# Questions tagged [vector-space-models]

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### What is the difference between finding the cosine angle and using logistic regression for 2 word vectors?

For finding the similarity between 2 documents, what is the difference between finding the cosine angle between 2 word vectors and using logistic regression?
31 views

### How to compare cosine distances across two groups of words?

I am using a word2vec model based on Wikipedia corpus. I was looking for a way to quantify if two sets of words - s1= {a1, a2...}...
26 views

### How come same cluster category be separated?

I have these 200 vectors which were clustered using K-means clustering based on keywords weight similarity that was given by TF-IDF (Term Frequency - Inverse Document Frequency). The vectors were ...
28 views

### Is it accurate to say that “K-means clustering the vectors based on keywords weight similarity”?

Long story short, I have 200 vectors as a result of TF-IDF (Term Frequency - Inverse Document Frequency) on thousands of keywords in hundreds of vectors. The total number of unique keywords that I got ...
24 views

### what is the difference between positional vector and attention vector used in transformer model?

what is the difference between positional vector and attention vector used in transformer model ? , i saw a video in youtue and the defintion for positional vector was give as :* "vector that ...
5 views

### Difference in Plots of VAR Plot_Forecast vs Simple Overlay on Pyplot

I am sure, I am doing some thing extremely silly but for the life of me not able to figure our cause of the issue. So here it is: Step 0: Form my training set ...
32 views

### How can we use the cosine similarity formula on document feature vector without a direction?

In mathematics, a vector has both magnitude and direction. In data science, for identifying document similarity we convert the document into a feature vector. Then apply cosine angle formula between ...
14 views

### How to represent a document in test data with the Document-Term Matrix created from the training set?

I build a classifier of documents using the vector representation of each document in the training set (i.e a row in the Document-Term Matrix). Now I need to test the model on the test data. But how ...
27 views

### Why is n-grams language independent?

I don't understand how n-grams are language independent. I've read that by using character n-grams of a word than the word itself as dimensions of a vector space model, we can skip the language-...
109 views

### Building Search Engine using Vector Space Model using a private database

Im trying to build a search engine for a private dataset using vector space model and have encountered following problem. Dataset Dataset is private. It is a collection of unstructed pdf . I have ...
126 views

### Can 2 different OOV words get the same vector in FastText?

Since FastText sums up the vectors(order is not considered) of an OOV word's subwords, is it possible for two different OOV words to get the same vector ? If so, then can you give an example?
3k views

### Getting 'ValueError: setting an array element with a sequence.' when attempting to fit mixed-type data

I have already seen this, this and this question, but none of the suggestions seemed to fix my problem (so I have reverted them). I have the following code: ...
26 views

### What is the best technique to transform documents into vectors?

What is the best algorithm between doc2vec and Singular Value Decomposition (SVD) to transform a set of 600 documents of around 1000 words each into vectors ?
110 views

### ways to represent document by its keyword vectors

I have documents, say for example, D1, D2, D3... Dm. Every Di has its individual components or keywords k1, k2, k3,... kn, where ki is an n-dimensional vector. The number of individual components ...
366 views

### How to dual encode two sentences to show similarity score

I've been trying to grasp the concept of Google's semantic experiences. By using it, I'm planning to implement a semantic query tool. With universal sentence encoder I can first pre-encode all ...
24 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 ...
48 views

### What are the main distribution semantics based algorithms?

I am aware that LSI, RRI and word embeddings are distributional semantics models. However, I am not certain if the below mentioned are also distributional semantic models. Non-Negative Tensor ...
48 views

### How can I train a model to modify a vector by rewarding the model based on the modified vectors nearest neighbors?

I am experimenting with a document retrieval system in which I have documents represented as vectors. When queries come in, they are turned to vectors by the same method as used for the documents. The ...
677 views

### Machine learning - Algorithm suggestion for my problem using NLP

I am looking for a machine learning algorithm for my problem. I have a set of sentences like, ...
3k views

### NN embedding layer

Several neural network libraries such as tensorflow and pytorch offer an Embedding layer. Having implemented word2vec in the past, I understand the reasoning behind wanting a lower dimensional ...
613 views

### Stacking/Concatenating/Combining two vector space models

I have two vector-space models, with different dimensions. The number of vectors in one model is the same as the number of vectors in the other. I.E: if I have vector representation for a car in one ...
107 views

### Collection Of Variable Length Sequences and Descriptions: A Search Problem

I have a tough problem and need some advice: Suppose I have a collection of variable length sequences, many of which are unique -- imagine the moves to a chess game, eg d4 Nf6 c4 g6 Nc3 Bg7 ...