Questions tagged [similarity]
The similarity tag has no usage guidance.
287
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Get accurate alias list of people without information on aliases
I'm working on a project where I have a large dataframe of paintings (from the Art500k dataset), each row corresponds with a painting, containing the author's name in the ...
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12
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Clustering of two datasets in different years
I want to analyze two datasets by running a clustering algorithm on both and comparing the results. The two datasets have the same variables. The only difference is that one dataset is from 2010 and ...
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4
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Clustering or Finding Similarities Among Portfolio Allocations
I am trying to cluster a set of portfolios with percentage allocations among Stock, Bond, Other, and Cash. I am not sure what's the best way to go about this because the variables are interdependent ...
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22
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Proper metric for measuring the similarity between two images
I want to calculate the similarity between these two images:
and
These are brain topography maps and colors inside the circles represent the area being activated while watching TV. Thus I am looking ...
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25
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Using text embeddings directly to compute similarity vs using them as features for a model that predicts similariy
Say you have a problem where you have a query and a set of result documents and you want to rank the result documents according to the query. Say also you have embeddings for the query and for the ...
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73
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how does netflix calculate the percentage match scores?
I know that these scores are calculated by considering the users' past interactions. But I need some details here. For example, suppose that user A has watched the movies X, Y, and Z. For a new movie ...
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1
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62
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What's Best way in selecting right model for document comparison
We have different pre-trained models like BERT, USE, ELMo, Word2Vec, FastText, etc..,
we have documents in different sizes (large, medium, small). now, we want to do document similarity. how can we ...
- 57
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41
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Distance Metric for a dataset with embeddings and numerical columns
I'm trying to build an Approximate Nearest Neighbours model that can fetch similar records in a dataset, that are contextually similar. For example, for a record of job=Software Engineer and age=25, a ...
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18
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Finding Look alike customers
I have a set of customers and their attributes (say spend/balance/etc.) per month.
At month X something happen for some customers, but not all (call this set A).
So, now I want to find customers who ...
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28
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Implementing efficient "Customers who viewed this, also bought that" recommendation algorithm
I'm not sure how to formulate this but I'll have a go. This code should be completely reproducible given the data below. I hope I've been clear in my question.
I'm trying to implement a recommendation ...
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17
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Align sub-sentences with sentences using embeddings
I would like ask for ideas
So I have sub-sentences, embedded in the context of their respective full-sentences. Then, I have other full-sentences and I would like to find
a) if they have similar sub-...
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562
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How to handle similarity search on mixed data types vectors?
I think this question is one that many beginners run into and I could not find a decent generic guide for it.
My issue is the following. I want to evaluate similarity of vectors which have mixed data ...
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639
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Using pyspark to create a large precomputed cosine similarity matrix from text data
I would like to precompute a cosine similarity matrix for a large dataset (upwards of 5 million rows) using pyspark.
Here's what I have so far.
libraries:
...
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79
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Better results in Document similarity using Word2Vec
I try to cluster similar support-tickets in a technical domain. The support tickets are very domain-specific and are written in various styles, lengths, using abbreviation, etc.
I made a training-...
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27
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Comparing images in N channels
I have an "image" of NxN dimensions in m channels (for reference, m is less than 17) in my training set and validation set. I would like to compare images in the training set with those in ...
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52
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Matching items in a recommender system
I would like to ask for a proposal for a machine learning model that would be suitable for the following problem:
I have a training set where each element of type A corresponds to a certain number of ...
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17
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How to effectively use CharBERT for text similarity?
I'm looking into CharBERT for an university project, and I noticed that it was finetuned on many tasks like sentiment analysis, NER, and so on. I tried to use it to do text similarity by using only ...
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For Q&A NLP system, how to extract the most relevant embedding if it is a combination of top K embeddings?
From my understanding, a typical "AI" Q&A system has a (vector) database of embedded text (from a set of documents). And when a user asks a question, the user's question is embedded and ...
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Given a Query set, find elements in a pool that are similar to the elements in the query set
I had some curiosity and I was wondering if anyone could shed some light on this. So, let's say I have a query set $Q$ that consists of the following sets of words: {...
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22
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getting wrong cosine similarity when using face_recognition.faceencodings
I am trying to calculate cosine similarity between two face encodings returned by face_Recognition.face encoding() which 128d vector which always is above 0.8
also is the face encoding normalized ...
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34
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Is there a reference dataset for contextual similarity?
I'm doing some experiments with word embeddings to try to capture context-aware similarity, so that for example the word pair apple - hardware, are very dissimilar in the context of a fruit store, but ...
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84
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Best string similarity metric not considering word order
I'm sorry if the title is misleading, but I didn't really know how to explain what I am searching for.
I have a dataset containing two columns representing names and surnames of a bunch of people. ...
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2
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93
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Similarity with respect to a specific concept in text embeddings
In text embeddings, cosine similarity is often used to find texts similar to a search query.
However, I don't want to find a text that is overall similar, but similar with regards to a specific ...
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21
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Applying feedback in content based recommendation
I have a content based recommender system, which finds similar items given a list of past liked items using cosine similarity.
What would be best way to implement feedback or personalization in the ...
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1
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39
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Best way to compare classification output between different locations
I ran a neural network for 20+ different locations across the United States. At each location I have a list of their predictions in an array. This looks something like this...
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17
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Find similarity in book pages
I try to find article which deals with book page similarity detection.
