Oh man, Literature Map looks really great for finding recs.
That said, I do think book-level might be much more valuable. My first thought for this was Night in the Lonesome October by Roger Zelazny. I haven't read anything else by him yet because my brother informs me his other stuff is entirely different. Looking at Goodreads, I think that qualifies as far from his biggest hit. Is it "more profound?"? Doubtful, but seems likely that you shouldn't group it with his others. I want recommendations based on the book I like, not the author I mostly might-not.
A better example might be how Stephenie Meyer wrote the extremely popular Twilight books, and also The Host which is much less well-known, and better in many respects. Probably qualifies as more profound, too—it's told from the perspective of a parasitic alien. Picture the Yeerks from Animorphs if you read those.)
Whoa, this is a great resource. Never heard of it before, it looks like I'm finally able to get some proper book recommendations. Absolutely loving it.
Weird though that for certain cases it spells English author names with Cyrillic alphabet. Like for instance when I center the graph on "Stanisław Lem", I can see names like George Orwell or Terry Pratchett spelled in Cyrillic. I wonder why.
Stella Gibbons is basically only known for Cold Comfort Farm, but IMO many of her other things are better, although in a different way. My favourite is Pure Juliet, which is a beautifully gentle portrayal of someone who is on the Autism spectrum, written before Autism was really a thing that people talked about.
I am about a week away from launching genre pages, age pages, and filters for all those things. So on the hard-science-fiction page, you can filter to see books in a variety of fun ways and keep following your curiosity:
Which reminds me of https://fivebooks.com/, where people from a particular field are asked their top five book recommendations for a given theme. The interview format is great, and I've picked up a few recommended books along the way.
Lol, I tried it out and put in one of my favorite books, "Liar's Poker" by Michael Lewis and it suggested me a list of "The best novels to help you understand the rich and dysfunctional."
Kind of hacky but I built something similar to apply the page rank algorithm to the authors referenced between books of various topics, here's the result for science:
The visualizations remind me of those in a paper I co-authored a while ago (2009) visualizing ~2400 scientific journal / ~5.7M full-text articles: "Semantic Journal Mapping for Search Visualization in a Large Scale Article Digital Library" https://nrc-publications.canada.ca/eng/view/accepted/?id=63e...
Cool visualization, but the model needs work. The closest book to "Harry Potter and The Chamber of Secrets" is "The Victorian Lady's Guide to Sex, Marriage, and Manners".
I have a theory (after having searched for The Diamond Age) that certain very popular books are ironically not going to be close to similar books because they appear on so many varied reading lists.
There's probably a graph theory phenomena that describes what I'm thinking.
Within our data books like lord of the rings and harry potter are nearly impossible to map for "books like" because they are connected to so many other things. I am working now to fine tune our model, but it has been an interesting challenge.
Yeah basically what I think you're saying is that in a weighted graph, if there are edge weights which are orders of magnitude larger then the average it throws off certain models. Like nearest neighbor.
Basically just prune the top and bottom %1 of weighted edges to get an appropriate average. Would be my guess for a fix.
IIRC you could do pretty okay in Netflix's recommendation contest by ignoring what an individual likes and just recommending the stuff that "everybody" likes.
Hypothesis: the sort of person who reads "The Victorian...", is likely to both like Harry Potter books, and also to review them enthusiastically online. The typical HP child reader, does not review books online. Just an hypothesis.
This looks super cool, but why not use this tool as a non-visual tool to show similar books given a title? As far as I know there aren't many tools for this
Also it would be super cool if we could import out goodreads reading lists and see them on the cluster
This is super cool! I actually have been working on a new book recommendation site (https://braincandy.com) that has a similar-ish (but much smaller scale) visualization for book similarity. It is really interesting how certain genres tend to be much more insular than others and it can be a real challenge to break out of genre boxes when making recommendations. There's so many books out there on the edges and in-betweens that get lost when they don't fit neatly into an existing popular genre, and those indeed can be some of the most interesting.
This is an awesome visualization, I am so impressed :). I've been working on (shepherd.com) with a similar goal to try to bring in human groupings to try to determine book connections via the many angles humans bring to the table. And more serendipity like wandering a local bookstore. I really love how you have done this.
I'm surprised there are enough books published under the category of "Reverse-harem" to make it its own category along with things like "Horror", "Fantasy", "Business", etc.
I was really hoping this would address "Visual Book" like in ふしぎの海のナディア, Fushigi no Umi no Nadia/The Secret of Blue Water. The LaserDiscs used to say "Visual Book" in every episode.
Great animated series (to me), a mix of 20,000 Leagues Under the Sea and the Illuminati.
Do NOT watch it with the english subs. Suffer with the Japanese, even if You don't speak it. You don't need the junk verbal translation, You will still get the main concepts. And Hanson's driving is so much more manaical in Japanese.
I also used more crude algorithms that sort by X, group elements in buckets, and within each, sort by Y. Then we get a grid of elements. The result is less high-quality than with iterative algorithms (and depends on if we sort by X or Y first), but it is hard to beat its simplicity.
I think that people in general don't read "enough", or maybe can't "enough." By that I mean, recommendations based on other people's reading habits aren't going to be as fine tuned as say, recommendations based on people's music listening habits.
I'm astonished by how well this works. I looked for a bunch of books I'd read recently and kept finding other books I've read or want to read near them.
Something's wrong here. I was very excited to explore this, until I searched for "Getting Things Done" by David Allen. A nearby book - "Crippled America: How to Make America Great Again" by Donald J. Trump.
Which is a map of all authors in the world sorted by overlap in readership. I found some of my favorite writers by browsing it.
I wonder which approach is better suited to find something that is spot on to my interests.
When I think of my favorite books, they usually are the most popular books of their authors.
Are there any counterexamples, where an author wrote a book that is more profound than their biggest hit but got overlooked for some reason?