Neo4j Graph Database Implementation for LinkedIn

Nikam, Punam; Bhoite, Sachin; Shenoy, Anuj

doi:10.32628/cseit206665

Cited by 4 publications

(3 citation statements)

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“…Salah satu graph database adalah Neo4j yang dapat digunakan untuk manajemen data platform media sosial. Neo4j yang diterapkan pada LinkedIn dapat memberikan manajemen dan pengambilan data yang lebih cepat dan tepat dibandingkan dengan relational database NoSQL atay MYSQL [18].…”

Section: Pendahuluanunclassified

Penerapan Metode Weighted Product Berbasis Visualisasi Graph Database dalam Merekomendasikan Parfum Isi Ulang

Qolbiah,

Fauzan,

Prabowo

2023

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Perfume is useful for increasing self-confidence, creating satisfaction, eliminating bad odors, and making self-assessment more attractive. Refill perfumes are made from certain perfume seeds dissolved in a suitable solvent. Perfume has many types and strengths of aroma, but there are obstacles when people want to choose the desired perfume scent. This problem becomes research material because it is expected that this problem can be solved. To determine perfume recommendations, it is calculated using the Weighted Product method and visualized using a graph database. In the Neo4j Graph Database visualization, the perfume category and perfume name are used as nodes and the ranking results are used as edges. From the ranking results using the Weighted Product method, 21 perfumes for each category are entered into the Graph Database visualization and a total of 63 perfumes will appear in the perfume recommendation system.Refill perfume is a perfume made from certain perfume seeds dissolved in the appropriate solvent.

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Section: Pendahuluanunclassified

Penerapan Metode Weighted Product Berbasis Visualisasi Graph Database dalam Merekomendasikan Parfum Isi Ulang

Qolbiah,

Fauzan,

Prabowo

2023

json

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“…Neo4j was launched in 2010 and stores data in the form of nodes, attributes, and edges, where each node and edge can have multiple attributes [17]. Neo4j implements a property graph that is made up of nodes, relationships, and properties.…”

Section: Related Workmentioning

confidence: 99%

Constructing Crop Portraits Based on Graph Databases Is Essential to Agricultural Data Mining

et al. 2021

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Neo4j is a graph database that can use not only data, but also data relationships. Crop portraits, a kind of property graph, model the crop entity in the real world based on data to realize the networked management of crop knowledge. The existing crop knowledge base has shortcomings such as single crop variety, incomplete description, and lack of agricultural knowledge. Constructing crop portraits can provide a comprehensive description of crops and make up for these shortcomings. This research used agricultural question-and-answer data and popular science data obtained by text crawling as the original data, selected labels to establish a crop portrait that including three categories (crops, pesticides, and diseases and pests), and used the graph database (Neo4j) to store and display these portrait data. Information mining found that the crop portrait revealed the occurrence trend of diseases and pests, exhibited a nonintrinsic connection between different diseases and pests, and provided a variety of pesticides to choose from for control of diseases and pests. The results showed that constructing crop portraits is beneficial to agricultural analysis, and has practical application values and theoretical research prospects in the field of big data analytics.

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“…In this study, Neo4j's labeled property graph is employed to represent citation and author collaboration network. Neo4j is a graph database which was launched in 2010 and stores data in the form of nodes, properties, and edges, where each node and edge can have multiple properties [7]. Neo4j uses the powerful query language Cypher to retrieve and manipulate graph data.…”

Section: Introductionmentioning

confidence: 99%

Exploring Citation and Author Collaboration Network with Graph Database

Yadav,

Bhandari,

Nikam

2024

Preprint

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There are several research papers available online that span a wide range of disciplines. Researchers are using this data through search engines, digital libraries and professional networks. To make effective use of this data we propose building a citation network consisting of papers, authors and citations. Complex queries based on connections can be best handled by graph databases like Neo4j. Neo4j is a graph database that is specially designed for interconnected data. Neo4j represents data in the form of nodes and relationships and uses Cypher query language for CRUD (CREATE, READ, UPDATE and DELETE) operations. The proposed study, uses DBLP citation dataset to model citation and author collaboration networks using Neo4j. The expressiveness of Cypher query language in extracting insights from vast bibliographic data has been explored. The citation and author collaboration networks are analyzed to identify influential papers, influential authors, co-author networks, and to compute researcher’s impact metrics.

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Neo4j Graph Database Implementation for LinkedIn

Cited by 4 publications

References 0 publications

Penerapan Metode Weighted Product Berbasis Visualisasi Graph Database dalam Merekomendasikan Parfum Isi Ulang

Penerapan Metode Weighted Product Berbasis Visualisasi Graph Database dalam Merekomendasikan Parfum Isi Ulang

Constructing Crop Portraits Based on Graph Databases Is Essential to Agricultural Data Mining

Exploring Citation and Author Collaboration Network with Graph Database

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