Common challenges in information retrieval (IR) include handling large and diverse datasets, ensuring the accuracy and relevance of search results, and addressing user query ambiguities. IR systems often struggle with retrieving documents that accurately meet user needs, especially in complex, subjective, or vague queries.
Another challenge is dealing with noisy, incomplete, or biased data, which can lead to suboptimal retrieval results. Ensuring diversity in search results, especially when the query has multiple interpretations or is related to trending topics, is also a significant hurdle.
Furthermore, as IR systems increasingly operate across multilingual datasets, addressing issues related to language differences, translation, and cultural context has become more complex.