171–180 of 205 posts
I love goodreads, but I've wished for so long for two things way more basic than good recommendations which I don't really care about (except the finding people with similar ratings, I would kill for that): - Proper search engine (all books with x+ ratings, rated y+ start, in genre z). From what I've heard one has to scrape the site to get any useful information. - Forbidding rated reviews before release dates. This…
The status quo regarding Goodreads and it's position in the industry is really interesting. There is not a single competent alternative to Goodreads, yet Goodreads just sucks! As simple as that, the UI is horrible, the UX is disgusting, the perfomance is that of toaster and still people are using it. I personally am using it for the last 5 years while continuously searching unsuccessfully for alternatives. If you thi…
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Can we have half stars or quarter stars? I read a lot of books, and choosing full-star 1 to 5 makes the ratings pretty useless for people who read a lot. My internal rankings are: 1 hated it/was offended/didn't finish 2 disliked it/likely didn't finish 3 finished but it was a struggle 4 finished/enjoyed/had some issues 5 finished fast/really enjoyed/may or may not have still had issues. If I look back at the 30 to 50…
Why take 60% of the rating space up by negative ratings? It seems like what you really care about is degrees of goodness. An alternative approach: 1 - I disliked it. 2 - It's OK 3 - This is good 4 - This is great 5 - This is a must-read
After reading and heavily agreeing with this post, I came to the conclusion that either goodreads is not really trying, or -more likely- the data is just not good enough to make decent recommendations. There are so many biases in the review data that are impossible to fix in any kind of sparse matrix recommendation algorithm. For those who want to try anyway, it might be worth downloading an existing dataset (1) (104…
the problem is that when you step out of genre fiction, you cant just recommend a book with a similar plot or setting, it needs to have a similar style of writing and sensibility and thats very hard to determine. the best way is friending/following people and learning their tastes compared to yours e: if you go to a specific book and look up similar books, goodreads actually does a pretty good job https://www.goodrea…
If only goodreads could somehow find others who like the same things you do and use it for recommendations!
Joking aside, they might already be doing that, but if so, they suck at it. They have enormous datasets of people and their tastes, yet their recommendations always seem to be simply matching genres that you happened to like a book from. You liked Watership Down? Here are 10 other books with talking animals!
If you and I can successfully identify people we share tastes with, then goodreads should be able to, too, they have even more data to base this on.
Haven't used it myself since it's in beta but I have been keeping my eyes on this for a while: https://beta.readng.co/ , https://twitter.com/readngco
Hi, I'm building this! Thanks for sharing. It's pretty basic right at the moment and we've a lot left to build (largely a reading list only, we've got more in the works) – but here's my profile as a preview, since our marketing site & messaging needs a bit of work: https://beta.readng.co/user/joe
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I downvoted you but I feel bad for not explaining why. One of my memories: Being pulled into a side office and grilled for a half hour for posting a similarly harmless statement to HN. So your comment triggered mild PTSD. It's not your place as an individual employee to post about your employer. You work in a team setting. If the team decides it's appropriate to post to HN, then that's fine. But you alone do not get…
What? You are suggesting that a person is unable to share his personal experiences and opinions unless their employer agrees? Obviously this may damage the company, but personally I have no sympathy for a company worth billions of dollars who is not known for their fair treatment of workers at all. I see nothing immoral in the original commenter releasing this information.
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Err, I disagree with your assessment of Youtube's recommendation engine being "poor." It is probably the most powerful recommendation engine in the world. 5 billion YT videos, comprising 1 billion hours, are watched every day, a meteoric rise ever since they improved the recommendation engine. That recommendation engine has also been accused of contributing to the rise in polarization and conspiracy theories world-wi…
Part of what makes YouTube’s recommendation algorithm so powerful is that it doesn’t necessarily have to be very good. I scrolled through my recommendations just now and only found one video after scrolling through fifteen that I was interested in watching — but that’s fine, since it’s easy to decide if you might like a video based on its title, thumbnail, and creator. However, if YouTube was as good at recommending…
When I see a book recommendation, I read the associated review (if it has one), read other people's reviews, look at the author and the blurb, and, yes, even the cover.
That tells me much more than a YouTube thumbnail, with only a little more time (but of course I'm going to put more time into choosing a book that might take me two weeks to finish). Indeed, my initial filter is probably much the same as a YouTube thumbnail: I skim past many recommendations based on the genre and author alone.
I think if the Times Book Review always wrote reviews in which 1 out of 15 of them made me thing "I need to get that book," I'd be amazed at how much they "get" me. I wouldn't bother with anything else. Every 15 recommendations lands me another "must-read?" Sign me up!
The problem listed in the article is that Goodreads is no where near 1 out of 15.
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Why take 60% of the rating space up by negative ratings? It seems like what you really care about is degrees of goodness. An alternative approach: 1 - I disliked it. 2 - It's OK 3 - This is good 4 - This is great 5 - This is a must-read
This is exactly the way the current Goodreads rating is supposed to work (and I'm personally OK with it). But my guesstimate is that for 95% Goodreads users everything below 4 stars means that the book sucks.
Has anybody ever used stack ranking to power book recommendations? Instead of rating books on a scale of 1-5 star you instead rate each book relative to every other book you’ve ever read. Some other factors that I think could be used to create a high quality book recommendation engine on top of stack ranking: number of books read (the top 5 books from someone who has read 200+ books is a stronger signal than someone…
I also can't help but think in graphs, so I could also see horizontal-ish linkages between the stacks as well. Each book, then, could have a number of attributes that get an independent stack ranking for each one, leaving you with a constellation score as well as a focused look at what the book is good at or focused on. I could see it getting unwieldy though.
Thinking through this, maybe genre stacks based on some collapse of attribute ranking scores.