mirror of
https://github.com/antos-rde/antosdk-apps.git
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50 lines
1.6 KiB
Lua
50 lines
1.6 KiB
Lua
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local path = require("fs/vfs").ospath("home://aiws/blog-clustering")
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local gettext = loadfile(path.."/gettext.lua")()
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local cluster = loadfile(path.."/cluster.lua")()
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local refresh = false
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local file = "/home/mrsang/test.csv"
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if refresh then
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local data = gettext.get({publish=1})
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local documents = {}
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if data then
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local sw = gettext.stopwords("home://aiws/blog-clustering/stopwords.txt")
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for k,v in pairs(data) do
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local bag = cluster.bow(data[k].content, sw)
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documents[data[k].id] = bag
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end
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cluster.tfidf(documents)
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--local v = cluster.search("arm", documents)
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--echo(JSON.encode(v))
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local vectors, maxv, size = cluster.get_vectors(documents)
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local s = cluster.save_topchart(vectors,file, 3)
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if s then echo("file saved") else echo("error save file") end
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--echo(JSON.encode(r))
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--r = cluster.similarity(vectors["14"],vectors["16"])
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--echo("Similarity "..r)
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--local c,l = cluster.kmean(3, documents, 10)
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--echo(JSON.encode(c))
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--echo(JSON.encode(l))
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else
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echo("Data missing")
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end
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else
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local f = io.open(file,"r")
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local result = {}
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for line in f:lines() do
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local arr = {}
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local cnt = 0
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for i in line:gmatch( "%S+") do
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cnt = cnt + 1
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arr[cnt] = i
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end
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if not result[arr[1]] then result[arr[1]] = {} end
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result[arr[1]][arr[2]] = tonumber(arr[3])
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end
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f:close()
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echo(JSON.encode(result))
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--local r = cluster.top_similarity("2",vectors, 3)
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--echo(JSON.encode(r))
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end
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