MIcrosoft News Dataset (MIND) is a large-scale dataset for news recommendation research. It was collected from anonymized behavior logs of Microsoft News website. The mission of MIND is to serve as a benchmark dataset for news recommendation and facilitate the research in news recommendation and recommender systems area.
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ReDial (Recommendation Dialogues) is an annotated dataset of dialogues, where users recommend movies to each other. The dataset consists of over 10,000 conversations centered around the theme of providing movie recommendations.
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This dataset contains product reviews and metadata from Amazon, including 142.8 million reviews spanning May 1996 - July 2014.
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Coached Conversational Preference Elicitation is a dataset consisting of 502 English dialogs with 12,000 annotated utterances between a user and an assistant discussing movie preferences in natural language. It was collected using a Wizard-of-Oz methodology between two paid crowd-workers, where one worker plays the role of an 'assistant', while the other plays the role of a 'user'.
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Dataset of restaurant reviews from TripAdvisor that includes images and texts uploaded in reviews by users. Reviews in six different cities are included: Gijón (Spain), Barcelona (Spain), Madrid (Spain), New York City (USA), Paris (France) and London (United Kingdom). In the original publication, the following task is proposed: Can we explain, using the existing image or text from a different user, why a given restaurant was recommended to a certain user?
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E-ReDial is a conversational recommender system dataset with high-quality explanations. It consists of 756 dialogues with 12,003 utterances, each with 15.9 turns on average. 2,058 high-quality explanations are included, each with 79.2 tokens on average.
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Description This Dataset contains review information on Google map (ratings, text, images, etc.), business metadata (address, geographical info, descriptions, category information, price, open hours, and MISC info), and links (relative businesses) up to Sep 2021 in the United States.
A large scale, C2C marketplace e-commerce dataset.
X-Wines is a consistent wine dataset containing 100,646 instances and 21 million real evaluations carried out by users. Data were collected on the open Web in 2022 and pre-processed for wider free use. They refer to the scale 1–5 ratings carried out over a period of 10 years (2012–2021) for wines produced in 62 different countries.
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