Assignment 1 Requirements & Suggestions

Task Overview

This assignment is to help you build up a sense about how data mining techniques can be applied in real-world applications. In this assignment, you are going to survey applications of data mining in one of the following domains (other domains are not optional):

Data Mining in eCommerces: related to how data mining is applied in Amazon.com, Taobao.com, 360buy.com, etc.
Data Mining in Web Search: related to how data mining is applied in Google.com, Yahoo.com, Bing.com, Baidu.com, etc.
Data Mining in Online Advertisements: related to how data mining is applied in Google Ads, Microsoft Ads, Baidu Ads, etc.
Data Mining in Social Networks: related to how data mining is applied in Facebook.com, Tweeter.com, Weibo.com, Renren.com, etc.
Data Mining in Auto-Driving: related to how data mining is applied in the self-driving cars of Google, Mercedes-Benz, Honda, Hyundai/Kia, Nissan, etc.

and write a survey using a given template restrictively.

In the rest of this page, you can find:
    what to read?
    what/how to write?
    how to submit?
    how is your survey evaluated?
Please read them carefully.

The author holds the copyright of the survey. The survey, unless agreed by the author, will not be disclosed to any third party.

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What to read?

To survey the applications of data mining, you surely need to know at first what data mining is. Therefore, you are highly encouraged to read the recommended papers on the course homepage (reading materials for each chapter) as comprehensive and intensive as possible.

You can find peer-reviewed papers, which are trustworthy with rich details, in IEEEXplore, ACM Portal, Elsevier, and DBLP (DBLP only provides paper titles and sources, you need to download the paper elsewhere). You can also search papers by search using Google Scholar. As data mining gains more and more attentions, it is easy to find information of data mining applications in mass media such as news papers, online forums, blogs, etc, which however should be carefully handled.

(NOTE: You will need a Nanjing University IP to access IEEEXplore, ACM Portal and Elsevier)

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What/How to write?

You are required to select one topic listed above, and investigate the topic by following the questions:
How did people do when the data mining techniques have not been applied?
What were the problems?
How the data mining techniques develop to solve the problem?
Are there any problems you think remaining and needed to be solved in the future?

Please use

this DOC template (open with Microsoft Word, WPS or OpenOffice)
or this LaTex template (compile with XeLaTeX, thanks Mr. Zhaokang Wang)

to write your survey in Chinese. You should follow the outline of the template restrictively, and note:

Follow the template, do NOT modify black text, but only replace the red text with your own words.
Save your finished DOC file to a PDF file for submission.

Must NOT plagiarize:

Whenever you are using words, tables, figures and any work of others, citations should be made clear.
A continuous verbatim copy of more than 50 English/Chinese words is identified as a plagiarism, regardless of citations.

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How to submit?

Name your PDF survey file using your student ID, e.g., '091221154.PDF'.

Upload your file to FTP: (recommend to use FTP software rather than Windows Explorer or IE)
     ftp://lamda.nju.edu.cn/dm/assignment1/
     username: dm13
     password: dm13

No other file formats are acceptable.
No submissions after the deadline are acceptable.
No email submissions are accepted.

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How is your survey evaluated?

Evaluation of your job will be based on the content and your writing. A smooth article reflecting your comprehension will receive a good score.

No scores will be given to a plagiarism.

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Received submissions

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