Affect Enriched Word Embeddings for News Information Retrieval
Table 3: Query expansion experiments on NYT
['Query expansion experiments on NYT Model', 'Query expansion experiments on NYT MAP', 'Query expansion experiments on NYT NDCG']
We observe that classic BM25 and query likelihood retrieval models provide better NDCG than almost all the models except some of the affect enriched ones. This is in line with what we observed for the ranking task on the same dataset. A GloVe retrofitted affect enriched embedding model is the top performing one for both NDCG and MAP.