scholarly journals Summary and Evaluation of the Application of Knowledge Graphs in Education 2007–2020

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yanmei Mao
Keyword(s):  
Research Tool ◽  
Knowledge Graph ◽  
Time Zone ◽  
Relevant Research ◽  
The Past ◽  
Visualization Software ◽  
Data Source ◽  
Knowledge Graphs ◽  
Social Sciences Citation Index ◽  
Author Cocitation

Since 2007, knowledge graphs, an important research tool, have been applied to education and many other disciplines. This paper firstly overviews the application of knowledge graphs in education and then samples the knowledge graph applications in CSSCI- (Chinese Social Sciences Citation Index-) indexed journals in the past two years. These samples were classified and analyzed in terms of research institute, data source, visualization software, and analysis perspective. Next, the situation of knowledge graph applications in education was summarized and evaluated in detail. Furthermore, the authors discussed and assessed the normalization of knowledge graph applications in education. The results show that in the past 15 years, knowledge graphs have been widely used in education. The academia has reached a consensus on the paradigm of the research tool: examining the hotspots, topics, and trends in the related fields from the angles of keyword cooccurrence network (KCN), time zone map, clustering network, and literature/author cocitation, with the aid of CiteSpace and other visualization software and text analysis. However, there is not yet a thorough understanding of the limitations of the visualization software. The relevant research should be improved in terms of scientific level, normalization level, and quality.

scholarly journals Predicting the relationships between gut microbiota and mental disorders with knowledge graphs

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Ting Liu ◽  
Xueli Pan ◽  
Xu Wang ◽  
K. Anton Feenstra ◽  
Jaap Heringa ◽  
...  
Keyword(s):  
Mental Disorders ◽  
Gut Microbiota ◽  
Research Effort ◽  
Sparql Query ◽  
Knowledge Graph ◽  
Test Cases ◽  
Relevant Research ◽  
Structured Knowledge ◽  
Knowledge Graphs ◽  
The Relationship

AbstractGut microbiota produce and modulate the production of neurotransmitters which have been implicated in mental disorders. Neurotransmitters may act as ‘matchmaker’ between gut microbiota imbalance and mental disorders. Most of the relevant research effort goes into the relationship between gut microbiota and neurotransmitters and the other between neurotransmitters and mental disorders, while few studies collect and analyze the dispersed research results in systematic ways. We therefore gather the dispersed results that in the existing studies into a structured knowledge base for identifying and predicting the potential relationships between gut microbiota and mental disorders. In this study, we propose to construct a gut microbiota knowledge graph for mental disorder, which named as MiKG4MD. It is extendable by linking to future ontologies by just adding new relationships between existing information and new entities. This extendibility is emphasized for the integration with existing popular ontologies/terminologies, e.g. UMLS, MeSH, and KEGG. We demonstrate the performance of MiKG4MD with three SPARQL query test cases. Results show that the MiKG4MD knowledge graph is an effective method to predict the relationships between gut microbiota and mental disorders.

scholarly journals Biological Insights Knowledge Graph: an integrated knowledge graph to support drug development

2021 ◽  
Author(s):  
David Geleta ◽  
Andriy Nikolov ◽  
Gavin Edwards ◽  
Anna Gogleva ◽  
Richard Jackson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Drug Development ◽  
Use Cases ◽  
Knowledge Graph ◽  
Multiple Use ◽  
Organisational Knowledge ◽  
Data Source ◽  
The Common ◽  
Knowledge Graphs ◽  
Use Of Knowledge

The use of knowledge graphs as a data source for machine learning methods to solve complex problems in life sciences has rapidly become popular in recent years. Our Biological Insights Knowledge Graph (BIKG) combines relevant data for drug development from public as well as internal data sources to provide insights for a range of tasks: from identifying new targets to repurposing existing drugs. Besides the common requirements to organisational knowledge graphs such as being able to capture the domain precisely and give the users the ability to search and query the data, the focus on handling multiple use cases and supporting use case-specific machine learning models presents additional challenges: the data models must also be streamlined for the performance of downstream tasks; graph content must be easily customisable for different use cases; different projections of the graph content are required to support a wider range of different consumption modes. In this paper we describe our main design choices in implementation of the BIKG graph and discuss different aspects of its life cycle: from graph construction to exploitation.

