Questions tagged [cosine-distance]
A measure of the angular distance between two vectors. Usually defined as 1-(cosine similarity).
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questions
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1answer
44 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 ...
0
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1answer
10 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, ...
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1answer
53 views
Calculating cosine similarity between 3D arrays using Python
I have two matrices with multiple columns and three rows each. I calculated the cosine similarity (sklearn) but it gives the result as a matrix. How can I obtain one single value?
The matrices are the ...
1
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1answer
17 views
Checking TF-IDF Results
I am working with TF-IDF and cosine similarity to do document comparisons and given a document, which document in the data is the most similar. However, sometimes it returns a high similarity between ...
1
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1answer
42 views
word2vec word embeddings creates very distant vectors, closest similarity is still very far
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), ...
1
vote
1answer
144 views
Hierarchical clustering with precomputed cosine similarity matrix using scikit learn produces error
We want to use cosine similarity with hierarchical clustering and we have cosine similarities already calculated.
In the sklearn.cluster.AgglomerativeClustering documentation it says:
A distance ...
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0answers
83 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 ...
0
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2answers
408 views
how to create word2vec for phrases and then calculate cosine similarity
I have just started using word2vec and I have no idea how to create vectors (using word2vec) of two lists, each containing set of words and phrases and then how to calculate cosine similarity between ...
2
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3answers
42 views
Match a two items from two different receipts
I have two different invoices or receipts. One is a Purchase order one is something like a receipt(acknowledgement).
Suppose I have ordered(PO) Wine:
White Wine
Red Wine
Rose Wine
And I receive ...
2
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1answer
21 views
When I would use a specific similarity coefficient over another?
Like using Jaccards over Dice.
I want real examples, of when I would prefer to use Jaccards, Dice, Cosine or any other similarity coefficient.
2
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1answer
302 views
cosine similarity between items (purchase data) and normalisation
I'm using IndexedRowMatrix which represents the products's user purchase behaviours and in order to build product recommendations, I use cosine similarity to calculate similarities between products. ...
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0answers
18 views
Best way to find dissimilarity in a 6x2 DataFrame?
I'm new to data science and am currently learning different techniques that I can do with Python. Currently, I'm trying it out with Spotify's API for my own playlists.
The goal is to find the most ...
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0answers
20 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 ...
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3answers
196 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 ...
2
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0answers
697 views
Clustering with cosine similarity with specific threshold (in Python)
Given :
1, either given the origin data matrix X , such as X = [[1,1,1,1],[1,1,-1,-1],[1,1,1,-1]]
or given the cosine similarity matrix of the original data X , ...
2
votes
1answer
1k views
How to find similar time series?
I've got a collection of yearly data (one value per year per category), and I'd like to find series that are most similar to one another.
Example data is here.
I don't know much about data science, ...
5
votes
1answer
8k 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]
[...
5
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2answers
5k 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?
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2answers
433 views
Confusion with cosine similarity
In information retrieval when we calculate the cosine similarity between the query features vector and the document features vector we penalize the unseen words in the query.
Example if we have two ...
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1answer
3k views
Cosine similarity between query and document confusion
I am going through the Manning book for Information retrieval. Currently I am at the part about cosine similarity. One thing is not clear for me.
Let's say that I have the tf idf vectors for the ...
0
votes
1answer
2k views
Create similarity matrix
I have a training set and a testing set of vectors. All the vectors are labeled.
For each labeled vector in the testing set, there are 3 vectors in the training set with the same label.
I'm using ...
1
vote
1answer
713 views
Computing Item-to-Item Similarity Using Cosine
I have a "User x Item" matrix as below:
user item1 item2 item3
u1 2 0 3
u2 1 2 0
u3 4 3 1
u4 0 2 2
I want to computer the ...
1
vote
2answers
809 views
What techniques should I use to compare the similarity between a bunch of texts?
If I have a list of job postings stored as raw texts and I want to compare the similarity of all the job postings to a given resume, what techniques or algorithms should I use?
I'm thinking of ...
4
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1answer
163 views
How should I evaluate writing quality to compare two articles(which article is better suited/written for a topic ) according to their content?
I am trying to come up with a platform which can Synthesize Quality Content among many articles found about some particular "topic" on the internet, the algorithm should be able to say recommend top ...
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0answers
294 views
Recommendation matrix as a product of User Similarity and Ratings
For both item-item and user-user collaborative filtering the recommendation matrix $Γ_{m x n}$, which is an (m x n) matrix, can be defined as:
$$Γ(i,j)=r_{ij}$$
For user-user collaborative ...
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4answers
4k views
Alternatives to TF-IDF and Cosine Similarity when comparing documents of differing formats
I've been working on a small, personal project which takes a user's job skills and suggests the most ideal career for them based on those skills. I use a database of job listings to achieve this. At ...
2
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1answer
762 views
Is it possible to use Jaccard similarity instead of Cosine similarity in gensim document similarity?
I am using gensim library to compute similarity between documents but it only uses cosine similarity. I was wondering if there was a way to use jaccard similarity or any other similarity measure for ...
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1answer
12k views
Calculate cosine similarity in Apache Spark
I have a DataFrame with IDF of certain words computed.
For example
...
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2answers
250 views
What should be the value of non-rated field when finding cosine similarity
I am working on a very basic book recommender system. I want to know what to do with the fields which aren't rated by the user when finding cosine similarity, should we ignore them and calculate only ...
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2answers
1k views
Word analysis in Python
I have a list of documents which look like this:
["Display is flickering"]
["Battery charger is broken"]
["Hard disk is making noises"]
These text documents are ...
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0answers
518 views
Compute angle of vector in word2vec models
If I understand correctly, the most_similar function computes the cosine similarity of the vector with all other vectors and finds the closest one. The vectors ...
3
votes
3answers
4k views
How to find similarity/distance matrix with mixed Continuous and Categorical data?
Say I have a dataset like this:
Hotel HasPool AvgPrice
1 1 $123
2 0 $234
3 1 $200
Currently I have broken down the ...
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2answers
133 views
Is Vector in Cosine Similarity the same as vector in Physics?
I'm new to Data Science. I'm trying to understand cosine similarity and it seems like the equation is about finding the distance between two vectors. From what I've Googled, a vector needs to have ...
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0answers
247 views
tf-idf clustering
I have over a million text documents that I would like to cluster. I used tf-idf modeling and term vector cosine for identifying similar documents in the corpus, which appeared to work well.
Some ...
5
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1answer
6k views
Cosine Distance > 1 in scipy
I am working on a recommendation engine, and I have chosen to use SciPy's cosine distance as a way of comparing items.
I have two vectors:
...
