Scalability in IR refers to the system’s ability to handle increasing amounts of data and user queries efficiently. A major challenge is indexing large datasets in a way that ensures fast retrieval times without sacrificing accuracy. As datasets grow, traditional indexing methods may become slower or less effective.
Another challenge is ensuring the IR system can handle spikes in query volume without degrading performance. Distributed systems and parallel processing are typically used to address this, but they introduce complexities related to load balancing, fault tolerance, and data consistency.
Additionally, maintaining search quality as the dataset scales requires continuous monitoring and adjustments to ranking algorithms, which can become computationally expensive with large data volumes.