Recommender Systems - Groups

MovieLens 1M dataset

The dataset used in this paper is the MovieLens 1M dataset, which contains a 1M 1-5 star ratings by 6,040 users for 3,952 movies.

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Deep Forgetful Novelty-Seeking Model

A Deep, Forgetful Novelty-Seeking Movie Recommender Model

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ColdNAS: Search to Modulate for User Cold-Start Recommendation

Making personalized recommendation for cold-start users, who only have a few interaction histories, is a challenging problem in recommendation systems.

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MovieLens-100K and MovieLens-ml-latest-small

The MovieLens-100K and MovieLens-ml-latest-small datasets are used to evaluate the effectiveness of the proposed detection method.

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Anime

The dataset is a two-mode tensor depicting binary (user, anime) preferences. The tensor contains 1, 300, 160 observed entries, of size 25, 838 × 4, 066.

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MovieLens1M, Anime

A dataset of movie ratings, a dataset of anime ratings.

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A First Look at Selection Bias in Preference Elicitation for Recommendation

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Content Management System (CMS) Dataset

The dataset used in this research work is a company's content management system (CMS) dataset. It has two significant entities: posts and users, which consists of 250 users, and...

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bAbI Movie Dialog dataset

The bAbI Movie Dialog dataset is a synthetic dataset containing elementary tasks such as selecting an answer between one or more candidate facts, answering yes/no questions,...

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Amazon dataset

The Amazon dataset is used to evaluate the performance of the proposed approach. It consists of 2000 users, 1500 items, 86690 reviews, 7219 number ratings, 3.6113 average number...

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Simplified Simulated Dataset

A simplified simulated dataset showing varying user preferences over time and how this can be evaluated with static and dynamic learning algorithms.

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STMV1

Offline evaluations of recommender systems attempt to estimate users’ satisfaction with recommendations using static data from prior user interactions.

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AZM5

Offline evaluations of recommender systems attempt to estimate users’ satisfaction with recommendations using static data from prior user interactions.

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ML1M

Offline evaluations of recommender systems attempt to estimate users’ satisfaction with recommendations using static data from prior user interactions.

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Music Corpus

The dataset used for term clustering to build a modular ontology according to core ontology from domain-specific text.

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Netﬂix

A dataset for interactive recommender systems, used to evaluate the proposed Tree-structured Policy Gradient Recommendation (TPGR) framework.

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Scholarly Paper Recommendation via User's Recent Research Interests

The dataset used in this paper is a collection of research papers, and the authors propose a scholarly paper recommendation system.

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Interactive Research Paper Recommender System

The dataset used in this paper is a collection of research papers, and the authors propose an interactive research paper recommender system.

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Large-Scale Recommendation System Dataset

The dataset used in the paper is a large-scale recommendation system dataset, which includes user profiles and user history behavior sequences.

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Epinions

The Epinions dataset is a large-scale opinion mining dataset. It contains 1 million user-item interactions and is widely used for evaluating the performance of recommender systems.

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62 datasets found