[PRESS] MyCreditChain, Proceeding 2nd Collaborative Research With Seoul National University’s…

[CCTV News=Reporter Cho Joong Hwan] MyCreditChain, a blockchain-based data collection and analysis company, announced on the 1st of July that they will be proceeding a second round of collaborative research for the implementation and visualization of a “Trust Network” with Seoul National University’s Industrial & Mathematical Data Analytics Research Center(hereinafter referred to as “IMDARC”).

Prior to this, MyCreditChain has already conducted collaborative research with IMDARC for the purpose of combining the mathematical theory with blockchain and the digital finance industry for a period of three months in May 2018. Currently, the results of the first joint research are being implemented on the “Good Morning” app, a rewarding social networking service, and its results are constantly evolving and improving the service.

The purpose of the second joint research with IMDARC is to find the influence analysis and evaluation method based on the data of activity accumulated through network participants on the ‘Good Morning’ service.

There are three main topics that will be proceeded in this research collaboration. First, is the Visualization of the network creation process. Using topological mathematical data analysis, the generation process of a given network will be possible for visualization over time. It will also allow for the analyses process of creating a neighboring network for each individual to help the intuitive understanding of the whole and in portions.

Second, is Network Centering and Clustering. Applying various clustering and clustering techniques to derive network features will play an important role in the network ecosystem and lay the foundation for recognizing influences that exert impact. This analysis will be proceeded from the viewpoint from the whole network, and simultaneously in small group units to analyze specialized extraction and influence.

Third, is Trust Algorithm and MapView. Trust algorithms consist of a combination of algorithms that detect influencers and are intended to be used for networking and extensibility. MapView is the research that will provide the potential to provide real service by visualizing the corresponding partial network for individual or small group based on each derived network characteristic.

Woosik Kim, CEO of MyCreditChain, has pointed that, “This is a role given to the leading companies in the field to provide unprecedented value to customers by combining new fields such as blockchain, data, and credit evaluation.” He also added by saying, “We will continue to provide new value by quickly incorporating the results of the collaborative research with the Seoul National Univerisity’s research team into the Good Morning Service.”

Source: CCTV News Reporter Cho Joong Hwan<illssimm@cctvnews.co.kr>

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What is the Good Morning Service?

The Good Morning service is a <Blockchain-Based Reward Social Networking Service> developed by MyCreditChain. Unlike existing social networking services, it offers a distinctive value by providing gifts called ‘Seeds’ in the form of ‘Likes’ that can be converted into MCC tokens. It is an innovative service that allows for the direct and indirect experience of cryptocurrency without the investment of money.

▶️Download the Good Morning App : [Google Playstore] [App Store]
▶️[How to use Good Morning?]
▶️[Indonesia TV Presenter Delvia’s Review]

Building Trust with Your Data!

▶Good Morning Homepage▶Telegram ▶Facebook ▶Twitter ▶YouTube

MyCreditChain (https://www.mycreditchain.org) is

A blockchain-based, decentralized, Trust Data Distribution ecosystem in which individuals have the ability to capitalize on their own information and expand relationships through the MyCreditChain platform in order to create new credibility for the underbanked. Our goal is to return the ownership of personal information back to the individual and to create a free and equal society by giving the ability for each individual to reap benefits from their personal information and Trust Data.

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