## 4 Results
### Application Domain and the Incorporated Concept Drifts  
The DRS has been extensively researched in recent ages across different fields such as multimedia [7; 22; 62; 63; 64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74; 75; 76; 77; 78; 79; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 90; 91; 92; 93; 94; 95; 96; 97; 98; 99; 100; 101], e-documents [67; 68; 69; 102; 103; 104; 105; 106; 107; 108], Travel, Tourism and Places [8; 10; 13; 30; 37; 109], and others [9; 12; 87; 88; 94; 110; 111; 112; 113; 114; 115; 116]. This was said to have started after the Netflix competition in 2009, where the time changing user behaviors were considered  
Figure 4: Distribution of selected papers according to publication year.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**No.** & **Quality questions** \\ \hline
1 & Are the aims clearly stated? \\
2 & How credible are the findings? \\
3 & If credible, are they important? \\
4 & Does the evaluation address its original aims and purpose? \\
5 & Is the scope for drawing wider inference explained? \\
6 & Is the basis of evaluative appraisal clear? \\
7 & Has diversity of perspective and context been explored? \\
8 & How well have detail, depth, and complexity of the data been conveyed? \\
9 & How clear are the links between data, interpretation, and conclusion? \\
10 & How clear and coherent is reporting? \\ \hline \hline \end{tabular}
\end{table}
Table 3: Quality Checklist.  
to improve recommendation accuracy [70; 71; 72; 73; 74; 75; 76; 77; 78; 79; 80; 81; 82]. In each application domain, we study different types of concept drifts incorporated for recommendation purposes.  
It is interesting to note that the gain of tracking concept drift varies from one domain to another [22]. As could be seen in Figure 5, the findings of our review indicated that the most common application domains where the dynamics-based model is applied are broadly categorized as multimedia (Movies and Music), e-commerce, e-documents, travel/tourism, and places. Among all the application domains, the studies related to multimedia fields (36 out of 87 research papers, or 41%) and e-commerce (17 out of 87 research papers, or 20%) had taken the majority of the publications. While few of the studies were related to other domains such as Travel, Tourism, and places (12 out of 87 research papers, or 14%), and others (6 out of 87 research papers, or 7%, respectively). This could be interpreted as a result of a larger number of available sources of multimedia data for practical applications more than other application fields. Specifically, the Movie Lens dataset (www.movielens.org) provides a rich quality data with time information needed to evaluate the dynamics-based model performances and are freely accessible, which explains the reason for more DRS researches in movie fields than in other fields. Table 4 presents the domains of application with their incorporated concept drifts that we discovered in the selected studies. Based on the review, the incorporated concept drifts in the DRS can be viewed as any changes that occur either from the side of users, items or system environment. The tracked change attribute can either be of a short term or a long term change duration.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Application** & **Incorporated Concept Drifts** & **No. of Papers** & **Reference** \\ \hline Multimedia & Personal preference, item popularity, time, seasonality, user’s location, age, current situation, social relations, emotion and mood, biases, rating behaviour. & 36 & [2,3,5,7,11,22,23,29,49,51,62,63,73; 74; 75; 76; 77; 77; 78; 79; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 80; 8