I'm doing some research on approximate dictionary matching algorithms. Everyone is familiar with at least one of these: the spell checker. You give it a word, possibly misspelled, and it tries to find the best match it can from a list of entries. I'm not writing a spell-checker, but the concept is similar: input might be misspelled, but I need to look for acceptable matches in the reference data. The problem is, as always: the naive methods are simple but unacceptably slow. So, it's off to the world of academic papers.<\/p>\n
As always with this kind of research, the papers are so abstract as to be almost opaque. I try to understand them, but they just crush my head. So, for a given paper, I usually end up using Google to see if anyone has written code to implement the algorithm the paper describes because it's almost always easier for me to read source code, even in languages I don't use, than it is to read academic papers. I rarely get good results because this stuff is always esoteric and people don't like to share their hard work. But it does work sometimes. <\/p>\n
So, I type the name of the algorithm from the paper into a search box. Google looks around, using its own<\/i> approximate dictionary matching algorithm, finds only a few results in obscure places, and concludes that I misspelled my query. So it gives me results for what it thinks I meant - which are irrelevant to what I asked for. <\/p>\n
It's like Google is defending itself, trying to stop me from finding out how it works. Which is kindof what I'm doing, actually. Except for the irrelevant results, of course.<\/p>\n","protected":false},"excerpt":{"rendered":"
I'm doing some research on approximate dictionary matching algorithms. Everyone is familiar with at least one of these: the spell checker. You give it a word, possibly misspelled, and it tries to find the best match it can from a list of entries. I'm not writing a spell-checker, but the concept is similar: input might […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-18420","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=\/wp\/v2\/posts\/18420","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=18420"}],"version-history":[{"count":0,"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=\/wp\/v2\/posts\/18420\/revisions"}],"wp:attachment":[{"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=18420"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=18420"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ok-cleek.com\/blogs\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=18420"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}