Affect Enriched Word Embeddings for News Information Retrieval
Table 2: Ranking experiments on NYT
['Ranking experiments on NYT Model', 'Ranking experiments on NYT NDCG', 'Ranking experiments on NYT MAP']
We observe that usage of term embeddings doesn’t give benefits in many cases, classic BM25 and query likelihood retrieval models provide better NDCG than almost all the models except the affect enriched ones. A GloVe retrofitted affect enriched embedding model is the top performing one for NDCG measure. On the other hand none of the term embedding ranking could outperform BM25 on the mean average precision measure.