Questions tagged [cosine-similarity]
An angular-type similarity coefficient between two vectors. It is like correlation, only without centering the vectors.
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LSA and cosine similarity approximation with large matrix
This question is the non-r related version of this one
I have a tdm with 16k x 350k dimension, for which I am trying to get the document-document similarity (cosine type). With RSpectra I have found a ...
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How to calculate Cosine Similarity from Keras model?
I'm trying to make hybrid recommender system that recommends movies to users from Movielens dataset.
Its Content part is based on Doc2Vec model from gensim library and its Collaborative Filtering part ...
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Understanding distance correlation computation for Multivariate Data
The original question and answer is in this link : Understanding distance correlation computations
Since I do not have enough reputation, I don't have the right to comment. This is the main reason why ...
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Scalar similarity measure between two vectors including both angle and magnitude
I have different models, predicting a vector $\boldsymbol{v}\in\mathbb{R}^3$. Now I would like to compare the performance of these models against a baseline vector $\boldsymbol{b}\in\mathbb{R}^3$, for ...
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What is the difference in interpretatation between Cosine Similarity and Correlation? [duplicate]
I'm studying PCA analysis and working with the FactoMineR an factoextra libraries in R. After generating a PCA object (with the PCA() or prcomp() functions) I access the "var" variable to ...
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Given embedding vector A and vector B, how to find top k embedding vectors such that they are similar to vector A and dissimilar to vector B
Which would be better approach for getting top k embedding vectors such that they are similar to embedding vector A and dissimilar to vector B.
Approach 1:
calculate ...
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Cosine similarity seems to perform better with higher dimensions than Euclidean distance? Should this be the case?
I've generated 100 random vectors (data points) in n∈[1,...,50] dimensions. I then compared distances between each pair of vectors and calculated the mean value. I've done this for all dimensions ...
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How Can I Reduce Similarity Analysis of Multiple Time-Series Vectors into a Single Value?
I have ~15 independently-sourced vectors with about 1600 samples in each. They are basically continuous, ~1 Hz, from t=0 to 22 minutes. The nature of the dataset is such that the signals are ...
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Search, rank and recommend in large text datasets
Imagine you are Spotify and you have billions of songs. Assume that each of these songs are transcribed into text. How do you design your search and recommendation pipeline such that when somebody ...
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Why very different cosine similarity scores when: mean(cos_sim(A, B), (A, C)) than when comparing to concatenated: cos_sim(A, concat(B, C))
I am trying to compare rhetorical similarity of politicians to the rest of their party in 2010.
Say party 1 consists of politician A, B and C. Each politician has made one speech in 2010.
If I want to ...
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Why is cosine similarity a lot higher between one document and all other documents grouped than vs the mean of each
I am trying to calculate a cosine similarity score for speeches made by various politicians.
Say I have politician A who belongs to party A. Party A has 20 other politicians who have made a total of ...
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Measuring similarity between students to build an exam recommender system
I am playing around with the following problem:
I have various groups of students from various schools and they receive online questions. A group receives the same questions, but different groups in ...
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cosine similarity with weights
We're doing pairwise similarity computation for some real estate properties. Our data goes something like this:
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Is cosine similarity applicable for BM25 weighted vectors?
It seems to be very common to use cosine similarity for TF-IDF weighted vectors for comparison of documents and their retrieval.
I am currently looking into the BM25 weighting scheme and here it seems ...
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How to calculate the level of cosine similarities across observations within a class and compare with other classes in text analysis?
I know that I can use cosine similarity to calculate the pairwise similarity between any two observations. But my problem is that I want to see if the observations in one class is more similar to each ...
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measure the overall similarity between two vectors
I have two paired vectors which report the number of times each object was found in the two experiments (the count value could be 0 or greater (e.g. 5,10,1000, etc)). I want to compare them and get a ...
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Cosine similarity with vectors of different lengths (time series)
I have time series of different lengths with different patterns. I want to find the similarity between them in such a way that it is defined from 0 to 1 and the measure takes into account the length (...
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Is combination of squared Euclidean and normalized cosine distance follow Bregman-divergence?
I know that squared euclidean distance satisfy the property of Bregman-divergence. I wanted to do some experiments using combination of various distance metric. So I am curious to know if I add ...
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how to calculate cosine similarity for bow
let's say i have these two sentences:
S1:premier league meet target audience watch game buy messi
S2:everyone offer discount ticket watch messi
these two have went through stopword removal, ...
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Searching for a distance metric or distance similarity to compare two arrays of counts
Every object in my dataset is described as a vector of n = 200 continuous counts. I need to choose a measure to evaluate the similarity of two objects in the dataset. I want to satisfy the following ...
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Should I consider the contribution of a variable in correspondance analysis if the $cos^2$ is weak?
So I have this table that represents contribution and cosinus of variable in CA
I noticed that the most popular choice ( 1-5 hours ) has the weakest contributions and the weakest cosinus.
It made ...
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Are absolute differences between factor scores a good way to quantify the similarity different things rated on the same factors?
I have x images rated on 25 dimensions. I also have x words rated on those 25 dimensions.
When I factor analyze the ratings, I get the same four factors for images and words (though extracted in a ...
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Cosine similarity with recentering - collaborative filtering
I don’t know much about stats (nor maths), so I’m sorry if I’m not being very clear on this...
I’m trying to build a simple recommender system for books using collaborative filtering item by item.
I’...
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Question related to using Pooled Output from BERT for similarity between sentences
I was hoping someone could give me advice and feedback on my current approach and possibly suggest to me a possible alternative. I'm trying to find the sentences that are most similar using the pooled ...
