Download Database and Expert Systems Applications: 27th International by Sven Hartmann, Hui Ma PDF

By Sven Hartmann, Hui Ma

This quantity set LNCS 9827 and LNCS 9828 constitutes the refereed lawsuits of the twenty seventh foreign convention on Database and professional platforms purposes, DEXA 2016, held in Porto, Portugal, September 2016.

The 39 revised complete papers provided including 29 brief papers have been conscientiously reviewed and chosen from 137 submissions. The papers speak about quite a number issues together with: Temporal, Spatial, and excessive Dimensional Databases; facts Mining; Authenticity, privateness, defense, and belief; information Clustering; dispensed and large facts Processing; choice help platforms, and studying; info Streams; information Integration, and Interoperability; Semantic internet, and information Semantics; Social Networks, and community research; associated facts; info research; NoSQL, NewSQL; Multimedia info; own info administration; Semantic net and Ontologies; Database and knowledge procedure Architectures; question Answering and Optimization; info Retrieval, and key-phrase seek; information Modelling, and Uncertainty.

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Additional resources for Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part I

Example text

We observe that all the CPs with same maxRS value k collectively form a skyline, which we call k-line. There are n number of k-lines, and they divide the maxRS matrix into n separate regions, as demonstrated as shaded regions of different colors in Fig. 1(c). Our new index just stores these n k-lines (each is organized as a list of CPs sorted on the x-axis). This gives us an index of size O(n · λ), where λ is the maximum size of any k-line. Lemma 2. λ is at most O(n2 ). The proof is based on the observation that each CP in Lk has distinct x(or y) intervals, and the size of A and B are bounded by O(n2 ).

Syntax of temporal keyword query in BNF ::= { : } ::= ::= | | , | , | ::= | , ::= | ::= |

In: ACM SIGMOD (2008) 15. : SPARK: top-k keyword query in relational databases. In: ACM SIGMOD (2007) 16. : Supporting temporal queries on XML keyword search engines. J. Inf. Data Manag. 1(3), 471 (2010) ¨ 17. : Temporal and real-time databases: a survey. IEEE Trans. Knowl. Data Eng. 7(4), 513–532 (1995) 18. : SQAK: doing more with keywords. In: ACM SIGMOD (2008) 19. : ExpressQ: identifying keyword context and search target in relational keyword queries. hk Abstract. The Maximizing Range Sum problem is widely applied in facility locating, spatial data mining, and clustering problems.

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