http://www.woshipm.com/it/1057792.html
Atlas association relationship network map based map database, is a visual intelligence analysis product. FIG calculation engine query data and analysis data extraction and conversion, second level data calculation and data visualization, and appear as a map to the user graphical analysis tool. Users can query, analyze, and explore been built on the map.
What is the relevance map?
In understanding what is related maps before we start to understand what the graph is what is drawing database. What is the view of it?
Figure is a structured expression of mutual connection of things and their relationships, is the closest real-world data organization structure. All data will be connected by drawing up instantly convey information, easy to reveal the complex relationship patterns.
Figure consists of nodes and edges, drawing entities will be able to see in real life can be touched (such as a person, a computer, a bank card, etc.), or not visible to the naked eye can not touch an accident, a cases, a particular accident, etc., are abstracted into nodes in the graph. And the relationship between any two nodes and the node, then abstracted into edges.
FIG is constituted by a set of a set of nodes and edges, the nodes can have multiple attributes, attributes can have multiple edge node may have several labels, representing different identities. As someone in your life that is a child's father, is a husband, he is a financial technology company's CPO.
Map can contain a wealth of related information, such as: a call relationship between the telephone and the telephone, e-mail relationships, kinship, relations have a variety of scenarios in various fields of social networks, transportation networks, communication networks, financial networks, etc. Fig able to show the most intuitive relationship links between entities, relationships convey path.
In the field of science and technology have a Six Degrees of Separation theory is that we often hear of any two people in the world simply by up to six relationship we will be able to find each other, and the associated maps can put this theory into reality.
Well, we now know what a chart, where it exists that figure? Large amount of data when how to do it?
After all, the network of social relations between China more than 1.3 billion people, all kinds of posed, it is the amount of data of millions of levels.
图存储在图数据库（Graph Database）中，图数据库以图论为理论基础，图论中图的基本元素是节点和边，在图数据库中对应的就是节点和关系。用节点和关系所组成的图为真实世界直观地建模，支持百亿量级甚至千亿量级规模的巨型图的高效关系运算和复杂关系分析。
目前市面上较为流行的图数据库有Neo4j、Orient DB、Titan、Flock DB、Allegro Graph等。
不同于关系型数据库，一修改便容易“牵一发而动全身”图数据库可实现数据间的“互联互通”，与传统的关系型数据库相比，图数据库更擅长建立复杂的关系网络。
关联图谱基于图数据库建立关系网络图，是一种可视化的智能分析产品。通过数据抽取和转换，图计算引擎对数据进行查询和分析，实现秒级数据运算和数据可视化，并以图谱的形式展示给用户的图形分析工具。用户可以基于已建好的图谱进行查询、分析和探索。
关联图谱在风控领域中主要用于事中、事后的查询和分析，目前在反欺诈、反洗钱、互联网授信、车险、项目审计、公司关系、信用卡申请、交易等场景下均有应用。
可以这么说，凡是有关系的地方都可以用到关联图谱，我们现实生活中的实体都是由一个一个看似非常简单的关系组成的，如:人与人之间、公司与人之间、公司与公司之间、人与某个项目、某个活动与某个明星、学校与某个学生，生活中可触摸的不可触摸的事物都可以用关系连接起来。
这些容易被我们忽视的隐形关系和看似非常常见的关联关系，往往是风险突破口和识别欺诈、发现团伙的重要线索，下篇将详细介绍关联图谱的应用场景。
作者：Amy，公众号Amy产品记，旨在与同行交流关联图谱（知识图谱）和风控领域产品
本文由 @Amy 原创发布于人人都是产品经理。未经许可，禁止转载
题图来自 Pexels，基于 CC0 协议