# Questions tagged [cosine-distance]

A measure of the angular distance between two vectors. Usually defined as 1-(cosine similarity).

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### How to create word2vec for phrases and then calculate cosine similarity

I just started using word2vec and have no idea how to create vectors (using word2vec) of two lists, each containing set of words and phrases and then how to calculate the cosine similarity between ...
27 views

### K-means++ with cosine distance

I am wondering how to implement k-means++ with cosine distance, acording to quote below (wikipedia), which says, that distance needs to be squared. But with square is lost direction of distance which ...
60 views

### Cosine similarity between sentence embeddings is always positive

I have a list of documents and I am looking for a) duplicates; b) documents that are very similar. To do so, I proceed as follows: Embed the documents using paraphrase-xlm-r-multilingual-v1. ...
31 views

### Plotting cosine similarities in 3d space from word embeddings

I'm working on a project in which I want to estimate biases from a large corpus of newspaper articles using word2vec. Following this and this paper, biases are calculated by constructing dimension x ...
370 views

### counter vector fit transform cosine similarity memory error

count_matrix = count.fit_transform(off_data3['bag_of_words']) I have count_matrix shape with count_matrix.shape (476147, 482824) ...
10 views

### How to compute similarity matrix for strings efficiently? [duplicate]

Here I'm trying to compute similarity between 1000 cross 10000 strings (using Levenshtein distance), I'm using a dataframe approach where you just need to compare n(n-1)/2 comparisons instead of n*n. ...
269 views

### How fit_transform, transform and TfidfVectorizer works

I'm a machine learning beginner and I tried to use the cosine similarity on fuzzy matching purpose. In the following example I want to compare 'data_dirty' with 'data_clean' : When I have to ...
17 views

### applicability of relative similarity computation

I've computed the cosine similarity between a & b (=x) and ...
866 views

### clustering 2-dimensional euclidean vectors - appropriate dissimilarity measure

I've got a set of approx. 50 000 2-dimensional euclidean vectors which are connected with 20 groups, i.e. each group has approx. 2500 2-dimensional euclidean vectors. My data includes endpoints ...
9 views

### Inner working behind combining two distance function as one function for similarity measure

I am comparing two images and for this I am testing various similarity function. For my case, Euclidean works much better than cosine(20% difference). However, I tried to combine two distance function ...
23 views

### String Matching [closed]

I have to work on 2 datasets where I have to find out the duplicates in addresses present in both the dataset. I am a bit confused that which one of the Levenshtein distance or cosine similarity, I ...
85 views

### Siamese networks vs Semantic similarity (may be gensim)

I am trying to understand the Siamese networks . In this vector is calculated for an object (say an image) and a distance metric is applied (say manhatten) on two vectors produced by the neural ...
519 views

### Elbow method for cosine distance

I have clustered vectors by cosine distance using nltk clusterer. If I understand correctly, Y axis for elbow method in euclidian distance would be the sum of every distance (squared) between centroid ...
47 views

### Document matching with more priority to certain features than others

I am working on recommendation systems wherein I need to match the similarity of 2 users. Now, I know that I can use Tfidf vectorizer to calculate the the cosine similarity score between them. But, ...
11 views

### Results interpretation of AgglomerativeClustering labelling

First of all I would like to say that I'm quite new to python and even more new to scikit, and I'm also a self learner, so please forgive my banal question, but it doesn't look banal to me. So, I have ...
295 views

### How to get the probability/closeness of a sample belonging to a specific cluster?

I'm new to this so please let me know if my logic of comparing cosine similarity and k-means is incorrect I got a set of ...
52 views

### Cosine vs Manhattan for Text Similarity [closed]

I'm storing sentences in Elasticsearch as dense_vector field and used BERT for the embedding so each vector is 768 dim. ...
41 views

### how to calculate the cosine similarity between two files?

I am using spark and scala to implement an issue. files contain phrases or sentences. I want to use domain based method to calculate the cosine similarity between tags.I convert two files into a ...
29k views

### cosine_similarity returns matrix instead of single value

I am using below code to compute cosine similarity between the 2 vectors. It returns a matrix instead of a single value 0.8660254. [[ 1. 0.8660254] [...
2k views

### Cosine similarity with arrays contaning NaN

I am trying to calculate a cosine similarity using Python in order to find similar users basing on ratings they have given to movies. As it can be expected there are a lot of NaN values. I am using ...
29 views

### Matching documents from different sets with tfidf and cosine distance

I have two different set of documents S1, S2, with 30 text documents each. Using some text representation method, such as tfidf ...
36 views

