iSynchronizer
Nourah AlRossais, Daniel Kudenko⋆ · 2018
The growing popularity of e-commerce has ignited the interest of the research community in e-commerce application research and development. For this purpose, variety of applications and resources such as MovieLens and IMDb datasets have been utilized, which present a rich database of items (movies), their attributes and ratings. It is a common practice to utilize both MovieLens and IMDb datasets to produce richer dataset about items and user-generated information such as tags and ratings for conducting research in recommender systems domain. Moreover, the combined dataset contains contextual feature represented by timestamps. However, dealing with a big chunk of the IMDb dataset and its integration with MovieLens dataset remains a challenge due to the various issues such as resource constraints and broken links. To address these issues, a more complex procedure has to be adopted for the integration of both datasets. Hence, this paper introduces iSynchronizer, which is an open-source tool for synchronizing MovieLens and IMDb datasets autonomously with minimum effort. Moreover, the tool includes code to generate a matrix of item features and user preferences over item features from the raw integrated dataset.