IJBTT

Advancing Financial Operations: Leveraging Knowledge Graph for Innovation
	© 2023 by IJCTT Journal
	Volume-71 Issue-10
	Year of Publication : 2023
	Authors : Shyam Balagurumurthy Viswanathan, Gaurav Singh
	DOI :  10.14445/22312803/IJCTT-V71I10P107

How to Cite?

Shyam Balagurumurthy Viswanathan, Gaurav Singh, "Advancing Financial Operations: Leveraging Knowledge Graph for Innovation," International Journal of Computer Trends and Technology, vol. 71, no. 10, pp. 51-60, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I10P107

Abstract
Recently, there has been a growing interest in Knowledge Graphs (KG) due to their ability to systematically structure and categorize complex information. These graphical representations uniquely identify intricate patterns, reveal hidden insights, process enormous amounts of data with intuitive visualization, and accurately retain diverse information. One domain where KGs can be particularly valuable is the financial market, specifically the stock sector, which generates vast amounts of data across various platforms. This research paper outlines the methodologies for constructing a knowledge graph using graph databases and explores how it can enhance our understanding of financial paradigms. By doing so, this paper aims to improve the accuracy and depth of stock analyses, facilitate better decision-making processes, and detect anomalies such as intellectual property theft or insider trading within the realm of finance.

Keywords
Knowledge graph, Financial operations, Cyber security, Trading, Intelligence.

Reference

[1] Zhibo Li et al., “Bearing Fault Diagnosis Method Based on Convolutional Neural Network and Knowledge Graph,” Entropy, vol. 24, no. 11, pp. 1-18, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Sergio Oramas et al., “Sound-and-Music-Recommendation-with-Knowledge-Graphs,” ACM Transactions on Intelligent Systems and Technology, vol. 8, no. 2, pp. 1-21, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Wen-Dong Li et al., “Is Being a Leader a Mixed Blessing? A Dual-Pathway Model Linking Leadership Role Occupancy to Well-Being,” Journal of Organizational Behavior, vol. 39, no. 8, pp. 971-989, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Mingfei Liu et al., “A Knowledge Graph-Based Approach for Assembly Sequence Recommendations for Wind Turbines,” Machines, vol. 11, no. 10, pp. 1-25, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[5] B.V. Shyam, How to Build a Knowledge Graph on Stocks, AWS Neptune, 2021. [Online]. Available: https://medium.com/code-sprout/build-a-knowledge-graph-on-stocks-aws-neptune-7c2b94fdc9b7
[6] Dive into Anything, Reddit. [Online]. Available: https://www.redditinc.com/
[7] How to Read a 10-K/10-Q, SEC.gov, 2021. [Online]. Available: https://www.sec.gov/oiea/investor-alerts-and-bulletins/how-read-10-k10- q
[8] Xiao Ding et al., “Knowledge-Driven Event Embedding for Stock Prediction,” Proceedings of COLING 2016, The 26th International Conference on Computational Linguistics, pp. 2133-2142, 2016.
[Google Scholar] [Publisher Link]
[9] Amazon Neptune, Amazon Web Services. [Online]. Available: https://aws.amazon.com/neptune/
[10] JanusGraph. [Online]. Available: https://janusgraph.org/
[11] Neo4j Documentation, Neo4j. [Online]. Available: https://neo4j.com/docs/
[12] Getting Started, Apache Tinker Pop. [Online]. Available: https://tinkerpop.apache.org/docs/current/tutorials/getting-started/
[13] Graph Database Platform Overview, TigerGraph. [Online]. Available: https://www.tigergraph.com/product/
[14] Cypher Query Language, Neo4j. [Online]. Available: https://neo4j.com/developer/cypher/
[15] SPARQL, World Wide Web Consortium (W3C). [Online]. Available: https://www.w3.org/2001/sw/wiki/SPARQL
[16] Financial Modeling Prep, Datarade. [Online]. Available: https://datarade.ai/data-providers/financial-modeling-prep/profile
[17] Apple (AAPL) Stock Price, Quote, News and History, Nasdaq. [Online]. Available: https://www.nasdaq.com/market-activity/stocks/aapl
[18] NASDAQ Composite Index (COMP) Latest Quotes, Charts, Data and News, Nasdaq. [Online]. Available: https://www.nasdaq.com/market-activity/index/comp
[19] Getting Started with Amazon Neptune, Amazon Web Service. [Online]. Available: https://docs.aws.amazon.com/neptune/latest/userguide/graph-get-started.html
[20] Named Entity Recognition, CoreNLP. [Online]. Available: https://stanfordnlp.github.io/CoreNLP/ner.html
[21] Batched Graph Classification with DGL, Deep Graph Library, 2019. [Online]. Available: https://www.dgl.ai/blog/2019/01/25/batch.html
[22] PyG Documentation, Pytorch_Geometric Documentation. [Online]. Available: https://pytorch-geometric.readthedocs.io/en/latest/
[23] Pankaj Gupta, “Leveraging Machine Learning and Artificial Intelligence for Fraud Prevention,” SSRG International Journal of Computer Science and Engineering, vol. 10, no. 5, pp. 47-52, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Mayorga Lira Sergio Dennis, Laberiano Andrade-Arenas, and Miguel Angel Cano Lengua, “Credit Risk Analysis: Using Artificial Intelligence in a Web Application,” International Journal of Engineering Trends and Technology, vol. 71, no. 1, pp. 305-316, 2023.
[CrossRef] [Google Scholar] [Publisher Link]