-
```
Rares' FuzzyJoin will run the following query with the default similarity
threshold 0.8f:
use dataverse fuzzyjoin;
for $i in dataset('DBLP')
for $j in dataset('CSX')
where similarity-jaccard(wo…
-
```
Rares' FuzzyJoin will run the following query with the default similarity
threshold 0.8f:
use dataverse fuzzyjoin;
for $i in dataset('DBLP')
for $j in dataset('CSX')
where similarity-jaccard(wo…
-
Could you make Neighbor word and similarity accessible?
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Not familiar with Torch, it seems not like "SG-Retrofit" ?
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## Feature Description
I would love to have the option to calculate either the [cosine similarity](https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.cosine.html) between two…
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# URL
- https://arxiv.org/abs/1703.05916
# Affiliations
- Yuya Sakaizawa, N/A
- Mamoru Komachi, N/A
# Abstract
- An evaluation of distributed word representation is generally conducted usinga wo…
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Hello, thank you for your great work, may I ask what part of the implementation code of the Noise-Aware-Masking module, thank you
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`Traceback (most recent call last):
File "D:/projects/miscellaneous/test.py", line 5, in
ws_tool = WordSimilarity2010()
File "C:\Users\00015426\AppData\Local\Programs\Python\Python37\lib\s…
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I see two primary issues with your solution. When finding the similarity between the speeches, you are not calculating `word_count_similarity` or `ngram_similarity` correctly, but `sentence_length_sim…
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I see word embeddings as some potentially low hanging fruit for a more robust product. Namely, word embeddings, such as GloVe, are (A) additive and (B) can quantify the similarity between words/phrase…