Search / NLP · CS 410 / information retrieval
Information Retrieval
Search, indexing and ranking experiments
Built information-retrieval experiments with Pyserini to understand how search systems turn a document collection into ranked results. The work covered indexing, querying, ranking, and evaluating whether the returned documents were actually relevant.
Built retrieval pipelines with Pyserini.
Tested how indexing and ranking choices affect search results.
Kept document preparation, retrieval, and result evaluation as separate stages.
A search system can return results correctly while still ranking poor matches highly, so relevance evaluation matters beyond simply making the query run.
Built hands-on experience with the core pieces of a text search and ranking pipeline.