什么“其他特征”?可以纳入火车数据库吗?
这是 DBMS 课程的一个迷你项目。我的任务是开发一个用于客运列车管理的数据库。
我正在设计客户、火车、订票(通过电话和互联网)、出发地和目的地的表格。
他说,我们可以自由地将其他功能合并到我们的数据库模型中。我们可以包括的一些功能如下:
- 临时查询
- 数据挖掘
- 人口统计乘客映射
- 始发地和目的地映射
我不知道这些功能的含义。我了解数据挖掘,但无法在这种情况下应用它。任何人都可以扩展这些功能或提出新的想法吗?
编辑:什么是临时查询?在这方面举一个例子。
This is a mini project for DBMS course. My task is to develop a Database for management of passenger trains.
I'm designing tables for Customers, Trains, Ticket Booking (via Telephone & Internet), Origins and Destinations.
He said, we are free to incorporate other features in our Database Model. Some of the features that we can include are as listed:
- Ad-hoc Querying
- Data Mining
- Demographic Passenger Mapping
- Origin and Destination Mapping
I've no clue about what these features mean. I know about datamining but unable to apply it in this context. Can any one kindly expand these features or suggest new ideas?
EDIT: What is Ad-hoc Querying? Give an example in this context.
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数据挖掘将包括从系统和数据获得的数据中提取有用的事实/数字。存储在数据库中。例如,数据挖掘可能会发现城市 x 和 y 之间的火车总是晚点 5 分钟,或者从未超过 50% 的载客量等。因此,您可能希望开发一些自动运行并生成统计数据(图表)的工具或脚本是最好的),它显示此信息并突出显示不寻常的趋势。在给定的示例中,调度员可以分析为什么火车总是晚点(例如,火车速度可能是错误的?)。
在我看来,第 3 点和第 4 点都是数据挖掘的子集。您可以尝试衡量大量指标,实际上是您能想到的任何指标。如果您指定要收集的数据类型,则可以更轻松地提出建议。
基本上,数据挖掘只是意味着“对数据进行排序以发现有趣的事实”。
根据下面的评论,您可以查找
Data mining would incorporate extracting useful facts/figures out of the data obtained by your system & stored in the database. For example, data mining might discover that trains between city x and y are always 5 minutes late, or is never at more than 50% capacity, etc. So you may wish to develop some tools or scripts that automatically run and generate statistics (graphs are best) which display this information and highlight unusual trends. In the given example, the schedulers could then analyse why the trains are always late (e.g., maybe the train speedos are wrong?).
Both points 3. and 4. are a subset of data mining imo. There is a huge amount of metrics you could try to measure, it is just really whatever you can think of. If you specify what type of data you are going to collect, that will make making suggestions easier.
Basically, data mining just means "sort the data to find interesting facts".
Based on comment below you could look for,