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3
votes
1answer
2k views

Euclidean Distance b/t unit vectors or cosine similarity where vectors are document vectors

I was reading Similarity Measures and suddenly my whole world was falling apart. I have implemented a search engine using clustering techniques. For clustering, I used k means which uses Euclidean ...
2
votes
2answers
328 views

How do you predict a continuous value from many booleans & a continuous value?

Hello: I am a computer science student working as a research assistant in an undergrad IR lab, feeling spectacularly out of my element. Given an input of a single continuous value and a vector of ...
2
votes
0answers
84 views

Software library for Hidden Markov Modeling of a large text database

Given we have a large database of texts (e.g. product descriptions) and we want to extract multiple types of information (e.g. brand, release date, features, price, etc.) what's a good library to ...
7
votes
2answers
330 views

Understanding and applying sentiment analysis

I was just having been assigned a project of conducting sentiment analysis for some document collections. By Googling, a lot of sentiment-related research has popped up. My questions are: What are ...
3
votes
0answers
316 views

Similarity calculations for arrays

First of all, my apologies if I mess up the terminology. I've been out of math for several years, so I'm certain I'm going to use terms incorrectly. Also, though I concentrated mathematics in college, ...
5
votes
1answer
333 views

Choosing a measure of similarity to quantify similarity between individuals on a set of personality scales

I have a bunch of users. Each user has a number of personality attributes, such as "fitness level" or "eco-consciousness", rated on a scale from 1 to 5. I want to calculate how similar two users are, ...
2
votes
0answers
156 views

How to to calculate the topic distribution of a document

I have a simple (may be stupid) question. I want to calculate Kullback–Leibler divergence on two documents. It requires probability distribution of each document. I do not know how to calculate ...
3
votes
1answer
686 views

Using latent Dirichlet allocation for information retrieval

I am working on understanding various document ranking algorithms like (TF-IDF, LSI, language models, etc) by actually implementing them. I want to understand LDA and using various resources to ...
4
votes
2answers
433 views

How to compute term frequency and find clusters in a dataset composed of strings?

I am currently looking for some Information Retrieval techniques. I have a SQL database table containing strings. It has 1000 records, each being a random sentence I picked from random web sites. I ...
4
votes
2answers
1k views

Comparing cosine similarities for tf-idf vectors for documents with different length

I'm computing cosine similarities between 2 vectors. These vectors are information retrieval query and document representations respectively. They have been computed using tf-idf weights. Since my ...
2
votes
2answers
581 views

KL divergence calculation

I am wondering that how one can calculate KL-divergence on two probability distributions. For example, if we have ...
7
votes
2answers
1k views

Can one use Cohen's Kappa for two judgements only?

I am using Cohen's Kappa to calculate the inter-agreement between two judges. It is calculated as: $ \frac{P(A) - P(E)}{1 - P(E)} $ where $P(A)$ is the proportion of agreement and $P(E)$ the ...
13
votes
1answer
3k views

Measuring Document Similarity

To cluster (text) documents you need a way of measuring similarity between pairs of documents. Two alternatives are: Compare documents as term vectors using Cosine Similarity - and TF/IDF as the ...
24
votes
7answers
1k views

Statistical classification of text

I'm a programmer without statistical background, and I'm currently looking at different classification methods for a large number of different documents that I want to classify into pre-defined ...