[{"data":1,"prerenderedAt":454},["ShallowReactive",2],{"project-11106386":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":26,"sentiment":27,"stance_mix":28,"scored_comments":33,"aspects":34,"strip":42,"post_text":43,"what":44,"said":71,"maker_in_thread":197,"shape":207,"grid":210,"attempts":416,"same_week":417,"maker_shows":31,"maker_hidden":446,"reader_version":447,"card":448},"11106386","sense2vec.spacy.io","Sense2vec model trained on all 2015 Reddit comments","title","Show HN: Sense2vec model trained on all 2015 Reddit comments","https:\u002F\u002Fsense2vec.spacy.io","syllogism",1455573767,2016,225,79,112,2264,5,"notable","ai","word embeddings","web_app",[23,20,24,25],"word2vec","reddit corpus","semantic similarity","mixed",-0.239,{"positive":29,"neutral":30,"mixed":31,"critical":32},11,19,3,22,55,{"docs":35,"idea":37,"execution":39,"performance":40},{"positive":36,"critical":36},0,{"positive":17,"critical":38},1,{"positive":17,"critical":30},{"positive":36,"critical":41},2,[31,31,36,31,31,31,17,36,31,38,31,31,36,38,38,31,38,36,17,36,31,38,38,38,38,38,31,31,17,17,17,38,31,38,17,38,38,38,38,31],null,{"problem":45,"audience":43,"pricing":43,"motivation":43,"time_to_build":43,"stack":55,"openness":68,"stage":69,"team_size":70},{"value":46,"source":47,"evidence":48},"Finds words and phrases with similar meaning, using Reddit comment usage","inferred",[49,51],{"id":50},"post",{"id":52,"by":53,"text":54},"11106668","henningpeters","Accompanying blog post is at https:\u002F\u002Fspacy.io\u002Fblog\u002Fsense2vec-with-spacy",[56,62],{"value":57,"source":47,"evidence":58},"Python",[59],{"id":60,"by":53,"text":61},"11108434","Maybe it wasn't clear, but we open-sourced everything, including the trained model. See here: https:\u002F\u002Fgithub.com\u002Fspacy-io\u002Fsense2vec For installation: $ pip install -e…",{"value":63,"source":64,"evidence":65},"spaCy","commenter",[66,67],{"id":52,"by":53,"text":54},{"id":60,"by":53,"text":61},"open_source","beta","team",{"praise":72,"objections":99,"requests":138,"questions":161,"alternatives":179},[73,88],{"value":74,"source":64,"evidence":75},"Good results for anime, bands, and game jargon",[76,80,84],{"id":77,"by":78,"text":79},"11106871","PeCaN","Interesting side effect: it has learned to give somewhat decent anime recommendations. At the very least it recognizes some basic genres to an extent (for example, TTGL is close…",{"id":81,"by":82,"text":83},"11106856","andrewtbham","The band names are particularly cool. It is sorta like a recommendation engine. If you like Pink floyd, you might like Led Zepplin.",{"id":85,"by":86,"text":87},"11106812","jldugger","Pretty good at picking up the Smash Bros Jargon: https:\u002F\u002Fsense2vec.spacy.io\u002F?dash_dance|NOUN",{"value":89,"source":64,"evidence":90},"Impressive semantic results overall",[91,95],{"id":92,"by":93,"text":94},"11107010","1ris","It's impressive how good it is. But there is still room for improvement. Searching \"Haskell\" leads to Clojure and C++. Yes, these are both Programming Languages, but out of all I…",{"id":96,"by":97,"text":98},"11106878","finishingmove","Searched for \"Best Iron Maiden album\" and it was smart enough not to pick one. Then I tried \"Seinfeld\" and it returned Seinfeld as the 10th result behind some other sitcoms,…",[100,115,130],{"value":101,"source":64,"evidence":102},"Search with Enter key does not work",[103,107,111],{"id":104,"by":105,"text":106},"11106648","Palomides","is it just me or does it not search when you hit enter?",{"id":108,"by":109,"text":110},"11106761","justinsaccount","It's not just you, I need to click the search icon.",{"id":112,"by":113,"text":114},"11106750","ssalenik","Nothing happens for me where I press enter either, I have to click on the search icon (firefox on linux).",{"value":116,"source":64,"evidence":117},"NSFW and some phrases return no results",[118,122,126],{"id":119,"by":120,"text":121},"11106934","thekingshorses","NSFW doesn't work: https:\u002F\u002Fsense2vec.spacy.io\u002F?NSFW%7CNOUN",{"id":123,"by":124,"text":125},"11106792","rocky1138","Searched