Addressing Bias in Information Retrieval

Addressing Bias in Information Retrieval
English | 2026 | ISBN: 3032241448 | 86 Pages | PDF EPUB (True) | 2.4 MB
Online search engines are an essential tool for seeking information, but results returned from these search engines can contain undesirable forms of bias with respect to protected attributes such as gender or race. These biases can exist due to the word embeddings used by search engines, the design of re-ranking algorithms, the development of retrieval algorithms, or a variety of other reasons. Classical information retrieval (IR) methods, such as query recommendation or query expansion, were designed to produce the most relevant results. However, if such biases are present in the system, then these methods will also deliver biased results.