This paper introduces a model for product recommendation grounded in customer behavior within e-commerce platforms, which incorporates purchase history, ...

Jun 4, 2023 · So, we should get significant improvement if we use OpenAI's Word Embedding Model to make a Content-Based Filtering recommendation system.

Our model utilizes a beautiful state-of-the-art multi-lingual embedding creation method, based on a pre-trained version of BERT from the sentence_transformers ...

In this paper, we describe the development of a content-based grant recommendation system that recommends funded grants to researchers.

Jun 12, 2018 · The method leverages past user interactions with items and their attributes to compute low-dimensional embeddings of items. Specifically, item ...

Dec 21, 2023 · This survey covers embedding methods like collaborative filtering, self-supervised learning, and graph-based techniques.

Oct 26, 2021 · In this post, we'll do a quick comparison of the different algorithms and share our experience adopting Item2Vec to improve the quality of recommendations at ...

Oct 16, 2024 · Enhancing Product Recommendations with FastText. The FastText model is an efficient and widely used implementation for learning word embeddings ...

We show that based on the proposed model, it is possible to predict which recommender will provide the most precise recommendations to a user. The theoretical ...

Aug 4, 2022 · As word embedding aims to capture the similarity between words, product embeddings aim to capture affinities between products. This is done by ...