for something NSFW and didn't get any results :(",{"id":127,"by":128,"text":129},"11106818","cowsandmilk","tried \"netflix and chill\", didn't find anything? That to me is the phrase of the year that is more than the sum of its parts.",{"value":131,"source":64,"evidence":132},"Some results are odd, e.g. Haskell near Clojure and C++",[133,134],{"id":92,"by":93,"text":94},{"id":135,"by":136,"text":137},"11106972","gradi3nt","The first name to show up when I search 'evil man' is 'Mr Rogers'...what the hell, reddit. (first name, not first word, had to scroll down a bit, past words like 'Nazi soldier'…",[139,146,154],{"value":140,"source":64,"evidence":141},"Downloadable trained vectors",[142],{"id":143,"by":144,"text":145},"11107656","j2kun","Would it be possible for you to make the trained vectors available for download and independent analysis without having to rescrape and retrain the model?",{"value":147,"source":64,"evidence":148},"Phrase and multi-word query support",[149,150],{"id":127,"by":128,"text":129},{"id":151,"by":152,"text":153},"11106851","sgarman","I tried \"rick and morty\" and got the same issue. My guess is it has something to do with the term \"and.\"",{"value":155,"source":64,"evidence":156},"An API",[157],{"id":158,"by":159,"text":160},"11108829","Kiro","This is awesome! I would pay for an API.",[162,169],{"value":163,"source":64,"evidence":164},"Can vector algebra queries be supported",[165],{"id":166,"by":167,"text":168},"11106804","MasterScrat","Now can't you experiment with algebra operations on those vectors, like \"queen minus female plus male = king\"?",{"value":170,"source":64,"evidence":171},"Can meanings be separated by subreddit",[172,176],{"id":173,"by":174,"text":175},"11107709","rockmeamedee","Word vectors are really intriguing to me, and I have a few questions: If you also trained a model on a different news aggregator's comments, would it be possible to \"match up\"…",{"id":177,"by":10,"text":178},"11108610","Let's say we want to know how usage differs in one subreddit vs another. If you just train two entirely separate models, you end up with two vector spaces. The meanings within…",[180,190],{"value":181,"source":64,"evidence":182},"WordNet",[183,186],{"id":184,"by":82,"text":185},"11106839","This is very cool. I have played with the word2vec download a lot and I have been sorta amazed. If you had a lot of money... like google... it would be cool to train word vectors…",{"id":187,"by":188,"text":189},"11106981","ecesena","I don't think wordnet (and similar) will ever be obsolete. From my point of view, they are a \"curated\" subset of the semantic that you can obtain with word2vec. The latter can…",{"value":191,"source":64,"evidence":192},"NLTK",[193],{"id":194,"by":195,"text":196},"11106602","danso","Great to see another use case of spacy...I've been wanting to give it a go ever since OP pitched it as an alternative to NLTK.",{"comments":198,"answered":17,"key":199},9,[200,201,204],{"id":177,"text":178},{"id":202,"text":203},"11106827","This is supported in the underlying data, but we don't expose it in the UI at the moment. We'll probably do something a bit different to help people make those queries.",{"id":205,"text":206},"11107026","Well, you can't do this in the web API obviously, but there are a few ways you could do this. This is a good idea really -- thanks for bringing this up. One way would be to…",{"commenters":33,"max_depth":17,"maker_replies":198,"first_comment_mins":208,"lifespan_hours":209},30,16,[211,213,217,219,220,224,225,227,228,231,234,235,238,241,243,246,247,250,253,256,259,261,264,265,268,271,275,279,282,285,286,288,292,296,298,302,306,309,311,314,317,319,321,324,325,327,329,332,333,335,336,338,341,344,348,349,351,353,356,358,360,363,367,369,373,376,381,385,387,390,394,398,400,403,407,409,411,413],[52,36,31,212,53,36],"project\u002Fneutral\u002Fdocs",[214,38,31,215,216,36],"11106553","project\u002Fmixed\u002Fidea","minimaxir",[173,41,31,218,174,36],"project\u002Fneutral\u002Fidea",[177,41,36,218,10,38],[221,41,36,222,223,36],"11109