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Data And Data Source Analysis

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4. Data source analysis
Data is one of the important factors in data forecasting studies because data represents the whole source of the business purpose of the study.

There are several reasons that the difference of data source makes it hard to compare prediction accuracy from each other.

First, the result of a prediction model may differ with different data sources. Theoretically, the more data we test, the more accurate result we can get, however, in real-world, it is often hard to collect as much data as desired. So a potential difficult question for all data prediction studies is that how much data is enough.

Second, the quality of data source is crucial for prediction studies. Apparently, false data or noisy data is not useful for …show more content…

With the similar target, Gordiievych and Shubin (2015) did not give any description of their data.
4.1.2. Different range and size of data
For airline prices prediction studies, it is a common practice to use time series data like airline ticket prices. The date ranges of data used by different studies vary from several months to as long as 18 years.

For example, Chen et al. (2015) used 110 days of data in their study, and the other study from Zhang et al. (2010) used 18 years of data to perform the experiment. Some studies did not specify their date range of the data explicitly, such as Wohlfarth et al. (2011), Gordiievych and Shubin (2015) and Cao, Ding, He, and Zhang (2010). Other studies chose other data lengths. Laik, Choy, and Sen (2014) used one year of data, as the same length as Liu, Tan, and Zhou (2016). Yuan, Xu, and Yang (2014), Ghomi and Forghani (2016), and An et al. (2016) used three years, six years, and ten years respectively.

One reason these studies chose different ranges of data for analysis is very likely the fact that data collection for a long time range is difficult. Those studies used data ranges longer than a year were mostly using historical data either from proprietary

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