Content-Based Table Retrieval for Web Queries
Table 2: Results on the WebQueryTable dataset.
['Setting', 'MAP', 'P@1']
We compare between different features for table ranking. An intuitive baseline is to represent a table as bag-of-words, represent a query with bag-of-words, and calculate their similarity with cosine similarity. Therefore, we use the BM25 score which is calculated in the candidate table retrieval step. This baseline is abbreviated as BM25. Results from This results reflect the necessary of taking into account the table structure for table retrieval. Furthermore, we can find that combining designed features and neural networks could achieve further improvement, which indicates the complementation between them.