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LibraryThing has several ways to suggest books you might like to read. Recommendations based on single books are available on each work's recommendations section or via the Book Suggester; you can view those recommendations even if you don't have a book in Your library.

If you want recommendations based on lots of books in Your library, then you'll appreciate the three types of recommendations linked from your Profile:

  • Automatic Recommendations
  • Member Recommendations
  • Unsuggestions

Although you can access your full list of recommendations from your Profile, new additions to your Automatic Recommendations and Member Recommendations lists also show up on your Home page.


LibraryThing Recommendations

Automatic Recommendations compares Your library (and selected other Collections) to the thousands of other member libraries on LibraryThing and provides a list of some books you might find interesting. Unless you use the Collections feature to organize your books, all of the books you add to LibraryThing are added to Your library and will be used to generate Automatic Recommendations. If you use other Collections, you can choose with a checkbox whether or not to include those books in Automatic Recommendations. See the Collections page for more information on how to include or exclude a Collection from Recommendations.

What are these recommendations based on?

  • books that have the same subjects as other books in Your library (including tags and Library of Congress subject headings)
  • books in the libraries of other LibraryThing members who share books with you

By the magic of LibraryThing, you can get recommendations even if you don't tag your own books. There's an important caveat to make, though. Recommendations are based on similar subjects or tags, but tags don't always give clues as to whether you will agree with a viewpoint in a book. For instance, books about a specific religion might praise it, or they might criticize it. You might even be recommended books you find offensive. What the recommendations feature can do, however, is to help you discover books about subjects you've found interesting, because you already have books about the same topic.

Recommendations can't take into account (by ratings) whether you liked a book in Your library. If you don't want all of your books to generate Recommendations, the best thing to do is to create a special Collection; see the notes section for more information. Also see the notes section for more information about how Automatic Recommendations are generated.

Member Recommendations

Member Recommendations gathers in one place recommendations LibraryThing members have made for any of the books in Your library (and selected other Collections). More on this feature may be found here.


  • Unsuggestions is based on the LibraryThing Unsuggester. The Unsuggester analyzes the statistics of "people who have X also have Y" and turns them upside down, finding the books least likely to coincide in a member's library. The Unsuggester makes some mistakes, particularly owing to work-combinations. Your Unsuggester looks at your library and provides a list of books that probably wouldn't strike your fancy. If you'd like to shake up your world and try something really different, your Unsuggester is a great place to start!

Notes and Frequently-Asked Questions

How does the computer calculate Automatic Recommendations?

While the specific method is a closely-guarded secret, the computer algorithm generates recommendations based on patterns of book co-occurrence in libraries, subject headings, and tags. There are rumours that the Early Reviewer algorithm accepts brie, but the Automatic Recommendations algorithm cannot be so easily swayed!

Warning: statistics are involved! For example, let's say there are 1000 LT members. 500 of them have book X, and 100 of them have book Y. If these two books were unrelated and entirely randomly distributed, you would expect 50 members to have both. That is, if everything is random, 1/2 of any subset of LT members should have book X, so if the subset is "members with book Y", then we would expect the overlap to be 1/2 * 100 = 50. If significantly more than 50 people own both X and Y, that indicates that ownership is not random, and that people interested in one book would be interested in another.

This algorithm also takes into account similar subject headings and tags for books in Your library. It uses subject headings assigned by libraries and the most common tags applied to your books by all LibraryThing members, so even if you don't tag, you can still generate recommendations. The computer adjusts recommendations (weights) based on tag/subject obscurity - so the fact that two books share the widely-used tag "fiction" counts less towards making them similar than if they share the tag "books about books" or "dystopian steampunk". If you share a lot of unusual books with another LT member, you may find that the algorithm suggests other items from these similar libraries.

When the computer generates your recommendations, it has to make these calculations for all of the books in your library compared to all other books - which is why it can take a while to load!

Why don't recommendations take rating into effect?

Doing book-to-book, library-to-library comparisons to get recommendations is already computationally expensive. Adding ratings to the mix would exponentially increase the number of calculations, and hence the time, that the recommendations engine has to do its job. Additionally, only about 10% of books on LibraryThing have ratings - either people haven't read them yet, don't remember them well enough to rate them, or just don't bother rating any books in their catalogs.

How can I help the computer generate better recommendations?

Recommendations are based on what books you own or have read and what subjects you find interesting. This suggests two ways to improve recommendations: include more books and more subjects. How do you do that? It may sound obvious, but recommendations will be much better once you've entered all of your library, so finish entering your books! If there are books that are your favorites, but you don't consider them part of Your library, you can add them to your Read but Not Owned Collection; some people do this for books they check out from the public library.

Creative use of tags is limited only by your imagination, and unique tags can help those with special interests find books. This can expand beyond just the subjects in a book. For instance, J. R. R. Tolkien and C. S. Lewis were in a social/literary club called the "Inklings," and some people use this tag. Maybe you have a passion for "African-American science fiction." With as many LibraryThing members as there are, unusual tags can spread and generate interesting results.

How can I stop getting all these Star Wars/Comic/Children's/Unwanted Topic recommendations?!

To keep certain types of books from overwhelming your recommendations list, create a new Collection--you can call it recommendations or some other name--and add only the desirable books to that collection. Check the "include in recommendations" box for that new Collection. Then change the Your library collection settings to remove the "use for recommendations" checkmark. See Collections for more information.

Why do I get recommendations for books I already have?

There are two main reasons you might get recommendations for books you have listed in LibraryThing.

  1. The first possible reason is what's known as the Part/Whole problem. The system can't recognize that a box set or an omnibus edition includes all of the parts within it. This work-within-a-work problem will be fixed in a later improvement to LibraryThing.
  2. The second possible reason is that the record for your book hasn't properly combined with other copies of the same work. If you don't feel comfortable tackling a work combination, the Combiners! group can help you sort this out.
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