[{"data":1,"prerenderedAt":1057},["ShallowReactive",2],{"project-45825733":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":5,"maker":10,"posted_at":11,"year":12,"points":13,"comments":14,"rank_in_year":15,"shown_in_year":16,"top":17,"tier":18,"category":19,"subcategory":20,"format":21,"keywords":22,"reception":27,"sentiment":28,"stance_mix":29,"scored_comments":34,"aspects":35,"strip":48,"post_text":51,"what":52,"said":108,"maker_in_thread":224,"shape":235,"grid":240,"attempts":1020,"same_week":1021,"maker_shows":37,"maker_hidden":1049,"reader_version":1050,"card":1051},"45825733","book.sv","I scraped 3B Goodreads reviews to train a better recommendation model","title","Show HN: I scraped 3B Goodreads reviews to train a better recommendation model","https:\u002F\u002Fbook.sv","costco",1762365045,2025,606,259,50,3837,2,"legend","ai","recommendation engine","web_app",[23,24,25,26],"book recommendations","goodreads","reading list","sequential recommendation","mixed",-0.038,{"positive":30,"neutral":31,"mixed":32,"critical":33},32,41,19,40,132,{"design":36,"idea":39,"execution":41,"privacy":43,"docs":46,"performance":47},{"positive":37,"critical":38},3,0,{"positive":40,"critical":32},15,{"positive":42,"critical":42},6,{"positive":44,"critical":45},1,9,{"positive":38,"critical":38},{"positive":44,"critical":44},[17,38,38,44,38,37,44,44,37,49,17,44,50,49,44,50,37,44,50,37,49,50,37,50,17,49,37,17,37,17,37,37,17,37,17,17,49,17,37,17],5,4,"Hi everyone,\n\nFor the past couple months I've been working on a website with two main features:\n\n- https:\u002F\u002Fbook.sv - put in a list of books and get recommendations on what to read next from a model trained on over a billion reviews\n\n- https:\u002F\u002Fbook.sv\u002Fintersect - put in a list of books and find the users on Goodreads who have read them all (if you don't want to be included in these results, you can opt-out here: https:\u002F\u002Fbook.sv\u002Fremove-my-data)\n\nTechnical info available here: https:\u002F\u002Fbook.sv\u002Fhow-it-works\n\nNote 1: If you only provide one or two books, the model doesn't have a lot to work with and",{"problem":53,"audience":59,"pricing":72,"motivation":73,"time_to_build":77,"stack":81,"openness":105,"stage":106,"team_size":107},{"value":54,"source":55,"evidence":56},"Finding what to read next based on books already read","maker",[57],{"id":58},"post",{"value":60,"source":61,"evidence":62},"Readers who use Goodreads and want book recommendations","inferred",[63,64,68],{"id":58},{"id":65,"by":66,"text":67},"45840129","vessenes","OK, I just added books until you told me I had too many. Fun idea! I have a couple of suggestions: * UI - once someone clicks \"Add\" you really should remove that item from the…",{"id":69,"by":70,"text":71},"45840083","jamesponddotco","The recommendations are pretty good; even though I only input six books, it was enough for it to recommend books I have on my wish list. Definitely going to play around some…",null,{"value":74,"source":55,"evidence":75},"Build a better book recommendation model using scraped Goodreads data",[76],{"id":58},{"value":78,"source":55,"evidence":79},"past couple months",[80],{"id":58},[82,88,92,96],{"value":83,"source":55,"evidence":84},"Go",[85],{"id":86,"by":10,"text":87},"45840702","Everything (namely Meilisearch, Postgres and the web server in Go) besides the model inference is running on a Hetzner server with a large SSD and an \"AMD Ryzen 7 3700X 8-Core…",{"value":89,"source":55,"evidence":90},"Meilisearch",[91],{"id":86,"by":10,"text":87},{"value":93,"source":55,"evidence":94},"Postgres",[95],{"id":86,"by":10,"text":87},{"value":97,"source":55,"evidence":98},"Transformer