Similarity between Sentence 1 and Sentence 2 giving wrong resultsHow to calculate the sentence similarity using word2vec model of gensim with pythonExtrapolate Sentence Similarity Given Word SimilaritiesSentence similarity using kerasSemantic Similarity between Sentences in a TextQuantifiying the similarity between two sentencesSiamese Network with LSTM for sentence similarity in Keras gives periodically the same resultspark similarities between text sentencesCompute similarity between sentences using SparkSimilarity between two sentences using word2vecComputing a similarity score for a set of sentences
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Similarity between Sentence 1 and Sentence 2 giving wrong results
How to calculate the sentence similarity using word2vec model of gensim with pythonExtrapolate Sentence Similarity Given Word SimilaritiesSentence similarity using kerasSemantic Similarity between Sentences in a TextQuantifiying the similarity between two sentencesSiamese Network with LSTM for sentence similarity in Keras gives periodically the same resultspark similarities between text sentencesCompute similarity between sentences using SparkSimilarity between two sentences using word2vecComputing a similarity score for a set of sentences
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we are doing some exercise to see how can I calculate similarity between 2 sentences. Below specified is some analysis. When you observe even though the sentences DO NOT match the scores are pretty high.
We are planning to have an assessment done based on this similarity and below results makes it clear that we cannot use that. Any suggestions on how we can sort this out. Please help.
Sentence1 = “Export Template Menu”.
Test sentence are:
1. Import Template Menu
2. Template Menu
3. Menu
4. Template
5. Rahul Dravid
6. Template template menu
7. it can be import template menu or export template menu
8. what difference does it make if its import template menu or export template menu or whatever template menu
When similarity score using gensim vectorization then
- Import Template Menu -- Similarity Score = 0.95984 -- danger sign
- Template Menu -- Similarity Score = 0.7096 -- danger sign
- Menu -- Similarity Score = 0.6264
- Template -- Similarity Score = 0.6264
- Rahul Dravid -- Similarity Score = 0.0
- template template menu -- Similarity Score = 0.6
- it can be import template menu or export template menu -- Similarity Score = 0.876 -- Danger sign
- what difference does it make if its import template menu or export template menu or whatever template menu -- Similarity Score = 0.787 -- Danger sign
sentence-similarity
asked Mar 22 at 17:21
ashwar hussainashwar hussain
426
add a comment |
we are doing some exercise to see how can I calculate similarity between 2 sentences. Below specified is some analysis. When you observe even though the sentences DO NOT match the scores are pretty high.
We are planning to have an assessment done based on this similarity and below results makes it clear that we cannot use that. Any suggestions on how we can sort this out. Please help.
Sentence1 = “Export Template Menu”.
Test sentence are:
1. Import Template Menu
2. Template Menu
3. Menu
4. Template
5. Rahul Dravid
6. Template template menu
7. it can be import template menu or export template menu
8. what difference does it make if its import template menu or export template menu or whatever template menu
When similarity score using gensim vectorization then
- Import Template Menu -- Similarity Score = 0.95984 -- danger sign
- Template Menu -- Similarity Score = 0.7096 -- danger sign
- Menu -- Similarity Score = 0.6264
- Template -- Similarity Score = 0.6264
- Rahul Dravid -- Similarity Score = 0.0
- template template menu -- Similarity Score = 0.6
- it can be import template menu or export template menu -- Similarity Score = 0.876 -- Danger sign
- what difference does it make if its import template menu or export template menu or whatever template menu -- Similarity Score = 0.787 -- Danger sign
sentence-similarity
asked Mar 22 at 17:21
ashwar hussainashwar hussain
426
Using the approach suggested in stackoverflow.com/questions/22129943/… using google News vectors results look more decent .. but its not able to get into more specific vocabulary. Can you train this model some how by using our own vocabulary?
– ashwar hussain
Mar 22 at 19:11
add a comment |
we are doing some exercise to see how can I calculate similarity between 2 sentences. Below specified is some analysis. When you observe even though the sentences DO NOT match the scores are pretty high.
