LSA stands for Latent Semantic Analysis, a natural language processing technique which involves analysing the relationships between documents and terms they contain by producing a set of related concepts.

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K-means on cosine similarities vs. Euclidean distance (LSA)

I am using latent semantic analysis to represent a corpus of documents in lower dimensional space. I want to cluster these documents into two groups using k-means. Several years ago, I did this using ...
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49 views

Different results for Singular Value Decomposition (SVD) using different tools

I am currently implementing Latent Semantic Analysis in Java using the EJML library for the preliminary Singular Value Decomposition (SVD). I am testing my code against the original term frequency ...
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Latent semantic classification

How can I create a training data set for document classification using LSA? I have created a term-to-document matrix and have class labels also. I don't know whether to add these class labels in a ...
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15 views

single categorical DV, single countinuous IV

Background: I have a set of student answers to some questions and also their scores, whether the answer is correct or not (1 - not correct, 2 - somewhat correct, 3 - correct). I also have for each ...
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How can I interpret the results of LSA?

I implemented LSA on MATLAB. I have a $D\times N$ term-document matrix, where $D$: # of words, $N$: # of docs. I did low-rank approximation using SVD, and got $$X_k = U_k \cdot S_k \cdot V_k' ...
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75 views

how to identify salient words after LSA?

I used Latent Semantic Analysis (LSA) to extract latent topics (i.e., the polynomials coefficient1*word1 + coefficient2*word2 + ...) from a certain corpus. I know that the larger the (absolute value ...
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45 views

What is the latent class in pLSA

I want to implement Probabilistic Latent Semantic Analysis(pLSA) in Python. I have searched many times but couldn't find a simple tutorial. ...
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31 views

Sliding window EM algorithm for PLSA?

I'm wondering is there a version of sliding window EM? I'm working on an application involving a stream of text (tweets). We are thinking of using 1 day data as training set, and extract the topics ...
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Application of LSA/LSI; Is it common to include the use of an edit distance?

I have been using Latent Semantic Analysis (LSA) or Latent Semantic Indexing (LSI) to identify whether different email addresses belong to the same individual by matching on names used for each email ...
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168 views

Clustering of documents that are very different in number of words

I have a corpus of 643 documents with different sizes and my goal is to cluster them according their topics and label each cluster with semantic name for its main topic. I have tired different ...
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503 views

Computing document similarity in latent semantic analysis

I have a question regarding Latent Semantic Analysis - after performing SVD decomposition of term-document matrix and choosing some number of dimensions, I get the set of new document vectors. Now, ...
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131 views

Probabilistic latent semantic analysis vs bag of words

I am going through probabilistic latent semantic analysis (pLSA) for image classification. I did some image classification experiments with BOW (bag of words) and pLSA but based on my experiments BOW ...
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Probabilistic latent semantic analysis - objective function

In pLSA we are trying to maximize a likelihood function. The likelihood function can be given as: $L = \Pi_i^N \Pi_j^M P(d_i,w_j)^{n(d_i,w_j)}$ Where, M is the number of words and N is the number of ...
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Computing similarity in LSA

I have a question regarding Latent Semantic Analysis (LSA) introduced in http://lsa.colorado.edu/papers/JASIS.lsi.90.pdf‎ . On page 14, schemas for calculating similarities between different types of ...
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LSA vs. PCA (document clustering)

I'm investigation various techniques used in document clustering and I would like to clear some doubts concerning PCA (principal component analysis) and LSA (latent semantic analysis). First thing - ...
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146 views

Is LSA and topic clustering easier in European languages similar to English?

I was watching a talk on latent semantic analysis and the speaker described experience applying LSA and REALLY messy data. He concluded that it demonstrated the difficulty of disambiguation of ...
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237 views

Using LSA for dimension reduction on test data

I am looking to explore using LSA as a dimension reduction technique for some textual data. To be specific I would like to take a matrix of M documents and N n-grams (ie: variables) and then create a ...
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137 views

pLSA using tempered EM

In an article by Hofmann pdf, he proposes: initialize $β$ to one, run until convergence, then rescale $β$ by a factor $η<1$, run again until convergence, and iterate this until changing ...
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Is that overfitting?

Given a document-term matrix $X$, where $$X(d, t) = \textit{occurrences of 't' in 'd'}$$, it's possible to compute it's Truncated Singular Value Decomposition:$$X_k = U_k \Sigma_k V_k^T$$ Then, for a ...
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462 views

A parellel between LSA and pLSA

In the original paper of pLSA the author, Thomas Hoffman, draw a parallel between pLSA and LSA data structures that I would like to discuss with you. Background: Taking inspiration the Information ...
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Derivation of M-step for pLSA

I was looking at section 6 of these notes and trying to understand the derivation of the M-step at the top of page 10. I understood the derivation for the model without background, but I do not ...
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93 views

Initialization in pLSA

I'm using pLSA (Probabilistic Latent Semantic Analysis). I'm trying to estimate the best value for some parameters with a process of k-fold cross-validation. I have noticed that the model fitting is ...
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1k views

How to cluster LDA/LSI topics generated by gensim?

I'm an enthusiastic single developer working on a small start-up idea. I reduced a corpus of mine to an LSA/LDA vector space using gensim. Now I have a bunch of ...
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Fast alternatives to the EM algorithm

Are there any speedy alternatives to the EM algorithm for learning models with latent variables (especially pLSA)? I'm okay with sacrificing precision in favor of speed.
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Is there a sequential version of probabilistic latent semantic analysis?

Does someone know if it exists some way to do online learning with pLSA? The model training is really time consuming, so it is not feasible to rebuild it after every changes in the data.
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Finding similarity between a reference and few working documents

I have to find the similarity between a reference document and a set of documents in a repository . Here is my method : ...
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314 views

Can LSA be used for document similarity?

I have to find the similarity between two documents. The two documents are simple text documents and i have to report a score. I was using cosine similarity initially. But I was told that LSA is a ...
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1k views

When to choose PCA vs. LSA/LSI

Question: Are there any general guidelines with respect to the input data characteristics, that can be used to decide between applying PCA versus LSA/LSI? Brief summary of PCA vs. LSA/LSI: ...
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334 views

pLSA - Probabilistic Latent Semantic Analysis, how to choose topic number?

I am learning about pLSA (Probabilistic Latent Semantic Analysis) right now, in the hopes of being able to apply it to biomolecular annotation prediction. I have a very simple question: How do you ...
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499 views

What is a “tempered EM algorithm”?

In the paper of Probabilistic Latent Semantic Analysis by Hofmann, the author fits the model for document $\times$ word matrix through EM Algorithm in section 3. I was able to follow the derivation ...
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330 views

Derivation of E step in EM algorithm

While im going through the derivation of E step in EM algorithm for pLSA, i came across the following derivation at this page. Could anyone explain me how the following step is derived. $\sum_z q(z) ...
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Deriving mathematical model of pLSA

After knowing how LSA works, I went on continue reading on pLSA but couldn't really make sense of the mathematical formula. This is what I get from wikipedia (other academic papers/tutorial show ...