505","other\u002Fneutral\u002Fnone","ppod",[166,31,31,218,167,36],[202,31,36,226,10,38],"project\u002Fneutral\u002Fnone",[143,31,31,226,144,36],[229,31,36,230,167,36],"11108391","commenter\u002Fneutral\u002Fnone",[232,31,36,230,233,36],"11108452","tartakovsky",[60,31,31,212,53,36],[184,236,17,237,82,36],4,"project\u002Fpositive\u002Fidea",[239,236,36,222,240,36],"11106853","RBerenguel",[187,236,36,242,188,36],"other\u002Fneutral\u002Fidea",[244,236,36,222,245,36],"11107046","rspeer",[92,17,31,215,93,36],[248,17,31,218,249,36],"11107278","nl",[251,17,36,230,252,36],"11107547","verroq",[135,254,38,255,136,36],6,"project\u002Fcritical\u002Fexecution",[257,254,38,255,258,36],"11108780","realusername",[81,260,17,237,82,36],7,[85,262,17,263,86,36],8,"project\u002Fpositive\u002Fexecution",[119,198,38,255,120,36],[266,198,36,230,267,36],"11106952","neo2006",[269,198,36,230,270,36],"11108170","singham",[272,198,31,273,274,36],"11107544","project\u002Fneutral\u002Fexecution","thisisdave",[276,277,38,255,278,36],"11106758",10,"fla",[280,277,31,273,281,36],"11107600","Houshalter",[283,29,38,284,188,36],"11106969","project\u002Fcritical\u002Fidea",[205,29,36,218,10,38],[287,29,31,218,249,36],"11107295",[289,290,36,222,291,36],"11107649",12,"dbunkerx",[293,294,38,255,295,36],"11109447",13,"Grue3",[297,294,36,273,10,38],"11109528",[299,300,36,222,301,36],"11108906",14,"stared",[303,304,17,263,305,36],"11106975",15,"aledalgrande",[307,304,31,273,308,36],"11107653","taneq",[310,304,36,222,305,36],"11107743",[312,304,36,222,313,36],"11107802","tylercubell",[315,209,31,218,316,36],"11106592","empath75",[318,209,36,230,281,36],"11108101",[104,320,38,255,105,36],17,[322,320,36,323,10,38],"11106682","maker\u002Fneutral\u002Fexecution",[112,320,38,255,113,36],[326,320,36,273,10,38],"11106775",[328,320,38,255,249,36],"11107122",[330,320,38,255,331,36],"11106764","Coding_Cat",[108,320,38,255,109,36],[127,334,38,255,128,36],18,[151,334,38,255,152,36],[337,334,36,218,10,38],"11106882",[339,30,31,218,340,36],"11109854","IshKebab",[194,342,17,343,195,36],20,"project\u002Fpositive\u002Fnone",[345,346,38,255,347,36],"11108684",21,"natch",[77,32,17,237,78,36],[350,32,17,263,93,36],"11107023",[352,32,17,263,78,36],"11107171",[354,32,17,237,355,36],"11107097","Pxtl",[96,357,17,263,97,36],23,[359,357,31,273,97,36],"11106921",[361,362,38,255,281,36],"11107592",24,[364,365,38,255,366,36],"11109223",25,"soft_dev_person",[368,365,36,323,10,38],"11109519",[370,371,31,218,372,36],"11107856",26,"biot",[374,371,31,218,375,36],"11107901","rangibaby",[377,378,38,379,380,36],"11106888",27,"project\u002Fcritical\u002Fperformance","andrewchambers",[382,383,31,226,384,36],"11109113",28,"beyondcompute",[158,386,17,237,159,36],29,[388,208,38,255,389,36],"11109584","bawana",[391,392,31,273,393,36],"11108153",31,"the_cat_kittles",[395,396,38,379,397,36],"11108677",32,"drakmail",[123,399,38,255,124,36],33,[401,399,31,273,402,36],"11106927","xyzzy123",[404,405,38,255,406,36],"11106746",34,"gleb",[408,405,36,323,10,38],"11106760",[410,405,38,255,406,36],"11106772",[412,405,31,273,53,36],"11106797",[414,405,31,415,249,36],"11106919","project\u002Fmixed\u002Fexecution",[],[418,423,427,432,436,441],{"id":419,"name":420,"points":421,"category":422},"11077823","Htop 2.0 released",613,"dev_tools",{"id":424,"name":425,"points":426,"category":422},"11109600","Food Pairing Ninja",337,{"id":428,"name":429,"points":430,"category":431},"11080539","HN Replies",217,"consumer_social",{"id":433,"name":434,"points":435,"category":422},"11104781","Laboratory",153,{"id":437,"name":438,"points":439,"category":440},"11109438","Go-git",114,"languages",{"id":442,"name":443,"points":444,"category":445},"11102912","The Top Fives",106,"productivity",false,"v2",{"id":449,"name":5,"line":6,"ai":446,"cat":19,"year":12,"points":13,"comments":14,"rec":26,"s":450,"top":17,"kw":451,"maker":10,"domain":5,"tier":18,"attempts":36,"strip":452,"url":9,"mix":453,"praise":74,"objection":101,"sub":20},11106386,-0.24,[23,20,24,25],"3303335031330113105031111133555131511113",[29,30,31,32],1794036540992]