On the Symbolism of Rain in A Farewell to Arms

2018 ◽  
Keyword(s):  
Research Tool ◽  
The Past ◽  
The World ◽  
Farewell To Arms

This paper critically analyzes the symbolic use of rain in A Farewell to Arms (1929). The researcher has applied the Sapir-Whorf Hypothesis as a research tool for the analysis of the text. This hypothesis argues that the languages spoken by a person determine how one observes this world and that the peculiarities encoded in each language are all different from one another. It affirms that speakers of different languages reflect the world in pretty different ways. Hemingway’s symbolic use of rain in A Farewell to Arms (1929) is denotative, connotative, and ironical. The narrator and protagonist, Frederick Henry symbolically embodies his own perceptions about the world around him. He time and again talks about rain when something embarrassing is about to ensue like disease, injury, arrest, retreat, defeat, escape, and even death. Secondly, Hemingway has connotatively used rain as a cleansing agent for washing the past memories out of his mind. Finally, the author has ironically used rain as a symbol when Henry insists on his love with Catherine Barkley while the latter being afraid of the rain finds herself dead in it.

Mobile Software Assurance Informed through Knowledge Graph Construction: The OWASP Threat of Insecure Data Storage

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Suzanna Schmeelk ◽  
Lixin Tao
Keyword(s):  
Data Storage ◽  
Program Analysis ◽  
Web Application ◽  
Security Analysis ◽  
Knowledge Graph ◽  
Healthcare Applications ◽  
Sensitive Data ◽  
Knowledge Graphs ◽  
Mobile Malware Detection ◽  
Software Assurance

Many organizations, to save costs, are movinheg to t Bring Your Own Mobile Device (BYOD) model and adopting applications built by third-parties at an unprecedented rate.  Our research examines software assurance methodologies specifically focusing on security analysis coverage of the program analysis for mobile malware detection, mitigation, and prevention.  This research focuses on secure software development of Android applications by developing knowledge graphs for threats reported by the Open Web Application Security Project (OWASP).  OWASP maintains lists of the top ten security threats to web and mobile applications.  We develop knowledge graphs based on the two most recent top ten threat years and show how the knowledge graph relationships can be discovered in mobile application source code.  We analyze 200+ healthcare applications from GitHub to gain an understanding of their software assurance of their developed software for one of the OWASP top ten moble threats, the threat of “Insecure Data Storage.”  We find that many of the applications are storing personally identifying information (PII) in potentially vulnerable places leaving users exposed to higher risks for the loss of their sensitive data.

Parent–Child Construction of Personal Memories in Reminiscing Conversations: Implications for the Development and Treatment of Childhood Psychopathology

2018 ◽  
Author(s):  
Karen Salmon
Keyword(s):  
Autobiographical Memory ◽  
Conduct Problems ◽  
Childhood Psychopathology ◽  
Relevant Research ◽  
The Past ◽  
Parents And Children ◽  
Emotion Competence ◽  
Critical Skills ◽  
Clinical Populations ◽  
Parent Child

Strong theory and research implicates parent–child conversations about the past in the child’s development of critical skills, including autobiographical memory and understanding of emotion and minds. Yet very little research has focused on associations between reminiscing and the development of childhood psychopathology. This chapter considers what is known about reminiscing between parents and children where there is anxiety or conduct problems. These findings provide clues as to how children come to manifest difficulties in autobiographical memory and emotion competence. Thereafter, the text reviews studies that have attempted to alter the style and content of parent–child reminiscing in clinical populations. The full implications of parent–child reminiscing, as a rich context for children’s development, have yet to be realized in clinically relevant research.

scholarly journals TransET: Knowledge Graph Embedding with Entity Types

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1407
Author(s):  
Peng Wang ◽  
Jing Zhou ◽  
Yuzhang Liu ◽  
Xingchen Zhou
Keyword(s):  
Link Prediction ◽  
State Of The Art ◽  
Score Function ◽  
Graph Embedding ◽  
Vector Spaces ◽  
Knowledge Graph ◽  
Semantic Features ◽  
Knowledge Graphs ◽  
Real World Datasets ◽  
Low Dimensional

Knowledge graph embedding aims to embed entities and relations into low-dimensional vector spaces. Most existing methods only focus on triple facts in knowledge graphs. In addition, models based on translation or distance measurement cannot fully represent complex relations. As well-constructed prior knowledge, entity types can be employed to learn the representations of entities and relations. In this paper, we propose a novel knowledge graph embedding model named TransET, which takes advantage of entity types to learn more semantic features. More specifically, circle convolution based on the embeddings of entity and entity types is utilized to map head entity and tail entity to type-specific representations, then translation-based score function is used to learn the presentation triples. We evaluated our model on real-world datasets with two benchmark tasks of link prediction and triple classification. Experimental results demonstrate that it outperforms state-of-the-art models in most cases.

scholarly journals A Little Something Goes a Long Way: Little in the Old Bailey Corpus

2021 ◽  
pp. 007542422098206
Author(s):  
Claudia Claridge ◽  
Ewa Jonsson ◽  
Merja Kytö
Keyword(s):  
Good Deal ◽  
Functional Profile ◽  
Prepositional Phrases ◽  
Related Data ◽  
The Past ◽  
Wide Range ◽  
Old Bailey ◽  
Version 2.0 ◽  
Data Source ◽  
Late Modern

