Responde en un ingles formal el siguiente correo indicando que son correctas las revisiones realizadas por los autores. El texto del correo es el siguiente: "Comment 1:

The proposal presented in the article “Attentive Review Semantics-Aware Recommendation Model for Rating Prediction” is intriguing and provides a valid solution to a known issue. However, there are several areas that require improvement:

The introduction needs restructuring. It is suggested that the authors present and describe the methodology of the proposal in a separate section of the article.

In addition, the exemplification appearing in the introduction could be relocated elsewhere.

Response 1:

Thank you for the constructive feedback. First, we have incorporated your suggestions and simplified the methodology section to enhance readability. The detailed description of the proposed methodology was revised in the problem definition section. Please see lines 81~91 and 255~263 on pages 3~4 and 7 for corrections.

Second, we apologize for the exemplification, this study aims to propose a recommender system based on considering the relevance of the review content to the items. Therefore, we decided to keep the exemplification in the introduction for a direct example consistent with our idea. Even though, we still replaced Table 1 with a figure and redesigned the components to show a clear example. Please see Figure 1 on page 3 for corrections.


Comment 2:

At times, more current bibliographic references are needed. It is recommended to cite more than one work to support certain claims.

It would be beneficial to refer to the current taxonomies of the most relevant recommendation systems in the state of the art.

Response 2:

Thank you for your feedback. Based on your comments, we tried our best to search recommender system-related works and cite recent research to support our claims. Thank you again for your specific insight.


Comment 3:

Furthermore, there should be a discussion on the emergence of Language Models with Attention (LLM) in recommendation systems.

The “Related Works” section should be restructured to make it more appealing to the reader.

Response 3:

Thank you for providing these comments. Based on your feedback, we restructured the section 2.2 in the related works into section 2.2.1 Large Language Models (LLMs), section 2.2.2 Attention Mechanism, and section 2.2.3 Research Gaps and Motivation. In section 2.2.1, we discussed the latest trends in the application of LLMs in the field of recommender system studies with your suggestions. In section 2.2.3, we detailed the research gaps between existing studies and our study. Please see pages 5~7 for corrections.


Comment 4:

In the “Experimental Results and Discussion” section, the authors should discuss the possible causes of the results obtained, not just indicate the results themselves.

Response 4:

We are very grateful for your constructive comments. The original manuscript described the results of each experiment after listing the experimental results. Such parts focus on explaining based on the values and why such results are shown. Based on your comment, we realized the manuscript lacked content related to the findings. Therefore, we revised section 7 to discuss the experimental findings in more detail, not only the simple result explanations but also the implications and limitations of this study. Please see line 574~608 on page 16~17 for corrections.

Thank you again for your helpfulness and kindness."