How can recommender systems foster exploration and discovery among users?

1 Diversity in recommender systems

Diversity refers to the degree of variety or difference among the items recommended to a user. Diversity can be measured in different ways, such as the dissimilarity of item features, categories, or ratings. A diverse recommender system can help users avoid the filter bubble effect, where they are exposed to only a narrow range of items that confirm their existing preferences and opinions. A diverse recommender system can also increase users' curiosity, interest, and trust in the system, as well as their willingness to try new things.

2 Serendipity in recommender systems

Serendipity refers to the occurrence of unexpected or surprising discoveries that are relevant and valuable to the user. Serendipity can be seen as a special case of diversity, where the recommended items are not only different from the user's usual choices, but also have a positive impact on the user's mood, knowledge, or behavior. A serendipitous recommender system can help users discover hidden gems, learn new things, or find solutions to their problems, that they might not have found otherwise.

3 Challenges of balancing diversity and serendipity with user satisfaction

One of the main challenges of designing recommender systems that foster exploration and discovery is to balance them with user satisfaction and engagement. User satisfaction is the degree to which the user is happy with the recommendations and the system's performance. User engagement is the degree to which the user interacts with the system and the recommended items. Both user satisfaction and engagement are influenced by the accuracy and relevance of the recommendations, as well as the user's expectations and goals. However, accuracy and relevance are not always aligned with diversity and serendipity, as they might lead to overfitting or homogenization of the recommendations. Moreover, user satisfaction and engagement are not always aligned with each other, as some users might prefer more exploratory or more confirmatory recommendations, depending on their context and mood.

4 Opportunities of designing recommender systems that foster exploration and discovery

Despite the challenges, there are also numerous opportunities for designing recommender systems that foster exploration and discovery among users. Incorporating user feedback and preferences into the recommendation process, such as ratings and reviews, can help the system learn more about the user's interests, needs, and goals. Providing explanations or transparency of the recommendations can help the user understand the logic and rationale behind them. Offering control or personalization options for the user, such as filters or sliders, can help customize the level of diversity or serendipity they want to see in the recommendations. Leveraging contextual or situational factors can tailor the recommendations to the user's current state and environment. Introducing novelty or surprise elements, like rewards or incentives, can motivate users to explore and discover new items while increasing their enjoyment and satisfaction.

5 Examples of recommender systems that foster exploration and discovery

Recommender systems are used across various domains and platforms to help users explore and discover new content. For instance, Spotify's Discover Weekly playlist uses collaborative filtering and natural language processing to generate personalized playlists of songs that the user might like but has not heard before. Netflix's Shuffle Play feature randomly selects a movie or show based on the user's profile and viewing history. Amazon's Interesting Finds section curates a collection of quirky products that the user may find appealing. Goodreads' Recommendations page utilizes a hybrid approach of content-based and collaborative filtering to suggest books that the user might enjoy. Lastly, Pinterest's Explore tab employs deep learning and computer vision to show pins that are similar to the user's saved pins, but with some variations or differences.

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?