### Can I sum up feature vectors of a user‘s collection?

I want to find items that are similar to items users already have in their collection. Every item has attributes, so I created feature vectors where every element of the vector represents an attribute ...
983 views

### word2vec word embeddings creates very distant vectors, closest cosine similarity is still very far, only 0.7

I started using gensim's FastText to create word embeddings on a large corpus of a specialized domain (after finding that existing open source embeddings are not performing well on this domain), ...
37 views

### Item-to-Item recommendation using DNN

I am new to DNN still learning, have a need to build item-to-item content based recommendation using DNN. For example, say I have a column of strings where each row represents a document I need to ...
110 views

### pairwise_distances with Cosine and weighting

Is there a way to get a weight into the pairwise_distances(X, metric='cosine') Potentially using **kwrds? ...
22 views

### Is there a way to calculate the cosine distance between 2 time series?

Let's say I have time series data of City A, City B, City C & City D that looks like this: ...
96 views

### Cosine Similarity but with weighting for vector indexes

I am very new to NLP and although this seems like a basic question I don't know how to search for an answer online. This is my problem: I have extracted and ranked keywords from 2 text sources: A ...
321 views

### Calculate the similarity between pairs of time series data

I have 5 pieces of time series data. It is the weekly sales of 5 different stores (A,B,C,D,E). There are no missing values. A quick visual inspection shows that these 5 pieces of time series data have ...
19 views

### TensorFlow: CosineDifference ObjFunc Constant throughout training

The following example is a simplified version of what I'm working on. I'm trying to find a neural network which minimises the cosine distance. The reason I have implemented my own cosine difference ...
82 views

### Is normalizing term weight necessary when cosine similarity is used in retrieval?

When using cosine similarity in information retrieval, document vector length and query vector length are used for normalization. So if TF-IDF is used as a weighting function, then using raw frequency ...
15k views

### Can I use cosine similarity as a distance metric in a KNN algorithm

Most discussions of KNN mention Euclidean,Manhattan and Hamming distances, but they dont mention cosine similarity metric. Is there a reason for this?
98 views

### Evaluate document similarity / content-based recommender system

I'm planning on building a basic content-based recommender system with word2vec and cosine similarity. The data consists of 300k documents in varying length. How do I evaluate my model if I have no ...
183 views

### Question about BERT embeddings with high cosine similarity

Under what circumstances would BERT assign two occurrences of the same word similar embeddings? If those occurrences are contained within similar syntactic relations with their co-occurrents?
33 views

### finding similarity of a new datapoint

I have built a recommendation engine using cosine similarity. When I want to find all the records similar to a given record that is already present in the dataset it works. Consider a case, a user ...
220 views

### If i use use BERT embeddings for if cosine(sent1,sent2) > 0.9, then is it fair to assume s1 and s2 are similar

According to BERT author Jacob Devlin: I'm not sure what these vectors are, since BERT does not generate meaningful sentence vectors. It seems that this is doing average pooling over the word tokens ...
55 views

### Is the magnitude of a word vector correlated with the frequency of the word in a text?

In order to find the similarity between words, cosine similarity seems to be the most common measure to use. In a conversation that I had about this topic, someone mentioned that words that mean more ...
711 views

### Semantic similarity between two or more sentences

I need to determine how similar sentences (in meaning) are to one another. In order to do it, I have been considering an algorithm (cosine similarity) to determine the similarity between sentences. I ...
1k views

### Why is the cosine distance used to measure the similatiry between word embeddings?

While computing the similarity between the words, cosine similarity or distance is computed on word vectors. Why aren't other distance metrics such as Euclidean ...
51 views

### Is summing a cosine similarity matrix a good way to determine overall similarity?

I'm trying to similar research abstracts, so I'm using word embeddings to convert words into 1x768 vectors, so overall turning abstracts into embeddings with shape (#ofwords, 768). Cosine similarity ...
4k views

### memory error in matrix cosine_similarity

I have (20905040, 7) of a dataset to recommend 10 different product to the user it could be larger than that but anyway I got memory error when processing the ...
1k views

### Word analysis in Python

I have a list of documents which look like this: ...
449 views

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### NearestNeighbors testing

I have used nbrs = NearestNeighbors(metric= 'cosine', algorithm='brute').fit(items_features) distances, indices = nbrs.kneighbors(item_features) to find some ...
100 views

### Understanding cosine distance with word vectors

I'm a new DL4J user, and I'm running all the works of Shakespeare through a Word2Vec neural net. I've got a pretty basic question about how to understand the results so far. In the below example, ...
I have a set of resumes $R=\{{r_1,...,r_n\}}$, which I've transformed to a vector space using TF-IDF. Each resume has a label, which is the name of their current employer. Each of these labels comes ...