Improved keyword extraction for short documents
I have a large database of historic events with descriptions that are on the order of 10-30 words each. I'm trying to build a keyword extractor that will tag each document with 1-3grams sensibly with regard to the database as a whole, so that tags will be re-used as much as possible.
TF-IDF is what first comes to mind, but I'm having poor results with, i.e., Natural.js's TFIDF tool (which doesn't use n-grams).
I've seen a lot of interesting research on more advanced ML techniques (Biterm Topic Model, unsupervised clustering, etc.) but I can't seem to find any useful implementations. Is there something out there I'm missing?
javascript machine-learning nlp keyword-extraction
edited Nov 26 '18 at 13:23
Gabriel M
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asked Nov 25 '18 at 23:21
T3db0tT3db0t
1,58141730
add a comment |
I have a large database of historic events with descriptions that are on the order of 10-30 words each. I'm trying to build a keyword extractor that will tag each document with 1-3grams sensibly with regard to the database as a whole, so that tags will be re-used as much as possible.
TF-IDF is what first comes to mind, but I'm having poor results with, i.e., Natural.js's TFIDF tool (which doesn't use n-grams).
I've seen a lot of interesting research on more advanced ML techniques (Biterm Topic Model, unsupervised clustering, etc.) but I can't seem to find any useful implementations. Is there something out there I'm missing?
javascript machine-learning nlp keyword-extraction
edited Nov 26 '18 at 13:23
Gabriel M
1,17541223
asked Nov 25 '18 at 23:21
T3db0tT3db0t
1,58141730
add a comment |
I have a large database of historic events with descriptions that are on the order of 10-30 words each. I'm trying to build a keyword extractor that will tag each document with 1-3grams sensibly with regard to the database as a whole, so that tags will be re-used as much as possible.
TF-IDF is what first comes to mind, but I'm having poor results with, i.e., Natural.js's TFIDF tool (which doesn't use n-grams).
I've seen a lot of interesting research on more advanced ML techniques (Biterm Topic Model, unsupervised clustering, etc.) but I can't seem to find any useful implementations. Is there something out there I'm missing?
javascript machine-learning nlp keyword-extraction
edited Nov 26 '18 at 13:23
Gabriel M
1,17541223
asked Nov 25 '18 at 23:21
T3db0tT3db0t
1,58141730
I have a large database of historic events with descriptions that are on the order of 10-30 words each. I'm trying to build a keyword extractor that will tag each document with 1-3grams sensibly with regard to the database as a whole, so that tags will be re-used as much as possible.
TF-IDF is what first comes to mind, but I'm having poor results with, i.e., Natural.js's TFIDF tool (which doesn't use n-grams).
I've seen a lot of interesting research on more advanced ML techniques (Biterm Topic Model, unsupervised clustering, etc.) but I can't seem to find any useful implementations. Is there something out there I'm missing?
javascript machine-learning nlp keyword-extraction
javascript machine-learning nlp keyword-extraction
edited Nov 26 '18 at 13:23
Gabriel M
1,17541223
asked Nov 25 '18 at 23:21
T3db0tT3db0t
1,58141730
edited Nov 26 '18 at 13:23
Gabriel M
1,17541223
asked Nov 25 '18 at 23:21
T3db0tT3db0t
1,58141730
edited Nov 26 '18 at 13:23
Gabriel M
1,17541223
edited Nov 26 '18 at 13:23
Gabriel M
1,17541223
edited Nov 26 '18 at 13:23
Gabriel M
1,17541223
1,17541223
asked Nov 25 '18 at 23:21
T3db0tT3db0t
1,58141730
asked Nov 25 '18 at 23:21
T3db0tT3db0t
1,58141730
asked Nov 25 '18 at 23:21
T3db0tT3db0t
1,58141730
1,58141730
add a comment |
add a comment |
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