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Questions tagged [vector-space-models]

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13 views

How to include engineered features as factors, along with a CountVectorizer matrix?

I'm doing a classification task on Excel files. For the example in this picture, it would not really make sense to include the 4 columns on the right inside the CountVectorizer matrix. From my ...
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583 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: ...
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8 views

How to vectorize unigrams character to use LSH functions?

I would like to implement fuzzy search based on Bloom Filter and LSH hashing. The problem is that: I have found almost ready package to get ngrams from words, now I don't know how to generate vector ...
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24 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 ?
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2answers
52 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 ...
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6 views

Why don't we use training/observation data's vector similarity for building models on Tabular data? or if we do , can you name some?

Considering , we get a new observation, we try to find a 100 similar vectors from the training data and average the labels from them to get the prediction.
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1answer
193 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 ...
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23 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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1answer
38 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 ...
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0answers
47 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 ...
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3answers
451 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, ...
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2answers
2k 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 ...
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1answer
493 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 ...
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2answers
101 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 ...
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2answers
480 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
402 views

How to improve Vector Space Models with semantic similarity?

I try to construct a classic querying system where I find the most probable candidate text for a query by computing cosine similarities of TFIDF vectors of normalized text of possible answers. This ...