sequential model",[99,102],{"id":100,"by":10,"text":101},"45841011","Yes I would say the handling of series is probably the biggest problem. Once my test metrics got to a point I was happy with and my quality spot checks passed (can I follow the…",{"id":103,"by":10,"text":104},"45840497","I'm not an expert by any means but as far as sequential recommendations go, aren't SASRec and its derivatives pretty much the name of the game? I probably should have looked into…","unknown","launched","solo",{"praise":109,"objections":131,"requests":175,"questions":200,"alternatives":213},[110,123],{"value":111,"source":112,"evidence":113},"Recommendations are good from few inputs and match wishlists","commenter",[114,118,119],{"id":115,"by":116,"text":117},"45841144","sodality2","This is fantastic!!! I've added many results to my want-to-read list, they're very on-point from very few inputs. It would be really cool to import from a user ID, where you can…",{"id":69,"by":70,"text":71},{"id":120,"by":121,"text":122},"45842626","majormajor","Neat! It's a validation of the model that 75%+ of the recommendations are things I've read and also enjoyed, with a few \"read, didn't like\" and some more \"didn't read, don't…",{"value":124,"source":112,"evidence":125},"Site is fast",[126,130],{"id":127,"by":128,"text":129},"45840783","dbl000","Echoing what everyone else has said here - awesome site, love how fast it was. I did notice that when I put in a single book in a series (in my case Going Postal, Discworld #33)…",{"id":69,"by":70,"text":71},[132,141,149,164],{"value":133,"source":112,"evidence":134},"Recommendations lean toward books the user already read, lacking discovery",[135,136,140],{"id":65,"by":66,"text":67},{"id":137,"by":138,"text":139},"45840446","varenc","I love this site, and the approach! Great seeing someone making good use of Goodreads data. Sadly my experience with the book recommender isn't too great because of the 64 book…",{"id":120,"by":121,"text":122},{"value":142,"source":112,"evidence":143},"Series books dominate recommendations",[144,145],{"id":127,"by":128,"text":129},{"id":146,"by":147,"text":148},"45840156","noir_lord","It has a tendency to recommend books in the same series as are input (putting aside that if I like a book in a series I've likely already read the series). It did suggest…",{"value":150,"source":112,"evidence":151},"Goodreads import fails for some users",[152,156,160],{"id":153,"by":154,"text":155},"45841024","androng","I tried to import my book list with \"Import goodreads\" button and inputting https:\u002F\u002Fwww.goodreads.com\u002Fuser\u002Fshow\u002F68515148-andrew but it said \"import failed, see console\"",{"id":157,"by":158,"text":159},"45841399","tristor","Two bugs to know about. First, you are using a deprecated API call that fails in Firefox. Second, you are using an HTTP endpoint that fails to upgrade to HTTPS to call the…",{"id":161,"by":162,"text":163},"45846899","mhb","Import doesn't work for me.",{"value":165,"source":112,"evidence":166},"Scraping Goodreads may violate its terms and robots.txt",[167,171],{"id":168,"by":169,"text":170},"45844530","voidUpdate","Does this break part 4 of the Goodreads TOS? \"[...] you agree not to sell, license, rent, modify, distribute, copy, reproduce, transmit, publicly display, publicly perform,…",{"id":172,"by":173,"text":174},"45844927","diffeomorphism","The robots.txt is pretty explicit that this scraping is \"disallowed\" https:\u002F\u002Fwww.goodreads.com\u002Frobots.txt So legalities aside, this seems unethical.",[176,183,188,196],{"value":177,"source":112,"evidence":178},"Filter out authors of input books",[179],{"id":180,"by":181,"text":182},"45841092","blehn","You should filter out authors from the input books in the output. If liked a book by an author, surely I'd read more of their work if I wanted to — recommending them isn't…",{"value":184,"source":112,"evidence":185},"Add diversification and discovery of new areas",[186,187],{"id":65,"by":66,"text":67},{"id":120,"by":121,"text":122},{"value":189,"source":112,"evidence":190},"Open source or API access",[191,192],{"id":69,"by":70,"text":71},{"id":193,"by":194,"text":195},"45844729","atomicnature","Will this be open source?",{"value":197,"source":112,"evidence":198},"Remove already-added books from suggestions",[199],{"id":65,"by":66,"text":67},[201,205],{"value":202,"source":112,"evidence":203},"Will the work be open source?",[204],{"id":193,"by":194,"text":195},{"value":206,"source":112,"evidence":207},"Was Goodreads data used with reviewer permission for LLM training?",[208,209],{"id":168,"by":169,"text":170},{"id":210,"by":211,"text":212},"45845945","boplicity","Please remove my reviews from your LLM model and training data. Thank you.",[214,220],{"value":215,"source":55,"evidence":216},"LibraryThing",[217],{"id":218,"by":10,"text":219},"45844451","Thank you for the kind remarks. I would say your request is reasonable and it’s something I thought about but it’s worth noting that if you scroll down on a Goodreads book page…",{"value":221,"source":55,"evidence":222},"StoryGraph",[223],{"id":218,"by":10,"text":219},{"comments":225,"answered":226,"key":227},31,11,[228,231,232],{"id":229,"text":230},"45845379","What do you think the probability that someone else read 15 books you also read is? It’s very unlikely unless they are all staples of a genre, part of the same series, or just…",{"id":100,"text":101},{"id":233,"text":234},"45862599","I just introduced something [1] which should give you much less repetitive recommendations if you want to try again. [1]…",{"commenters":236,"max_depth":237,"maker_replies":225,"first_comment_mins":238,"lifespan_hours":239},177,7,187,122,[241,243,247,251,253,256,258,261,264,268,271,274,276,279,281,284,287,290,292,294,297,300,302,305,308,312,315,317,320,322,325,328,330,332,336,338,341,344,347,350,353,355,358,360,363,366,368,371,373,376,378,380,383,386,389,391,395,398,400,402,405,406,410,413,415,418,421,425,427,430,434,436,439,442,444,446,449,452,454,456,458,461,465,467,471,472,475,477,482,485,488,491,493,497,499,502,504,506,510,512,516,519,523,527,530,532,535,536,539,542,546,548,551,553,555,558,561,564,568,572,576,580,583,587,591,593,596,598,600,603,607,609,611,613,617,619,621,625,627,629,632,635,639,644,648,652,654,658,660,662,664,666,670,673,675,677,680,684,688,692,695,699,703,705,708,710,713,715,717,721,725,727,730,733,736,740,744,747,751,753,756,759,761,762,766,769,773,775,778,782,785,789,793,797,800,802,805,808,810,813,817,821,825,829,831,835,839,841,845,848,852,856,860,864,868,872,876,880,883,888,890,894,898,902,906,910,912,916,920,924,927,931,935,939,942,944,946,950,954,957,961,966,968,971,973,975,977,979,981,985,987,991,995,999,1004,1009,1012,1015,1017],[65,38,37,242,66,38],"project\u002Fmixed\u002Fdesign",[244,38,37,245,246,38],"45842069","project\u002Fneutral\u002Fidea","kace91",[248,38,44,249,250,38],"45844343","project\u002Fcritical\u002Fexecution","idoubtit",[229,38,38,252,10,44],"maker\u002Fneutral\u002Fnone",[254,38,38,255,250,38],"45849793","commenter\u002Fneutral\u002Fnone",[168,44,37,257,169,38],"project\u002Fneutral\u002Fnone",[259,44,38,255,260,38],"45844646","petralithic",[262,44,38,255,263,38],"45844982","hananova",[265,44,38,266,267,38],"45844706","other\u002Fneutral\u002Fnone","kosolam",[269,44,38,266,270,38],"45846574","saaaaaam",[272,44,38,266,273,38],"45848039","IncreasePosts",[275,44,38,266,270,38],"45849683",[277,44,38,266,278,38],"45844801","esskay",[280,44,38,266,169,38],"45845138",[282,44,38,266,283,38],"45845202","hopelite",[285,44,38,266,286,38],"45845209","zigzag312",[288,44,38,255,289,38],"45848255","hrimfaxi",[291,44,38,255,286,38],"45856455",[293,44,38,255,289,38],"45859316",[295,44,38,266,296,38],"45851534","margalabargala",[298,44,38,266,299,38],"45845174","SahAssar",[301,44,38,266,289,38],"45848322",[303,44,38,266,304,38],"45853692","estimator7292",[306,44,38,255,307,38],"45860732","danielmarkbruce",[309,44,44,310,311,38],"45845454","project\u002Fcritical\u002Fnone","exe34",[313,44,38,266,314,38],"45845710","paulnpace",[316,44,38,266,311,38],"45846492",[318,44,38,266,319,38],"45846722","portaouflop",[321,44,38,266,311,38],"45847388",[323,44,38,255,324,38],"45847265","6stringmerc",[326,44,38,255,327,38],"45850705","kulahan",[329,44,38,255,278,38],"45866074",[331,44,38,266,289,38],"45848290",[333,44,49,334,335,38],"45844965","project\u002Fpositive\u002Fnone","pantropy",[337,44,38,266,169,38],"45844993",[339,44,38,266,340,38],"45845793","tonyhart7",[342,44,38,266,343,38],"45849741","bravoetch",[345,44,44,310,346,38],"45845345","croes",[348,44,44,310,349,38],"45845460","kemotep",[351,44,38,266,352,38],"45845508","simianparrot",[354,44,38,266,346,38],"45846828",[356,44,38,266,357,38],"45846409","mejutoco",[359,44,38,266,346,38],"45846801",[361,44,38,266,362,38],"45847764","lm28469",[364,44,38,255,365,38],"45845823","jalk",[367,44,38,255,260,38],"45852368",[369,44,38,255,370,38],"45845662","MichaelBosworth",[372,44,44,310,169,38],"45846100",[374,44,38,255,375,38],"45846952","caconym_",[377,44,38,255,370,38],"45849630",[379,44,38,266,375,38],"45850381",[381,44,38,266,382,38],"45856956","nextaccountic",[384,44,38,266,385,38],"45847031","lunias",[387,44,38,255,388,38],"45847719","Vvector",[390,44,38,255,385,38],"45847887",[392,44,37,393,394,38],"45848136","project\u002Fneutral\u002Fprivacy","contravariant",[396,44,38,266,397,38],"45850733","irl_zebra",[127,17,37,399,128,38],"project\u002Fmixed\u002Fexecution",[100,17,38,401,10,44],"maker\u002Fneutral\u002Fexecution",[403,17,37,399,404,38],"45842652","walletdrainer",[233,17,38,245,10,44],[407,17,49,408,409,38],"45844222","project\u002Fpositive\u002Fidea","IanCal",[411,17,38,266,412,38],"45847630","Peritract",[414,17,38,266,128,38],"45847849",[416,17,38,266,417,38],"45849647","mulakosag",[419,37,49,408,420,38],"45841505","mscbuck",[422,37,38,423,424,38],"45851550","other\u002Fneutral\u002Fidea","maaaaattttt",[180,50,44,426,181,38],"project\u002Fcritical\u002Fidea",[428,50,44,426,429,38],"45842400","honkycat",[431,50,38,432,433,38],"45843520","commenter\u002Fneutral\u002Fidea","Semaphor",[435,50,38,432,181,38],"45862255",[437,50,44,426,438,38],"45849130","Ntrails",[440,50,38,255,441,38],"45855064","martin82",[443,50,38,255,181,38],"45862223",[172,49,44,445,173,38],"project\u002Fcritical\u002Fprivacy",[447,49,44,445,448,38],"45844995","galdauts",[450,49,38,255,451,38],"45848086","psandor",[453,49,38,266,314,38],"45845750",[455,49,38,255,173,38],"45846338",[457,49,38,255,314,38],"45846856",[459,49,38,255,460,38],"45847303","wongarsu",[462,49,49,4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