Data & Software
Data
xMIND (A Multilingual Dataset for Cross-lingual News Recommendation)
xMIND is a large-scale multilingual news dataset for multi- and cross-lingual news recommendation. xMIND is derived from the English MIND dataset using open-source neural machine translation (i.e., NLLB 3.3B).
xMIND contains 130K news translated into 14 linguistically and geographically diverse languages, with digital footprints of varying sizes. The goal of xMIND is to serve as a benchmark dataset for news recommendation, and to foster broader research into multilingual and cross-lingual news recommendation, for speakers of both high and low-resource languages.
Access the dataset at this https URL.
Paper: MIND Your Language: A Multilingual Dataset for Cross-lingual News Recommendation
NeMig - A Bilingual News Collection and Knowledge Graph about Migration
NeMig represents a bilingual news collection and knowledge graphs on the topic of migration. The news corpora in German and English were collected from online media outlets from Germany and the US, respectively. NeMIg contains rich textual and metadata information, sentiment and political orientation annotations, as well as named entities extracted from the articles’ content and metadata and linked to Wikidata. The corresponding knowledge graphs (NeMigKG) built from each corpus are expanded with up to two-hop neighbors from Wikidata of the initial set of linked entities.
Access the dataset at this https URL.
Paper: NeMig - A Bilingual News Collection and Knowledge Graph about Migration
Software
NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation
- Code: GitHub
- Documentation: Read the Docs
- Paper: NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation