推荐系统学习资料、源码、及读书笔记

A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECCV2022.

Opinion recommendation is a task, recently introduced, for consistently generating a text review and a rating score that a certain user would give to a certain product, which has never seen before. Input information driving recommendation is text reviews and ratings for this product contributed by other users and text reviews submitted by the user under consideration for other products. The aforementioned task faces the same problems emerging in text generation using neural networks, namely repetition and specificity. In this paper, it is experi- mentally demonstrated that by employing coverage loss during training, repetition is reduced without adding extra parameters. Furthermore, the amount of repetition in the generated text review is defined as a measure of the captured information. Such measure is used to improve rating score prediction significantly during testing.

Basic Implementation of Recommender System.

Collection of algorithms to compute diversity between elements and identify diverse element collections within a dataset. Technologies for Information Systems course project (A.Y. 2018/2019) at Politecnico di Milano.

A collection of neighborhood based collaborative filtering variants

Implementation of a Recommender system by using Steam Dataset corpus.

Binary classification using kNN, neighborhood and perceptron from scratch in python. Using the stressed/Not Stressed dataset