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Finding Cosine similarity threshold (cut-off point) with Logistic Regression
I want to preprocess my data sets, removing similar articles. To do this, I'll perform cosine similarity, I don't know the best threshold (cut-off point) of my data set. I Found in this paper, there's ...
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Calculate similarity between two matrices
I have two matrices, $A$ and $B$, each of size $n\times m$, where $n$ is discrete time points, and $m$ are the variables measured (specifically, $n$ are dates and $m$ are investments measured in ...
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Baffled by cosine similarity - these results seem counterintuitive
Haven't used cosine similarity much in the past so getting into it now. Seeing results that are counterintuitive and would love your help making sense of them.
Assume these simple vectors:
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Euclidian distance vs cosine similarity
Currently I'm working on facial recognition. If I use encoding/feature vectors of 2 images which method will prove more accuracy, L2 norm or cosine similarity and why?
I read "ICA performs ...
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Cosine similarity for Categorical datasets?
Can I use Cosine similarity measure for estimating similarity/relationship between D1 and D2 (two categorical datasets)
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How to calculate similarity between two sets of items rated on a single dimension?
(I'm just making up variables for this example.)
Let's say I have 100 words rated on their pleasantness.
I also have 100 images rated on their pleasantness.
I then had participants rate the fit ...
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cosine of angle between random variables is equal to the correlation coefficient? [duplicate]
I have seen this said multiple times where (1) the cosine of the angle between the random variables (on a vector space) is equal to the correlation coefficient, and (2) the claim if random variables ...
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Difference between an interaction and combining two variables into one with a similarity measure?
Conceptually, what would be the difference between interacting two variables in a regression and combining these two variables into one via a similarity measure? I'm looking at top managers and boards ...
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What are the conditions for 2-dimensional curve fitting when the estimator function is a type of sine and cosine?
What are the conditions for 2-dimensional curve fitting when the estimator function is a type of sine and cosine?
For example I wanted to estimate F=xy with Asin (((n*pi)/L)*x)sin ((((npi)/L)*z) ...
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Which text similarity algorithm should I use to compare the context of Instagram hashtags?
For a study I am comparing companies based on the posts written by their Instagram followers. I apply the following technique:
Nike has 1.000.000 followers.
2000 random followers of Nike are selected ...
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Should we apply PCA before calculating similarities in high-dimensional space if my observations have length 1?
I have high-dimensional space (around 20 features) and I want to calculate similarity based on the angle of observation, not the magnitude. I have a nice function that can compute euclidean distance ...
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Normalized Levenshtein distance and triangle inequality
One question regarding to the triangle inequality of normalized Levenshtein Distance. I use the well-known form D(X,Y) = 1 - d(X,Y) / MAX(|X|,|Y|) where ...
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Rao-Stirling diversity index
I need help to calculate the Rao-Stirling diversity index. I tried it several times but cannot achieve equal results to R packages yet (e.g. diverse).
I used the Rao-Stirling diversity index as ...
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How to find the list of nearest vectors if ony a vector is given?
I know there are many ways to compute similarity of two different non-zero vectors but is it possible to get a list of nearest vectors whose values are continous given a single continous vector.
Lets ...
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Cosine similarity for recommendation systems
Recently picked up recommendation systems and was going through User Based Collaborative Filtering(UB-CF).
Somewhere in the text, it specified that cosine similarity is one of the measures to find ...
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Why is the cosine similarity between these (seemingly uncorrelated) vectors so high?
I am calculating the correlations between vectors of experimental data by a variety of methods (Pearson's, cosine similarity, Euclidian distance, etc.). Most the results look fine, but occasionally ...
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Cosine similarity vs quadratic objective function
The aim is to calculate the similarity between two foods given the nutritional content of each. After some reading, it seems the most popular measure for this sort of problem is the cosine similarity ...
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Does it make sense to normalize vectors after PCA for cosine distance?
I start off with word2vec embeddings and process them in the following way:
Standardize dimensions to mean 0 and standard deviation of 1
PCA to keep the top k-dimensional eigenvector, whereby ...
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Deep item-based recommender objective function
I'm trying to understand the following paper written by researchers at eBay that uses deep learning to overcome the problem of making recommendations when you mostly have one-of-a-kind items. A ...
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Extension of the K-Nearest neighbor algorithm to get results in different neighborhoods
I would like to use the kNN algorithm to find the closest neighbor to a vector. But I would like it to limit to a point per neighborhood (radius)
In this image, given the point in red, I would like ...
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Should I normalize the vectors by row or by column before performing cosine similarity?
I have a dataset which contains vectors of different features that generated from subtitles in movies, something like:
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How can I define a accuracy measure for word2vec predictions
I have a data set consisting of tags and some classes.I'm suppose to find the nearest class to each set of tags with Word2vec embeddings and cosine similarity.Each set of tags have multiple classes ...
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the accuracy of covariance between two high-dimensional vectors
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Is the covariance between high-dimensional vectors less accruate than covariance between two vectors in low-dimensional vecotrs?
I am asking this questio to check if there is a need for '...
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analyze time-series consine similarity matrices (in R)
I have calculated the cosine similiarity between multiple users for 10 years separately.
I can visualize and cluster the matrix of each year but I was wondering if there is a smart approach, vignette ...
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Are there advanced "cos similarity" that influence of dim size is less?
I found that the cosine similarity is
affected to the effect of "Curse of dimension" by trying the following simulation.
create(select) two vectors form uniform random numbers U[-1, 1], each dim = 2,...
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Did my text data come from two distinct distributions?
I have labeled text data from two different classes. I have calculated tfidf feature representation of all the sentences in question. I have a huge matrix where rows are sentences and columns are ...
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