What are some of the challenges and opportunities of relevance feedback in web search?

1 How relevance feedback works

Relevance feedback works by collecting explicit or implicit feedback from the user, and using it to modify the original query or the ranking algorithm. Explicit feedback is when the user explicitly indicates which documents are relevant or irrelevant, for example by clicking on a button or rating a document. Implicit feedback is when the user's behavior or actions imply their preferences, for example by clicking on a link, spending time on a document, or scrolling down a page. Relevance feedback can be applied either in an interactive or a non-interactive way. In an interactive way, the user can see the updated results after providing feedback, and can provide more feedback if needed. In a non-interactive way, the feedback is collected in the background, and used to improve the ranking for future queries.

2 Why relevance feedback is important

Relevance feedback is important because it can help to overcome some of the limitations of web search, such as the vocabulary mismatch, the ambiguity, and the diversity of user needs. Vocabulary mismatch is when the user's query does not match the terms used in the documents, or when different terms have the same meaning. Relevance feedback can help to expand or refine the query with synonyms, related terms, or more specific terms, and to filter out irrelevant documents. Ambiguity is when the user's query or the documents have multiple meanings or interpretations, depending on the context or the domain. Relevance feedback can help to disambiguate the query or the documents, and to rank them according to the user's intended meaning. Diversity of user needs is when different users have different preferences, expectations, or goals for the same query. Relevance feedback can help to personalize the ranking of the documents, and to adapt to the user's profile, behavior, or feedback history.

5 How to implement relevance feedback in web search

If you want to implement relevance feedback in your web search application, you'll need to think about the type of feedback and the mode of feedback. You could use explicit or implicit feedback, or a combination of both. Additionally, you'll need to decide if you want to use interactive or non-interactive feedback. Furthermore, when it comes to the algorithm of feedback, you'll need to decide how to interpret and integrate the feedback into your query or ranking algorithm. You could use methods such as query expansion, query reformulation, query reweighting, document reweighting, document reranking, or document clustering.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?