Ringo: Interactive Graph Analytics on Big-Memory Machines

We present Ringo, a system for analysis of large graphs. Graphs provide a way to represent and analyze systems of interacting objects (people, proteins, webpages) with edges between the objects denoting interactions (friendships, physical interactions, links). Mining graphs provides valuable insights about individual objects as well as the relationships among them. In building Ringo, we take advantage of the fact that machines with large memory and many cores are widely available and also relatively affordable. This allows us to build an easy-to-use interactive high-performance graph analytics system. Graphs also need to be built from input data, which often resides in the form of relational tables. Thus, Ringo provides rich functionality for manipulating raw input data tables into various kinds of graphs. Furthermore, Ringo also provides over 200 graph analytics functions that can then be applied to constructed graphs. We show that a single big-memory machine provides a very attractive platform for performing analytics on all but the largest graphs as it offers excellent performance and ease of use as compared to alternative approaches. With Ringo, we also demonstrate how to integrate graph analytics with an iterative process of trial-and-error data exploration and rapid experimentation, common in data mining workloads.Comment: 6 pages, 2 figure

Using resource graphs to represent conceptual change

We introduce resource graphs, a representation of linked ideas used when reasoning about specific contexts in physics. Our model is consistent with previous descriptions of resources and coordination classes. It can represent mesoscopic scales that are neither knowledge-in-pieces or large-scale concepts. We use resource graphs to describe several forms of conceptual change: incremental, cascade, wholesale, and dual construction. For each, we give evidence from the physics education research literature to show examples of each form of conceptual change. Where possible, we compare our representation to models used by other researchers. Building on our representation, we introduce a new form of conceptual change, differentiation, and suggest several experimental studies that would help understand the differences between reform-based curricula.Comment: 27 pages, 14 figures, no tables. Submitted for publication to the Physical Review Special Topics Physics Education Research on March 8, 200

Training Neural Language Models with SPARQL queries for Semi-Automatic Semantic Mapping

Abstract Knowledge graphs are labeled and directed multi-graphs that encode information in the form of entities and relationships. They are gaining attention in different areas of computer science: from the improvement of search engines to the development of virtual personal assistants. Currently, an open challenge in building large-scale knowledge graphs from structured data available on the Web (HTML tables, CSVs, JSONs) is the semantic integration of heterogeneous data sources. In fact, such diverse and scattered information rarely provide a formal description of metadata that is required to accomplish the integration task. In this paper we propose an approach based on neural networks to reconstruct the semantics of data sources to produce high quality knowledge graphs in terms of semantic accuracy. We developed a neural language model trained on a set of SPARQL queries performed on knowledge graphs. Through this model it is possible to semi-automatically generate a semantic map between the attributes of a data source and a domain ontology

Model Ranges Analysis of Excavators more than 20 tons

Cílem této bakalářské práce je vypracovat přehled současného stavu stavebních mobilních strojů - rypadel. Rozbor bude zahrnovat technické a provozní parametry rypadel nad 20 tun hmotnosti od tuzemských a zahraničních výrobců. Jednotlivá rypadla budou rozdělena do hmotnostních kategorií, kde budou porovnávány jednotlivé parametry, ze kterých se zhotoví tabulky a grafy.The aim of this study is to work out the summary of present building mobile machines – excavators. The analysis contains technical and operating parameters of over 20 tons heavy excavater from home and foreign manufactures. Excavators are dividet into groups according to their weight. In each group there are compared qualities of the machines and then tables and graphs will be created.

THE IMPROVEMENT OF STUDENT ACHIEVEMENT LEARNING SMK N 3 YOGYAKARTA OF BUILDING SKILLS BEFORE AND AFTER THE IMPLEMENTATION OF TEACHER CERTIFICATION (ACADEMIC YEAR 2005-2010)

This study aims at understanding the development of student achievement SMK N 3 Yogyakarta area of building expertise before and after the certification of teachers of the school year 2005-2010. Specifically, this study also seeks to identify the developmental competency of teachers in building expertise SMK N 3 Yogyakarta along with the implementation of the teacher certification program organized government. This study is a quantitative descriptive research. In this study sample will be deducted from the student of SMK N 3 Yogyakarta areas of building expertise in the academic year 2005-2010. Data collection was using documentation in the form of a data value rapport/results student school year 2005-2010. Analysis of the development of student achievement in terms of learning outcomes in one eye training, learning on the combined results of training the eye, and in terms of teacher certification passing score. Data analysis techniques were using quantitative descriptive analysis of the figures presented in the form of tables, graphs and pie charts. The results (1) in terms of one eye on the teacher's training certification, in 2005 (6.539), 2006 (7.136), 2007 (7.528), 2008 (7.318), 2009 (7.328), 2010 (7.217). In the teacher has not been certified, in 2005 (6.886), 2006 (6.774), 2007 (7.202), 2008 (7.162), 2009 (7.364), 2010 (7.143). (2) in terms of combined eye on the teacher's training certification, in 2005 (6.783), 2006 (7.002), 2007 (7.401), 2008 (7.332), 2009 (7.656), 2010 (7.211). In the teacher has not been certified, in 2005 (6.586), 2006 (6.868), 2007 (7.202), 2008 (7.216), 2009 (7.306), 2010 (7.107). (3) in terms of graduation teacher certification, graduation interval 650- 799 (7.299), 800-949 (7.180), 950-1099 (7.524), 1100-1249 (7218). Key words: learning achievement, certified teacher