• Genomics & Informatics
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• v.15 no.1
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• pp.19-27
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• 2017

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2211-2232
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• 2018

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.163-180
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• 2022

Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.

• Macromolecular Research
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• v.12 no.4
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• pp.325-335
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• 2004

Molecular weight distributions of poly(vinyl neo-decanoate) produced by the bulk polymerization of the monomer to low conversions were investigated to obtain values of the rate constants for the chain transfer to monomer ( $C_{M}$). The value of $C_{M}$ of 7.5($\pm$0.6)${\times}$10$^{-4}$ was obtained from a logarithmic plot of the number distribution at 5,25, and 5$0^{\circ}C$, which suggests that the activation energy for chain transfer is on the order of 20-25 kJ ㏖$^{-1}$ . These plots were linear between the number and weight-average degrees of polymerization, but not over the whole molecular weight range for which a significant signal was observed in the gel permeation chromatography (GPC) trace. Modeling suggests that the deviations observed at high molecular weights can be explained by branching of the chains through chain transfer to the polymer, with a branching density as low as 10$^{-5}$ , without affecting the slope at low values of the number of monomer unit, N. This deviation from the expected distribution of linear chains was used to estimate the branching densities at low conversion.ion.

• Journal of Microbiology and Biotechnology
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• v.27 no.1
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• pp.197-205
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• 2017

Exposure of Jurkat T cell clone (J/Neo cells) to acacetin (5,7-dihydroxy-4'-methoxyflavone), which is present in barnyard millet (Echinochloa esculenta (A. Braun)) grains, caused cytotoxicity, enhancement of apoptotic $sub-G_1$ rate, Bak activation, loss of mitochondrial membrane potential (${\Delta}{\Psi}m$), activation of caspase-9 and caspase-3, degradation of poly(ADP-ribose) polymerase, and FITC-Annexin V-stainable phosphatidylserine exposure on the external surface of the cytoplasmic membrane without accompanying necrosis. These apoptotic responses were abrogated in Jurkat T cell clone (J/Bcl-xL) overexpressing Bcl-xL. Under the same conditions, cellular autophagic responses, including suppression of the Akt-mTOR pathway and p62/SQSTM1 down-regulation, were commonly detected in J/Neo and J/Bcl-xL cells; however, formation of acridine orange-stainable acidic vascular organelles, LC3-I/II conversion, and Beclin-1 phosphorylation (Ser-15) were detected only in J/Neo cells. Correspondingly, concomitant treatment with the autophagy inhibitor (3-methyladenine or LY294002) appeared to enhance acacetin-induced apoptotic responses, such as Bak activation, ${\Delta}{\Psi}m$ loss, activation of caspase-9 and caspase-3, and apoptotic $sub-G_1$ accumulation. This indicated that acacetin could induce apoptosis and cytoprotective autophagy in Jurkat T cells simultaneously. Together, these results demonstrate that acacetin induces not only apoptotic cell death via activation of Bak, loss of ${\Delta}{\Psi}m$, and activation of the mitochondrial caspase cascade, but also cytoprotective autophagy resulting from suppression of the Akt-mTOR pathway. Furthermore, pharmacologic inhibition of the autophagy pathway augments the activation of Bak and resultant mitochondrial damage-mediated apoptosis in Jurkat T cells.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.429-437
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• 2022

Recently, the demand for a QA (Question Answering) system for human-machine communication has increased. Among the QA systems, a closed domain QA system that can handle spatial-related questions is called GeoQA. In this study, a new type of graph database, LPG (Labeled Property Graph) was used to overcome the limitations of the RDF (Resource Description Framework) based database, which was mainly used in the GeoQA field. In addition, GraphQL (Graph Query Language), an API-type query language, is introduced to address the fact that the LPG query language is not standardized and the GeoQA system may depend on specific products. In this study, database was built so that answers could be retrieved when spatial-related questions were entered. Each data was obtained from the national spatial information portal and local data open service. The spatial relationships between each spatial objects were calculated in advance and stored in edge form. The user's questions were first converted to GraphQL through FOL (First Order Logic) format and delivered to the database through the GraphQL server. The LPG used in the experiment is Neo4j, the graph database that currently has the highest market share, and some of the built-in functions and QGIS were used for spatial calculations. As a result of building the system, it was confirmed that the user's question could be transformed, processed through the Apollo GraphQL server, and an appropriate answer could be obtained from the database.

• Journal of Microbiology and Biotechnology
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• v.26 no.2
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• pp.287-294
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• 2016

The effect of kaempferol (3,5,7,4-tetrahydroxyflavone), a flavonoid compound that was identified in barnyard millet (Echinochloa crus-galli var. frumentacea) grains, on G₂-checkpoint and apoptotic pathways was investigated in human acute leukemia Jurkat T cell clones stably transfected with an empty vector (J/Neo) or a Bcl-xL expression vector (J/Bcl-xL). Exposure of J/Neo cells to kaempeferol caused cytotoxicity and activation of the ATM/ATR-Chk1/Chk2 pathway, activating the phosphorylation of p53 (Ser-15), inhibitory phosphorylation of Cdc25C (Ser-216), and inactivation of cyclin-dependent kinase 1 (Cdk1), with resultant G₂-arrest of the cell cycle. Under these conditions, apoptotic events, including upregulation of Bak and PUMA levels, Bak activation, mitochondrial membrane potential (Δψm) loss, activation of caspase-9, -8, and -3, anti-poly (ADP-ribose) polymerase (PARP) cleavage, and accumulation of apoptotic sub-G₁ cells, were induced without accompanying necrosis. However, these apoptotic events, except for upregulation of Bak and PUMA levels, were completely abrogated in J/Bcl-xL cells overexpressing Bcl-xL, suggesting that the G₂-arrest and the Bcl-xL-sensitive mitochondrial apoptotic events were induced, in parallel, as downstream events of the DNA-damage-mediated G₂-checkpoint activation. Together these results demonstrate that kaempferol-mediated antitumor activity toward Jurkat T cells was attributable to G₂-checkpoint activation, which caused not only G₂-arrest of the cell cycle but also activating phosphorylation of p53 (Ser-15) and subsequent induction of mitochondria-dependent apoptotic events, including Bak and PUMA upregulation, Bak activation, Δψm loss, and caspase cascade activation.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.800-807
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• 2022

This study aims to review the use of graph databases in construction research. Based on the diagnosis of the current research status, a future research direction is proposed. The use of graph databases in construction research has been increasing because of the efficiency in expressing complex relations between entities in construction big data. However, no study has been conducted to review systematically the status quo of graph databases. This study analyzes 42 papers in total that deployed a graph model and graph database in construction research, both quantitatively and qualitatively. A keyword analysis, topic modeling, and qualitative content analysis were conducted. The review identified the research topics, types of data sources that compose a graph, and the graph database application methods and algorithms. Although the current research is still in a nascent stage, the graph database research has great potential to develop into an advanced stage, fused with artificial intelligence (AI) in the future, based on the active usage trends this study revealed.