Help to choose algorithm for computing difference between 2 texts?
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I have a task to create a tool, which will be able to find articles-duplicates of a given reference article.
I know word vectorization (tf-idf,word2vec), RNN methods, but i can not choose something suitable for my situation.
My requirments:
- data are being collected on the fly (program parses articles from web sites, so i don't have regular DB with collection of texts)
- there is a reference text, whose copies need to be found
- copies could be copypasted, partially copypasted (by paragraphs) or paraphrased
reference-vs-copy comparison algorithm is preferable, but not required (instead of reference-vs-corps)- algorithm shouldn't do deep semantic analyzis, only kind of word counting, word vectorization, substring search
- instead one algorithm, i can use a set of herurisitcs
- algorithms can do false positive dicisions
I come up with such ideas:
- download pretrained word2vec and compare means of word-vectors
- Build a dictionary word->count from every text and compare it to reference dictionary
- collect about 100 texts, vectorize them according to tf-idf and find closest to the reference
I will apreciate, if you will point specific algorithms, libs, examples based on key-word extractions, dummy substring search, line difference comparison for python or CLI.
python nlp
asked 4 mins ago
ДмитрийДмитрий
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$begingroup$
I have a task to create a tool, which will be able to find articles-duplicates of a given reference article.
I know word vectorization (tf-idf,word2vec), RNN methods, but i can not choose something suitable for my situation.
My requirments:
- data are being collected on the fly (program parses articles from web sites, so i don't have regular DB with collection of texts)
- there is a reference text, whose copies need to be found
- copies could be copypasted, partially copypasted (by paragraphs) or paraphrased
reference-vs-copy comparison algorithm is preferable, but not required (instead of reference-vs-corps)- algorithm shouldn't do deep semantic analyzis, only kind of word counting, word vectorization, substring search
- instead one algorithm, i can use a set of herurisitcs
- algorithms can do false positive dicisions
I come up with such ideas:
- download pretrained word2vec and compare means of word-vectors
- Build a dictionary word->count from every text and compare it to reference dictionary
- collect about 100 texts, vectorize them according to tf-idf and find closest to the reference
I will apreciate, if you will point specific algorithms, libs, examples based on key-word extractions, dummy substring search, line difference comparison for python or CLI.
python nlp
asked 4 mins ago
ДмитрийДмитрий
1
New contributor
Дмитрий is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I have a task to create a tool, which will be able to find articles-duplicates of a given reference article.
I know word vectorization (tf-idf,word2vec), RNN methods, but i can not choose something suitable for my situation.
My requirments:
- data are being collected on the fly (program parses articles from web sites, so i don't have regular DB with collection of texts)
- there is a reference text, whose copies need to be found
- copies could be copypasted, partially copypasted (by paragraphs) or paraphrased
reference-vs-copy comparison algorithm is preferable, but not required (instead of reference-vs-corps)- algorithm shouldn't do deep semantic analyzis, only kind of word counting, word vectorization, substring search
- instead one algorithm, i can use a set of herurisitcs
- algorithms can do false positive dicisions
I come up with such ideas:
- download pretrained word2vec and compare means of word-vectors
- Build a dictionary word->count from every text and compare it to reference dictionary
- collect about 100 texts, vectorize them according to tf-idf and find closest to the reference
I will apreciate, if you will point specific algorithms, libs, examples based on key-word extractions, dummy substring search, line difference comparison for python or CLI.
python nlp
asked 4 mins ago
ДмитрийДмитрий
1
New contributor
Дмитрий is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I have a task to create a tool, which will be able to find articles-duplicates of a given reference article.
I know word vectorization (tf-idf,word2vec), RNN methods, but i can not choose something suitable for my situation.
My requirments:
- data are being collected on the fly (program parses articles from web sites, so i don't have regular DB with collection of texts)
- there is a reference text, whose copies need to be found
- copies could be copypasted, partially copypasted (by paragraphs) or paraphrased
reference-vs-copy comparison algorithm is preferable, but not required (instead of reference-vs-corps)- algorithm shouldn't do deep semantic analyzis, only kind of word counting, word vectorization, substring search
- instead one algorithm, i can use a set of herurisitcs
- algorithms can do false positive dicisions
I come up with such ideas:
- download pretrained word2vec and compare means of word-vectors
- Build a dictionary word->count from every text and compare it to reference dictionary
- collect about 100 texts, vectorize them according to tf-idf and find closest to the reference
I will apreciate, if you will point specific algorithms, libs, examples based on key-word extractions, dummy substring search, line difference comparison for python or CLI.
python nlp
python nlp
asked 4 mins ago
ДмитрийДмитрий
1
New contributor
Дмитрий is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 4 mins ago
ДмитрийДмитрий
1
New contributor
Дмитрий is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 4 mins ago
ДмитрийДмитрий
1
New contributor
Дмитрий is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 4 mins ago
ДмитрийДмитрий
1
asked 4 mins ago
ДмитрийДмитрий
1
1
New contributor
Дмитрий is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Дмитрий is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Дмитрий is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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