RARD II: The 2nd Related-Article Recommendation Dataset
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'We introduce RARD II: The 2nd Related-Article Recommendation Dataset from the recommendation-as-a-service provider Mr. DLib (http://mr-dlib.org). The RARD II dataset encompasses 94m recommendations, covering an item-space of 24m unique items. RARD II provides a range of rich recommendation data, beyond conventional ratings. Information includes details on which recommendation approaches were used (e.g. content-based filtering, stereotype, most popular), what types of features were used in content based filtering (simple terms vs. keyphrases), where the features were extracted from (title or abstract), and the time when recommendations were delivered and clicked. In addition, the dataset contains an implicit item-item rating matrix that was created based on the recommendation click logs. Compared to its predecessor RARD I, RARD II contain' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["dataset","digital libraries","recommender system","related-article recommendations","research-paper recommender system"]} <|eot_id|>
 Here is the Description of a dataset. Description:'We introduce RARD II: The 2nd Related-Article Recommendation Dataset from the recommendation-as-a-service provider Mr. DLib (http://mr-dlib.org). The RARD II dataset encompasses 94m recommendations, covering an item-space of 24m unique items. RARD II provides a range of rich recommendation data, beyond conventional ratings. Information includes details on which recommendation approaches were used (e.g. content-based filtering, stereotype, most popular), what types of features were used in content based filtering (simple terms vs. keyphrases), where the features were extracted from (title or abstract), and the time when recommendations were delivered and clicked. In addition, the dataset contains an implicit item-item rating matrix that was created based on the recommendation click logs. Compared to its predecessor RARD I, RARD II contain' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
We introduce RARD II: The 2nd Related-Article Recommendation Dataset from the recommendation-as-a-service provider Mr. DLib (http://mr-dlib.org). The RARD II dataset encompasses 94m recommendations, covering an item-space of 24m unique items. RARD II provides a range of rich recommendation data, beyond conventional ratings. Information includes details on which recommendation approaches were used (e.g. content-based filtering, stereotype, most popular), what types of features were used in content based filtering (simple terms vs. keyphrases), where the features were extracted from (title or abstract), and the time when recommendations were delivered and clicked. In addition, the dataset contains an implicit item-item rating matrix that was created based on the recommendation click logs. Compared to its predecessor RARD I, RARD II contain
dataset; digital libraries; recommender system; related-article recommendations; research-paper recommender system