By Marta Indulska, Sandeep Purao

This e-book constitutes the refereed court cases of workshops, held on the thirty third overseas convention on Conceptual Modeling, ER 2014, in Atlanta, GA, united states in October 2014. The 24 revised complete and six brief papers have been rigorously reviewed and chosen out of fifty nine submissions and are offered including four demonstrations. The papers are equipped in sections on the topic of the person workshops: the 1st foreign Workshop on firm Modeling, ENMO 2014; the second one foreign Workshop on Modeling and administration of huge information, MoBiD 2014; the 1st foreign Workshop on Conceptual Modeling in standards and enterprise research, MReBA 2014; the 1st overseas Workshop on caliber of versions and versions of caliber, QMMQ 2014; the eighth foreign Workshop on Semantic and Conceptual matters in GIS, SeCoGIS 2014; and the eleventh overseas Workshop on internet details platforms Modeling, WISM 2014. The contributions hide a number of subject matters in conceptual modeling, together with necessities and firm modeling, modeling of massive info, spatial conceptual modeling, exploring the standard of types, and concerns particular to the layout of net info systems.

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Extra info for Advances in Conceptual Modeling: ER 2014 Workshops, ENMO, MoBiD, MReBA, QMMQ, SeCoGIS, WISM, and ER Demos, Atlanta, GA, USA, October 27-29, 2014. Proceedings

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2 Related Work Large-scale graphs are commonly encountered in a number of industries and academic areas such as web service, social communication, and bioinformatics among others. These graphs are processed in parallel on multi-core processor based cluster computing systems using data-intensive parallel programming models such as Hadoop [12], Pregel [13], M3R [14], to name a few. These models are based on partitioned parallelism and split data in a set of partitions, each of which is allocated on a node of a A Semi-clustering Scheme for High Performance PageRank on Hadoop 37 cluster.

The cost of finding connected components is extremely high, even if each connected component is small enough to be stored in one single node. Therefore, data partitioning scheme according to connected components is not effective for improving the performance of PageRank computation on Hadoop. To solve these problems, we propose a semi-clustering scheme for improving the performance of PageRank on Hadoop. Outline of the scheme is as follows: i) A group of reachable vertices from a vertex is assigned to a single data partition to reduce the cost of data exchange among nodes.

Our motivation to evaluate eUFO in this paper and not UFO comes from the fact that eUFO is a simplified version and therefore is less complicated. It is also based upon an ontological view of endurants and also contains perdurants. This makes eUFO more practical for comparing it to another ontology than UFO. 2 BORO BORO is a reference ontology that uses object semantics with the goal of developing models that are functionally rich and structurally simple [11]. Object semantics can be explained as objects where time is treated as another dimension, making it easier to capture change patterns.

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