I already work on image similarity using embedding but in book case, I wanted to know if there are a more specific algorithm to ...
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2
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4
answers
538
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Algorithm to determine whether the first row in CSV is likely to be a header row or a data row
I have a fairly simple problem. I am trying to determine whether the first row in CSV is likely to be a header row or a data row. Looking at single column, the problem can be simplified to: I have a ...
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38
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The best approach and library for time-series similarity
I have a time-series classification problem with IoT signals. The training dataset has seven target signals.
I used tsai as a fastai/torch library, and I achieved satisfying results.
However, in a ...
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46
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Siamese network for a sequence-to-sequence generation
Shall I use the siamese network for a sequence-to-sequence generation problem in machine learning?
Eg:
Input 1: Sentence 1 (sequence)
Input 2: Sentence 2 (sequence)
Output: Newly Generated sentence (...
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3
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207
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How to vectorize and speed-up double for-loop for pandas dataframe when doing text similarity scoring
I have the following dataframe:
...
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50
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What is the fastest way to detect lag and calculate cross correlation of two binary time series?
Example,
arr1 = array([0,0,0,1,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,0,0])
arr2 = array([1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0])
arr2 is almost perfectly correlated with ...
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1
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25
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Find short similar sequences in long time series
Input data is a short time series, and I want to find a scalable short series that looks like the input from a long time series, should I use the sliding window, or do you have any better suggestions?
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121
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Nearest Neighbor Recommendation System w/ categorical variables
I would like to build a recommendation system:
no ratings are available at the time of recommendation, therefore only a purely context-based recommendation system is needed
as input features answers ...
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3
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Why use cosine similarity instead of scaling the vectors when calculating the similarity of vectors?
I'm watching a NLP video on Coursera. It's discussing how to calculate the similarity of two vectors. First it discusses calculating the Euclidean distance, then it discusses the cosine similarity. It ...
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783
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Adjusted Cosine Similarity With Zero Vectors
I create a recommendation engine which finds item similarities according to user ratings. I'm trying to use adjusted cosine similarity to find similarities. I follow these steps.
Find mean rating of ...
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103
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Compute similarity with given weights for each different feature
I would like to find similar products based on the features.
I have:
3 categorical features (X1,X2,X3)
1 numerical (continuous) feature (X4)
1 date feature (X5)
Therefore, I want to give a pre-...
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1
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20
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Recommendation engine optimization
Recommendation engines typically include propensities to like the items (e.g, in a content-based approach). However, they generally do not take into account the fact that the customer may buy the ...
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2
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55
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Which method of correlation is appropriate for two paired lists of numbers?
I have a program which produces an image, and I use a metric to understand how accurate that image is. I choose five cases (A, B, C, D, E), and make a list of the accuracy metric for each case:
...
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1
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47
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A way to perform voting and select a candidate based on nearest neighbours
I'm working on a project where I use FAISS to retrieve n neighbouring vectors based on a query vector. The data in question is textual and is being embedded by using a machine learning model to create ...
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235
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How to measure similarities between two datasets with same features?
I have multiple datasets with the same features, a few numerical and a few categorical. The only difference is that they are market behavior for different countries. I wanted to know if there is a way ...
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1
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630
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Building a graph out of a large text corpus
I'm given a large amount of documents upon which I should perform various kinds of analysis. Since the documents are to be used as a foundation of a final product, I thought about building a graph out ...
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1
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94
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What is the logic/algorithm behind 'did you mean' suggestion by search engines, command suggestion in command prompt like git?
For eg. https://stackoverflow.com/questions/307291/how-does-the-google-did-you-mean-algorithm-work
this is the logic behind google's did you mean algorithm - used for spell correction suggestion.
What ...
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97
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High Performance Classification or Similarity Algorithim for Mixed Data Types?
I have a database holding 10-ish features that describe different breeds of dogs. They are mostly categorical features, but some provide ranges for values. Here's a demo representation of the database,...
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1
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35
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Word similarity considering special characteristics
I'm looking for an algorithm that computes the similarity between two strings just like the levenshtein distance. However, I want to consider the following. The <...
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2
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1
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2k
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Measuring similarity from massive embedded vectors
I am given a set of 10,000 journal articles, with their corresponding 100th-dimension embedded vectors. (The way they are embedded is unknown, but I'm guessing it is ...
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1
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50
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Document Similarity with User Preference
To measure the similarity between two documents, one can use, e.g. TF-IDF/Cosine Similarity. Supposing that after calculating the similarity scores of Doc A against ...
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285
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How to measure the similarity between two medical images of different imaging modalities according to similar objects in both of them?
I have two series of medical images each one from different imaging modalities.
According to that, I have been segmented the Region of interest (the object which appears in both modalities )using U-...
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25
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Transformer similarity fine-tuned way too often predicts pairs as similar
I fine-tuned a transformer for classification to compute similarity between names. This is a toy example for the training data:
...
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769
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How to choose similarity measurement between sentences and paragraphs
Problems
1. How to find appropriate measurement method
There are several ways to measure sentence similarities, but I have no idea how to find appropriate method among them for my data (sentences).
...
user120022
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143
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Dynamic Time Warping (DTW) for time series with different step sizes
Is it possible to use Dynamic Time Warping (DTW) algorithm as a method to find the similarity between two time-series data that have different step/measurement sizes? For example, one is measured ...
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