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We derive a method to enhance the evaluation for a text-based Emotion AwareRecommender that we have developed. However, we did not implement a suitableway to assess the top-N recommendations subjectively. In this study, weintroduce an emotion-aware Pseudo Association Method to interconnect disjointedusers across different datasets so data files can be combined to form a moreextensive data file. Users with the same user IDs found in separate data filesin the same dataset are often the same users. However, users with the same userID may not be the same user across different datasets. We advocate an emotionaware Pseudo Association Method to associate users across different datasets.The approach interconnects users with different user IDs across differentdatasets through the most similar users' emotion vectors (UVECs). We found themethod improved the evaluation process of assessing the top-N recommendationsobjectively.

international journal on natural language computing (print)/international journal on natural language computing

An Affective Aware Pseudo Association Method to Connect Disjoint Users  Across Multiple Datasets -- An Enhanced Validation Method for Text-based  Emotion Aware Recommender