Our recommender system would recommend users a list of interesting exhibitors based on associations that mined from the web server logs. The recommendations are ...

This work shows that the recommender system would recommend users a list of interesting exhibitors based on associations that mined from the web server logs ...

Our recommender system would recommend users a list of interesting exhibitors based on associations that mined from the web server logs. The recommendations are ...

The study highlights the importance of feature selection based on conditional entropy in automated e-commerce recommender systems (Sharma & Sadagopan, 2022).

Oct 22, 2024 · This paper evaluates the machine learning model for exhibition recommendations given to visitors through virtual tour applications. Exploring ...

In this paper, we formalize this concept by providing a new formal definition of unexpected recommendations and differentiating it from various related concepts ...

We introduce the Framework for Evaluating Recommender systems (FEVR), which we derive from the discourse on recommender systems evaluation.

Collaborative filtering (CF) techniques have been proven to called interesting rules. ... (at least to some extent) with the target user's preferences.

Oct 31, 2022 · The paper presents a large-scale analysis of the performance of existing recommender system algorithms on multiple (85) datasets on 315 ...

Aug 14, 2024 · In this paper, we investigate the Top-N implicit recommendation problem and focus on optimizing the benchmark recommendation algorithm commonly used in ...