Even though intensifiers have received a good deal of attention over the past few decades, downtoners, comprising diminishers and minimizers, have remained by and large a neglected category (but cf. Brinton, this issue). Among downtoners, the adverb little or a little stands out as the most frequent item. It is multifunctional and serves as a diminishing and minimizing intensifier and also in non-degree uses as a quantifier, frequentative, and durative. Therefore, the present paper is devoted to the structural and functional profile of ( a) little in Late Modern English speech-related data. The data source is the socio-pragmatically annotated Old Bailey Corpus (OBC, version 2.0), which allows, among other things, the investigation of the usage of the item among different speaker groups. Our research charts the semantic and formal uses of adverbial little. Downtoner uses outnumber non-degree uses in the data, and diminishing uses are more common than minimizing uses. The formal realization is predominantly a little, with very rare determinerless or modified instances, such as very little. Little modifies a wide range of “targets,” but most frequently adjectives and prepositional phrases, focusing on human states and circumstantial detail. With regard to variation and change, adverbial little declines in use over the 200 years and is used more commonly by speakers from the lower social ranks and by the lay, non-professional participants in the courtroom.

scholarly journals Development of Knowledge Graph for Data Management Related to Flooding Disasters Using Open Data

2021 ◽  
Vol 13 (5) ◽  
pp. 124
Author(s):  
Jiseong Son ◽  
Chul-Su Lim ◽  
Hyoung-Seop Shim ◽  
Ji-Sun Kang
Keyword(s):  
Artificial Intelligence ◽  
Domain Knowledge ◽  
Open Data ◽  
Heterogeneous Data ◽  
Big Data Analysis ◽  
Knowledge Graph ◽  
Cross Domain ◽  
Disaster Data ◽  
Knowledge Graphs ◽  
Open Datasets

Despite the development of various technologies and systems using artificial intelligence (AI) to solve problems related to disasters, difficult challenges are still being encountered. Data are the foundation to solving diverse disaster problems using AI, big data analysis, and so on. Therefore, we must focus on these various data. Disaster data depend on the domain by disaster type and include heterogeneous data and lack interoperability. In particular, in the case of open data related to disasters, there are several issues, where the source and format of data are different because various data are collected by different organizations. Moreover, the vocabularies used for each domain are inconsistent. This study proposes a knowledge graph to resolve the heterogeneity among various disaster data and provide interoperability among domains. Among disaster domains, we describe the knowledge graph for flooding disasters using Korean open datasets and cross-domain knowledge graphs. Furthermore, the proposed knowledge graph is used to assist, solve, and manage disaster problems.

scholarly journals Research of Personalized Recommendation Technology Based on Knowledge Graphs

2021 ◽  
Vol 11 (15) ◽  
pp. 7104
Author(s):  
Xu Yang ◽  
Ziyi Huan ◽  
Yisong Zhai ◽  
Ting Lin
Keyword(s):  
Neural Network ◽  
Hot Spot ◽  
Experimental Results ◽  
Graph Representation ◽  
Personalized Recommendation ◽  
Knowledge Graph ◽  
Learning Technology ◽  
Data Set ◽  
Model Based ◽  
Knowledge Graphs

Nowadays, personalized recommendation based on knowledge graphs has become a hot spot for researchers due to its good recommendation effect. In this paper, we researched personalized recommendation based on knowledge graphs. First of all, we study the knowledge graphs’ construction method and complete the construction of the movie knowledge graphs. Furthermore, we use Neo4j graph database to store the movie data and vividly display it. Then, the classical translation model TransE algorithm in knowledge graph representation learning technology is studied in this paper, and we improved the algorithm through a cross-training method by using the information of the neighboring feature structures of the entities in the knowledge graph. Furthermore, the negative sampling process of TransE algorithm is improved. The experimental results show that the improved TransE model can more accurately vectorize entities and relations. Finally, this paper constructs a recommendation model by combining knowledge graphs with ranking learning and neural network. We propose the Bayesian personalized recommendation model based on knowledge graphs (KG-BPR) and the neural network recommendation model based on knowledge graphs(KG-NN). The semantic information of entities and relations in knowledge graphs is embedded into vector space by using improved TransE method, and we compare the results. The item entity vectors containing external knowledge information are integrated into the BPR model and neural network, respectively, which make up for the lack of knowledge information of the item itself. Finally, the experimental analysis is carried out on MovieLens-1M data set. The experimental results show that the two recommendation models proposed in this paper can effectively improve the accuracy, recall, F1 value and MAP value of recommendation.

Sign in / Sign up

Export Citation Format

Share Document