I edited the Nepalese Ambassador in Russia. I included the current ambassador at the very top.

Examples of data mining

  • Is each fact referenced with an appropriate, reliable reference?
  • Is everything in the article relevant to the article topic? Is there anything that distracted you?
  • Is the article neutral? Are there any claims, or frames, that appear heavily biased toward a particular position?
  • Where does the information come from? Are these neutral sources? If biased, is that bias noted?
  • Are there viewpoints that are overrepresented, or underrepresented?
  • Check a few citations. Do the links work? Is there any close paraphrasing or plagiarism in the article?
  • Is any information out of date? Is anything missing that could be added

From when I first opened this page, I noticed that it was very raw. First off, usually there is some sort of picture and related topics in the top right corner of most Wikipedia pages, however in my page, there was not. Next, the table of contents was very simple, lacking sub categories within topics like Business, Games, Science and Engineering. It is most definitely possible to break down and sort the information into more sub-categories, for example, for Business, instead of listing the categories into more specific and organized sub-categories, they instead just listed the many different applications of data mining in different industries plainly under the Business category. I believe there could at least be a sub-category under business like supply-chain or inventory within the example of Walmart. However one of the issues that I saw was that although they listed examples and categorization of inventory for e-commerce, there was a citation to that information, however, there was not enough links of key terms. It seems poorly cited within the Business category. It becomes much better cited in categories like Science and Engineering. Definitely if you were to compare the Business category to categories like Medical data mining, you will notice the deep contrast in which the Business category is lacking information. I do believe everything in this article is relatively objective and not biased except for certain categories like the Business categories, which only lists a few specific cases that are not significant enough to be listed alone, and by significant, I mean historic changes that could have transformed the technology or legislation around data mining. Under the category of Spacial data mining, they listed several organizations that did different kinds of geographic data mining. These categories have examples that lack links and definition sources that could greatly enhance this article. The information from this article seems to be pulled from various credible sources like scholarly journals and Universities. Some of the citations work, however, some of the citations do not work. When I clicked on the broken citations, their website was not found. I do not believe any information is out of date, but definitely, more information, as well as more pictures and organizations can be added.