MoGaL: Novel Movie Graph Construction by Applying LDA on Subtitle | ||
| Journal of AI and Data Mining | ||
| دوره 11، شماره 2، تیر 2023، صفحه 221-228 اصل مقاله (1.4 M) | ||
| نوع مقاله: Technical Paper | ||
| شناسه دیجیتال (DOI): 10.22044/jadm.2023.12481.2396 | ||
| نویسندگان | ||
| Mohammad Nazari1؛ Hossein Rahmani* 2؛ Dadfar Momeni3؛ Motahare Nasiri3 | ||
| 1School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran. | ||
| 2School of Computer engineering, Iran University of Science and Technology, Tehran, Iran. | ||
| 3School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| چکیده | ||
| Graph representation of data can better define relationships among data components and thus provide better and richer analysis. So far, movies have been represented in graphs many times using different features for clustering, genre prediction, and even for use in recommender systems. In constructing movie graphs, little attention has been paid to their textual features such as subtitles, while they contain the entire content of the movie and there is a lot of hidden information in them. So, in this paper, we propose a method called MoGaL to construct movie graph using LDA on subtitles. In this method, each node is a movie and each edge represents the novel relationship discovered by MoGaL among two associated movies. First, we extracted the important topics of the movies using LDA on their subtitles. Then, we visualized the relationship between the movies in a graph, using the cosine similarity. Finally, we evaluated the proposed method with respect to measures genre homophily and genre entropy. MoGaL succeeded to outperforms the baseline method significantly in these measures. Accordingly, our empirical results indicate that movie subtitles could be considered a rich source of informative information for various movie analysis tasks. | ||
| کلیدواژهها | ||
| Subtitle analysis؛ Movies graph؛ Graph Analysis، Graph entropy؛ Graph homophily | ||
| مراجع | ||
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