Optimizing Component Combination in a Multi-Indexing Paragraph Retrieval System
This work addresses the challenge of enhancing retrieval performance in question answering systems, but it is incremental as it focuses on optimizing existing components rather than introducing new methods.
The paper tackled the problem of optimizing component combinations in a multi-indexing paragraph retrieval system by using a heuristic algorithm to weight components, resulting in improved result quality and identification of valuable components, as evaluated on a Question Answering dataset.
We demonstrate a method to optimize the combination of distinct components in a paragraph retrieval system. Our system makes use of several indices, query generators and filters, each of them potentially contributing to the quality of the returned list of results. The components are combined with a weighed sum, and we optimize the weights using a heuristic optimization algorithm. This allows us to maximize the quality of our results, but also to determine which components are most valuable in our system. We evaluate our approach on the paragraph selection task of a Question Answering dataset.