A large amount of information is created and stored by social medie, from which we can anglyse the preference of people towards something, such as, how they feel or evaluate. A method in data mining is called aspect-level analysis, which extracts the characaterised aspects or attributes of an entity. Here, I think, is fairly similar with the memorizing method of graph memory.
Take two-dimension code for example. Two-dimension code is invented before 1990 and afterwards in 2012 applied in large-scale among Chinese mobile market by Wechat. There are few people who can memorise the key information of two-dimension code so that they can distinguish one among a group of graphs containing two-dimension codes. The key that these people can realize this is that they extract the key aspects of this kind of code.
Now, let us think about,when we are in our childhood, how our parents teach us to recognize one person from so many people. Undoutedly, our parents teach us to focus on their color and length of hairs, whether wearing glasses, figure and weight, which all are the key-aspect of a person.
We memorize a graph or scene through catching the characters. Data mining is extremely like this.
Algorithms written as a few lines of codes or an application cannot behave well like humans upon extracting all the potential information of a few words. Therefore, what we can do is to analysing the key characters and digitalise these characters so that we can form a more direct image towards the information.
Hi Guilin~Thanks for your sharing of analyzing the relevance between data mining and graph memory. The example of two-dimension code is quite appropriate and now I know that both of their objectives are catching the key characters of information. Hope you can share more detailed algorithms based on this.
回覆刪除I really like your blog because they are abstract but innovative,you mention the two-dimension code in the blog and it is such a surprise that it is invented in such a early time but the application is more than 10 years after the invention.With the widely usage of the 2 dimension code,most people haven't come up with the idea of finding the principle of the 2-dimention code.Charaters extraction does look a lot like the data mining since the extraction is also one step of the whole process.
回覆刪除hi Guilin,your blog is really brief but enjoyable,you use an analog of the experience in our childhood to held us understand the key aspects in two-dimension code,and it proved to be really efficient:-)
回覆刪除data mining and graph memorise is linked by method and target. I am thinking if there possibility to do some data process in graph. because, most data mining are focused on articles. Graph analyst is a new way to try.
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