76 datasets found

Conversational and question-based recommender systems have gained increasing attention in recent years, with users enabled to converse with the system and better control...

CiteULike is a user-article dataset, where each article has a 300-dimension tf-idf vector. XING is a user-view-job dataset where each job is described by a 2738-dimension...

The dataset used in the paper is a collection of implicit interactions gathered from various sources, including social networks and online communities.

The dataset used in the paper is a collection of explicit interactions gathered from various sources, including music websites, movie ratings, book clubs, social networks, and...

The dataset used in the paper is a collection of implicit interactions gathered from various sources, including music websites, movie ratings, book clubs, social networks, and...

Movielens-100k dataset is a network of user-movie ratings

The dataset used in the paper is the Yelp Challenge Dataset and the IMDB corpus of movie reviews.

The dataset used in the paper is a collection of explicit interactions gathered from various sources, including music websites, movie ratings, book clubs, social networks, and...

The dataset consists of data from seven participants whose response times ranged from 4 to 429 seconds. The dataset includes information about the participant, the response...

The Yahoo dataset used for training and testing the proposed model, containing leaked passwords.

The Book-Crossing dataset is a book rating dataset that contains rating records of books by users from the Book-Crossing community.

The KuaiRec-big dataset is a recommender system dataset jointly released by the University of Science and Technology of China and the Kuaishou Community Science Research...

The dataset used in this paper for recommendation system, it is a bipartite graph of user-item interactions.

The dataset used in the paper is a user-item bipartite graph, where each user and item is represented as a node, and the edges between them represent the interactions between...

The Yelp dataset challenge contains reviews and images of restaurants, with the goal of recommending images for each review.

Click-Through Rate (CTR) prediction plays a core role in recommender systems, serving as the final-stage filter to rank items for a user. The key to addressing the CTR task is...

The Flixster dataset is a collection of user-item interactions.

The Yahoo! Music dataset is a collection of user-item interactions.

MovieLens-100K and MovieLens-1M datasets are used for performance testing of comparative experiments.

The MovieLens dataset contains questions answerable using Wikidata as the knowledge graph, focusing on questions with a single entity and relation.