What happens when documents are included in the training set?

When documents are included in the training set, they may be used for conceptually relevant indexing. This means that these documents can help the system understand the context and meaning of similar documents in the dataset, enabling more accurate and relevant results during the indexing process. By analyzing the content and structure of the included documents, the system learns to identify patterns and relationships that can guide how other documents are indexed.

This training enhances the system's ability to recognize and tag documents based on their conceptual similarities, ultimately improving the retrieval and relevance of search results. This process is critical in fields such as eDiscovery, where understanding the context behind documents is essential for effective case management.

The other options do not accurately reflect the role of documents in the training set. For instance, including documents in the training set does not mean they are permanently saved in the index, nor does it lead to their exclusion from future searches or influence the ranking of all documents uniformly. The focus is on how these documents can aid in the broader indexing process rather than on the mechanics of document storage or retrieval.