Research On Method Of User Preference Analysis Based on Entity Similarity and Semantic Assessment

The rapidly evolving landscape of Internet technology has led to an increasing interest in smart terminal devices, particularly smartphones, among users. As users interact with these devices, they encounter a range of applications (APPs) with diverse functionalities and consume services according to their individual needs. The service consumption process elicits different emotional experiences from users, which serve as an instinctive reflection of their satisfaction with the service consumption experience. Thus, there is an urgent need to address the challenge of accurately identifying and analyzing users’ emotional experiences, assessing their service experience during service consumption, and exploring the factors that influence their service experience. This research addresses the challenge of accurately identifying and analyzing user emotions during service consumption on smart terminal devices. In the ontology alignment work, we integrate existing methods for edit distance similarity, WordNet similarity, and shared nearest neighbor similarity calculation. We achieve entity alignment in the requirement ontology based on both element and structure. Furthermore, we propose an improved method for calculating WordNet similarity.