Which parameter is used to define the number of closest vector candidates considered during HNSW index creation?

The correct parameter used to define the number of closest vector candidates during HNSW (Hierarchical Navigable Small World) index creation is EFCONSTRUCTION. This parameter plays a critical role in determining the efficiency and accuracy of the index by controlling how many closest neighbors are taken into account when building the graph structure used for nearest neighbor searches.

In HNSW, during the construction phase, the algorithm needs to connect new nodes to existing nodes based on their proximity. EFCONSTRUCTION sets the number of nearest neighbors that the construction algorithm will consider for each newly added node. A higher value for EFCONSTRUCTION results in a more densely connected graph, which can improve search accuracy but may increase the index creation time and memory usage. Conversely, a lower value may speed up the construction process but could lead to less effective searches due to fewer connections.

The other parameters mentioned, while relevant to different aspects of the vector search process, do not specifically control the number of closest vector candidates in the construction of the HNSW index. Consequently, EFCONSTRUCTION is the key parameter for this particular aspect of the HNSW indexing strategy.