defmodule ContentIndexer.Services.Calculator do use GenServer alias ContentIndexer.Services.{ListCheckerWorker, ListCheckerServer} @moduledoc """ ** Summary ** calculates the content_indexer weights for a document of tokens against a corpus of tokenized documents https://en.wikipedia.org/wiki/Tf-idf ** What is Tf-Idf ** tf–idf, short for term frequency–inverse document frequency, is a numerical statistic that is intended to reflect how important a word is to a document in a collection or corpus. It is often used as a weighting factor in information retrieval and text mining. This library supports calculating large datasets in parallel using the Erlang OTP based server and actors Currently the supported file types are plain-text, PDF and DOCX (xml) ** Basic Useage ** Pass it a list of tokens and a corpus of tokens as a list of lists and it will return a list of tokens with corresponding content_indexer weights based on the corpus of tokens iex> ContentIndexerService.calculate_content_indexer_documents( ["bread","butter","jam"], [["red","brown","jam"],["blue","green","butter"],["pink","green","bread","jam"]] ) {:ok, [bread: 0.3662040962227032, butter: 0.3662040962227032,jam: 0.3662040962227032]} """ def start_link do GenServer.start_link(__MODULE__, :ok, [name: __MODULE__]) end def init(:ok) do {:ok, init_calculator()} end def init_calculator do IO.puts "\nInitialising Calculator\n" end def handle_call({:state}, _from, state) do {:reply, {:ok, state}, state} end def handle_call({:total, _count}, _from, state) do {:reply, {:ok, state}, state} end def total(count) do GenServer.call(__MODULE__, {:total, count}) end @doc """ calculates the content_indexer iex> ContentIndexerValidateService.calculate_tokens_againts_corpus( "bread,butter,jam", ["red,brown,jam","blue,green,butter","pink,green,bread,jam"] ) {:ok, [ {"bread", 0.13515503603605478}, {"butter", 0.13515503603605478}, {"jam", 0.0} ] } """ def calculate_tokens_againts_corpus(content, corpus) do token_list = Tfidf.calculate_all(content, corpus, &String.split(&1, ",")) {:ok, token_list} end @doc """ calculates the word count for each token in the list of tokens representing the document and returns a list of the tokens with their respective word counts iex> ContentIndexerService.calculate_token_count_document(["bread","butter","jam","jam","bread","bread"]) {:ok, [bread: 3, butter: 1, jam: 2]} """ def calculate_token_count_document(tokens) do token_stream = Stream.map(tokens, fn(token) -> {token, word_count(token, tokens)} end) uniq_tokens = token_stream |> Stream.uniq |> Enum.to_list {:ok, uniq_tokens} end @doc """ calculates the term frequency for each token in the list of tokens representing the document and returns a list of the tokens with their respective term frequencies iex> ContentIndexerService.calculate_tf_document(["bread","butter","jam","jam","bread","bread"]) {:ok, [bread: 0.5, butter: 0.16666666666666666, jam: 0.3333333333333333]} """ def calculate_tf_document(tokens) do token_stream = Stream.map(tokens, fn(token) -> {token, tf(token, tokens)} end) uniq_tokens = token_stream |> Stream.uniq |> Enum.to_list {:ok, uniq_tokens} end @doc """ calculates the content_indexer weights for each token in the query - weights the query against itself iex> ContentIndexerService.calculate_content_indexer_query( ["bread","butter","jam"] ) {:ok, [bread: 0.0, butter: 0.0, jam: 0.0]} """ def calculate_content_indexer_query(tokens) do tokenized_tokens = case tokens do [_|_] -> tokens _ -> tokenize(tokens) end token_content_indexer_counts = tokenized_tokens |> Enum.uniq |> Enum.map(fn(token) -> {token, (tf(token, tokenized_tokens) * idf_streamed(token, 1, [tokens]))} end) {:ok, token_content_indexer_counts} end @doc """ calculates the content_indexer weights for each token in the list of tokens against the corpus of tokens iex> ContentIndexerService.calculate_content_indexer_documents( ["bread","butter","jam"], [["red","brown","jam"],["blue","green","butter"],["pink","green","bread","jam"]] ) {:ok, [bread: 0.3662040962227032, butter: 0.3662040962227032,jam: 0.3662040962227032]} """ def calculate_content_indexer_documents(tokens, corpus_of_tokens) do corpus_size = length(corpus_of_tokens) # this is so we can avoid calculating it again! case corpus_size do 1 -> calculate_content_indexer_documents_single(tokens, corpus_of_tokens) _ -> calculate_content_indexer_documents_multiple(tokens, corpus_of_tokens, corpus_size) end end def calculate_content_indexer_documents(tokens, corpus_of_tokens, corpus_size) do case corpus_size do 1 -> calculate_content_indexer_documents_single(tokens, corpus_of_tokens) _ -> calculate_content_indexer_documents_multiple(tokens, corpus_of_tokens, corpus_size) end end defp calculate_content_indexer_documents_single(tokens, corpus_of_tokens) do token_content_indexer_counts = tokens |> Enum.uniq |> Enum.map(fn(token) -> {token, (tf(token, tokens) * idf(token, corpus_of_tokens))} end) {:ok, token_content_indexer_counts} end # The corpus_of_tokens has more than one document in it defp calculate_content_indexer_documents_multiple(tokens, corpus_of_tokens, corpus_size) do token_content_indexer_counts = tokens |> Enum.uniq |> Enum.map(fn(token) -> {to_string(token), (tf(token, tokens) * idf_streamed(token, corpus_size, corpus_of_tokens))} end) {:ok, token_content_indexer_counts} end defp idf_streamed(word, corpus_size, corpus_of_tokens) do :math.log(corpus_size / (1 + n_containing_calc(word, corpus_of_tokens, corpus_size))) end # Corpus of tokens is a list of tuples with the index being the second item in the tuple defp n_containing_calc(word, corpus_of_tokens, collection_size) do ListCheckerServer.initialise_collection(collection_size, self()) indexed_stream = Stream.with_index(corpus_of_tokens) indexed_stream |> Enum.each(fn(streamed_item) -> {tokens, index} = streamed_item ListCheckerWorker.list(index, word, tokens) end) total = receive do {:total, count} -> count end total end def list_contains(list, item) do Enum.find(list, fn(cur_item) -> item == cur_item end) != nil end defp idf(word, corpus_of_tokens) do :math.log(length(corpus_of_tokens) / (1 + n_containing(word, corpus_of_tokens))) end defp tf(word, tokens) do word_count(word, tokens) / length(tokens) end defp word_count(word, tokens) do Enum.reduce(tokens, 0, fn(cur_word, acc) -> if cur_word == word, do: acc + 1, else: acc end) end defp n_containing(word, corpus_of_tokens) do Enum.reduce(corpus_of_tokens, 0, fn(text, acc) -> if list_contains(text, word), do: acc + 1, else: acc end) end defp tokenize(text, split_char \\ ",") do split_str = String.split(text, split_char) split_str |> Enum.filter(fn x -> x != "" end) # remove empty elements end end