNAI 4694, represent the refereed court cases of the eleventh foreign convention on Knowledge-Based clever details and Engineering structures, KES 2007, held in Vietri sul Mare, Italy, September 12-14, 2007. The 409 revised papers provided have been conscientiously reviewed and chosen from approximately 1203 submissions.

Multimedia Data Mining and Analytics: Disruptive Innovation

This booklet presents clean insights into the innovative of multimedia facts mining, reflecting how the learn concentration has shifted in the direction of networked social groups, cellular units and sensors. The paintings describes how the background of multimedia information processing might be seen as a chain of disruptive recommendations.

What stays in Vegas: the world of personal data—lifeblood of big business—and the end of privacy as we know it

The best possibility to privateness this day isn't the NSA, yet good-old American businesses. web giants, prime shops, and different organizations are voraciously accumulating facts with little oversight from anyone.
In Las Vegas, no corporation is aware the price of information higher than Caesars leisure. Many hundreds of thousands of enthusiastic consumers pour throughout the ever-open doorways in their casinos. the key to the company’s good fortune lies of their one unequalled asset: they comprehend their consumers in detail by way of monitoring the actions of the overpowering majority of gamblers. They be aware of precisely what video games they prefer to play, what meals they take pleasure in for breakfast, after they wish to stopover at, who their favourite hostess may be, and precisely the right way to hold them coming again for more.
Caesars’ dogged data-gathering equipment were such a success that they have got grown to turn into the world’s biggest on line casino operator, and feature encouraged businesses of every kind to ramp up their very own facts mining within the hopes of boosting their distinctive advertising efforts. a few do that themselves. a few depend upon info agents. Others truly input an ethical grey sector that are meant to make American shoppers deeply uncomfortable.
We stay in an age whilst our own details is harvested and aggregated no matter if we adore it or now not. And it really is turning out to be ever tougher for these companies that opt for to not have interaction in additional intrusive info collecting to compete with those who do. Tanner’s well timed caution resounds: convinced, there are lots of merits to the unfastened movement of all this knowledge, yet there's a darkish, unregulated, and harmful netherworld in addition.

Machine Learning in Medical Imaging: 7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings

This publication constitutes the refereed court cases of the seventh overseas Workshop on laptop studying in clinical Imaging, MLMI 2016, held along side MICCAI 2016, in Athens, Greece, in October 2016. The 38 complete papers offered during this quantity have been rigorously reviewed and chosen from 60 submissions.

Additional info for Beyond Databases, Architectures, and Structures: 10th International Conference, BDAS 2014, Ustron, Poland, May 27-30, 2014. Proceedings

Sample text

If the GROUP node has no children, remove it. Replace columns and aggregates that are members of the metagranule with columns from the table that stores the aggregated data of the metagranule. 6. Remove tables from the FROM node that are no longer referenced. 7. Add the table that stores the data of the metagranule to the FROM node. 6 Performance We used a computer with Intel i5 3570 (ivy bridge) and 8GiB RAM. The storage was Raid 0 over 4xBlack Caviar 1TB controlled by Adaptec 2405. 10. 1. We tested against three database instances: small (base data of size 34 GiB), medium (130 GiB) and big (345 GiB).

For the sake of readability we present them in SQL, since there can be interested readers who are not familiar with HQL. 4. A query for five the best invoices on a given day SELECT name , SUM( qty ∗ p r i c e ) AS s u m q t y x p r i c e FROM i n v l i n e JOIN i n v USING ( i n v i d ) JOIN c u s t USING ( c i d ) WHERE date = ’ 2 0 1 3 . 1 1 . 5. The optimized query for five the best invoices on a given day SELECT date , name , s u m q t y x p r i c e FROM mg inv JOIN c u s t USING ( c i d ) WHERE date = ’ 2 0 1 3 .

Fig. 2. DTP architecture overview 24 4 M. Iwaniak and W. Khadzhynov CPN Model of DTP Environment with Single AP To create our CPN model we have used PIPE modeling tool. Strong sides of PIPE are its constant developed, intuitive model creation and animation mode in which we can fire enabled transitions and observe marking changes. Most of analysis and simulation modules of PIPE works only for Ordinary Petri Nets with one color define and are useless for CPN analysis. Fig. 3 presents our base CPN model and its places are described by Tab.

Download PDF sample

Rated 4.75 of 5 – based on 7 votes