Using a knowledge graph data structure to analyze text documents (VAST challenge 2014 MC1)

2014 ◽  
Author(s):  
Florian Stoffel ◽  
Fabian Fischer
Keyword(s):  
Data Structure ◽  
Knowledge Graph ◽  
Text Documents ◽  
Graph Data

scholarly journals From Tabulated Data to Knowledge Graph: A Novel Way of Improving the Performance of the Classification Models in the Healthcare Data

2021 ◽  
Author(s):  
Nazar Zaki ◽  
Elfadil Abdalla Mohamed ◽  
Tetiana Habuza
Keyword(s):  
Machine Learning ◽  
Data Structure ◽  
Data Analysis ◽  
Knowledge Graph ◽  
Classification Models ◽  
Effective Technique ◽  
Graph Data ◽  
Healthcare Data ◽  
Suggested Technique ◽  
Tabulated Data

In sectors like healthcare, having classification models that are both reliable and accurate is vital. Regrettably, contemporary classification techniques employing machine learning disregard the correlations between instances within data. This research, to rectify this, introduces a basic but effective technique for converting tabulated data into data graphs, incorporating structural correlations. Graphs have a unique capacity to capture structural correlations between data, allowing us to gain a deeper insight in comparison to carrying out isolated data analysis. The suggested technique underwent testing once the integration of graph data structure-related elements had been carried out and returned superior results to testing solely employing original features. The suggested technique achieved validity by returning significantly improved levels of accuracy.

scholarly journals Automatically Generating a MEP Logic Chain from Building Information Models with Identification Rules

2019 ◽  
Vol 9 (11) ◽  
pp. 2204 ◽  
Author(s):  
Ya-Qi Xiao ◽  
Sun-Wei Li ◽  
Zhen-Zhong Hu
Keyword(s):  
Data Structure ◽  
Topological Analysis ◽  
Failure Detection ◽  
Facility Management ◽  
Graph Data ◽  
Information Models ◽  
Average Accuracy ◽  
Connection Table ◽  
Building Information ◽  
Building Information Models

In mechanical, electrical, and plumbing (MEP) systems, logic chains refer to the upstream and downstream connections between MEP components. Generating the logic chains of MEP systems can improve the efficiency of facility management (FM) activities, such as locating components and retrieving relevant maintenance information for prompt failure detection or for emergency responses. However, due to the amount of equipment and components in commercial MEP systems, manually creating such logic chains is tedious and fallible work. This paper proposes an approach to generate the logic chains of MEP systems using building information models (BIMs) semi-automatically. The approach consists of three steps: (1) the parametric and nonparametric spatial topological analysis within MEP models to generate a connection table, (2) the transformation of MEP systems and custom information requirements to generate the pre-defined and user-defined identification rules, and (3) the logic chain completion of MEP model based on the graph data structure. The approach was applied to a real-world project, which substantiated that the approach was able to generate logic chains of 15 MEP systems with an average accuracy of over 80%.

scholarly journals Question-led approach in designing Dijkstra algorithm game-based learning: A pilot study

2020 ◽  
Vol 9 (4) ◽  
pp. 926
Author(s):  
Rosni Binti Ramle ◽  
D’oria Islamiah Rosli ◽  
Shelena Soosay Nathan ◽  
Mazniha Berahim
Keyword(s):  
Data Structure ◽  
Pilot Study ◽  
Teaching Tool ◽  
Game Model ◽  
Dijkstra Algorithm ◽  
Game Based Learning ◽  
Learning Context ◽  
Graph Data ◽  
Self Regulated Learning ◽  
Post Test

Dijkstra algorithm is important to be understood because of its many uses. However, understanding it is challenging. Various methods to teach and learn had been researched, with mixed results. The study proposes questionled approach of the algorithm in a game-based learning context. The game designed based on an existing game model, developed and tested by students. Pre- and post-game tests compared and game feedback survey analysed. Results showed that students’ performance in graph data structure Dijkstra algorithm improved after playing the game where post-test mark was higher than pre-test. Game feedback were mostly positive, with areas of improvement. Students may use the game as a learning tool for self-regulated learning. Educators may get some ideas on how to design teaching tool using question-led approach.

From Frequencies to Vectors

2020 ◽  
Author(s):  
Bernhard Rieder
Keyword(s):  
Information Retrieval ◽  
Data Structure ◽  
Sentiment Analysis ◽  
Full Text ◽  
Text Documents ◽  
Document Collections ◽  
Intermediate Data ◽  
Algorithmic Information ◽  
Digital Objects ◽  
Language Meaning

This chapter investigates early attempts in information retrieval to tackle the full text of document collections. Underpinning a large number of contemporary applications, from search to sentiment analysis, the concepts and techniques pioneered by Hans Peter Luhn, Gerard Salton, Karen Spärck Jones, and others involve particular framings of language, meaning, and knowledge. They also introduce some of the fundamental mathematical formalisms and methods running through information ordering, preparing the extension to digital objects other than text documents. The chapter discusses the considerable technical expressivity that comes out of the sprawling landscape of research and experimentation that characterizes the early decades of information retrieval. This includes the emergence of the conceptual construct and intermediate data structure that is fundamental to most algorithmic information ordering: the feature vector.

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