We are planning to have an assessment done based on this similarity and below results makes it clear that we cannot use that. Any suggestions on how we can sort this out. Please help.
Sentence1 = “Export Template Menu”.
Test sentence are:
1. Import Template Menu
2. Template Menu
3. Menu
4. Template
5. Rahul Dravid
6. Template template menu
7. it can be import template menu or export template menu
8. what difference does it make if its import template menu or export template menu or whatever template menu
When similarity score using gensim vectorization then
- Import Template Menu -- Similarity Score = 0.95984 -- danger sign
- Template Menu -- Similarity Score = 0.7096 -- danger sign
- Menu -- Similarity Score = 0.6264
- Template -- Similarity Score = 0.6264
- Rahul Dravid -- Similarity Score = 0.0
- template template menu -- Similarity Score = 0.6
- it can be import template menu or export template menu -- Similarity Score = 0.876 -- Danger sign
- what difference does it make if its import template menu or export template menu or whatever template menu -- Similarity Score = 0.787 -- Danger sign
sentence-similarity
asked Mar 22 at 17:21
ashwar hussainashwar hussain
426
we are doing some exercise to see how can I calculate similarity between 2 sentences. Below specified is some analysis. When you observe even though the sentences DO NOT match the scores are pretty high.
We are planning to have an assessment done based on this similarity and below results makes it clear that we cannot use that. Any suggestions on how we can sort this out. Please help.
Sentence1 = “Export Template Menu”.
Test sentence are:
1. Import Template Menu
2. Template Menu
3. Menu
4. Template
5. Rahul Dravid
6. Template template menu
7. it can be import template menu or export template menu
8. what difference does it make if its import template menu or export template menu or whatever template menu
When similarity score using gensim vectorization then
- Import Template Menu -- Similarity Score = 0.95984 -- danger sign
- Template Menu -- Similarity Score = 0.7096 -- danger sign
- Menu -- Similarity Score = 0.6264
- Template -- Similarity Score = 0.6264
- Rahul Dravid -- Similarity Score = 0.0
- template template menu -- Similarity Score = 0.6
- it can be import template menu or export template menu -- Similarity Score = 0.876 -- Danger sign
- what difference does it make if its import template menu or export template menu or whatever template menu -- Similarity Score = 0.787 -- Danger sign
sentence-similarity
sentence-similarity
asked Mar 22 at 17:21
ashwar hussainashwar hussain
426
asked Mar 22 at 17:21
ashwar hussainashwar hussain
426
asked Mar 22 at 17:21
ashwar hussainashwar hussain
426
asked Mar 22 at 17:21
ashwar hussainashwar hussain
426
asked Mar 22 at 17:21
ashwar hussainashwar hussain
426
426
Using the approach suggested in stackoverflow.com/questions/22129943/… using google News vectors results look more decent .. but its not able to get into more specific vocabulary. Can you train this model some how by using our own vocabulary?
– ashwar hussain
Mar 22 at 19:11
add a comment |
Using the approach suggested in stackoverflow.com/questions/22129943/… using google News vectors results look more decent .. but its not able to get into more specific vocabulary. Can you train this model some how by using our own vocabulary?
– ashwar hussain
Mar 22 at 19:11
Using the approach suggested in stackoverflow.com/questions/22129943/… using google News vectors results look more decent .. but its not able to get into more specific vocabulary. Can you train this model some how by using our own vocabulary?
– ashwar hussain
Mar 22 at 19:11
Using the approach suggested in stackoverflow.com/questions/22129943/… using google News vectors results look more decent .. but its not able to get into more specific vocabulary. Can you train this model some how by using our own vocabulary?
– ashwar hussain
Mar 22 at 19:11
add a comment |
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Using the approach suggested in stackoverflow.com/questions/22129943/… using google News vectors results look more decent .. but its not able to get into more specific vocabulary. Can you train this model some how by using our own vocabulary?
– ashwar hussain
Mar 22 at 19:11