Apologizes in advance, if this question is so basic,


I have read this paper and noticed that Information Retrieval can be identified as a field of study whereas Recommender Systems are a technology.

Information retrieval addresses the information needs of users by delivering relevant pieces of information but requires users to convey their information needs explicitly. In contrast, recommender systems offer personalized suggestions of items automatically. Ultimately, both fields help users cope with information overload by providing them with relevant items of information.

I have some doubt about the concept and differences between these two. Therefore, I tried to formulate my research question as follows:

Given the information retrieval field as an umbrella term, my goal is to conduct the research on the state-of-the-art recommendation system (technology) which is able to retrieve the best TOP-N (N=5, 10, 20 , ...) search matches, in a dataset,


  1. Is this a legitimate statement in Data Science or AI community?
  2. if not, is there a better way to formulate the research question to address recommendation systems?
  • $\begingroup$ Is this for a Master project or similar? If yes this is fine imho (the phrasing could be a bit better but that's ok). What you describe is just the standard search task with a query, afaik recommender systems also include other cases like predicting items that the user likes based on their past behaviour or other users. I would suggest to make the research question more specific wrt to the particular task and/or domain of application, because this is a quite broad topic. $\endgroup$
    – Erwan
    Oct 24, 2022 at 15:02


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