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29
votes
7answers
2k 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 ...
17
votes
2answers
6k 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 ...
7
votes
2answers
468 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 ...
7
votes
2answers
2k 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 ...
6
votes
1answer
168 views

Why does Lucene IDF have a seemingly additional +1?

From the Lucene docs $\text{IDF} = 1 + \log\left(\frac{\text{numDocs}}{\text{docFreq}+1}\right)$ In other references (i.e. wikipedia), IDF is typically calculated as ...
5
votes
1answer
884 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 ...
5
votes
1answer
172 views

In inverse theory, how do I transform the averaging kernel matrix to a new grid?

Rodgers and Connor (2003) describe how measurements by remote sounders can be properly compared, taking into account differences in averaging kernels and error covariances. They make the assumption ...
5
votes
1answer
518 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, ...
4
votes
3answers
676 views

Summary statistics of the precision-recall curve

From what I understand, one can use the AUC of the ROC curve as a summary statistic of the full curve. Q1. Are there any similar summary statistics that one can use on a single precision-recall ...
4
votes
2answers
3k 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 ...
4
votes
2answers
637 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
1answer
159 views

What is the standard procedure for evaluating a user-based CF algorithm with a dataset offline?

I have read some papers and other materials about the evaluation of recommender systems (RS). Most of them discuss the various properties of RS (e.g. accuracy, diversity, etc.), and metrics for ...
3
votes
2answers
1k 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 ...
3
votes
1answer
3k 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 ...
3
votes
1answer
874 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 ...
3
votes
1answer
288 views

Difference between Weighted Average Entropy and Adjusted Mutual Information (for evaluating Clustering)

I was advised by my team leader to use this weighted average entropy to evaluating the performance of my dbscan clustering algorithm, and its mathematical formulation is: Scikit provides what many ...
3
votes
2answers
393 views

Dataset and papers for baseline [closed]

I'm doing a project about Topic Detection and Tracking in text. I need to perform a baseline so I can compare existing results with mine. I read some papers where they use datasets that are not so ...
3
votes
2answers
184 views

Vector Space Model for Online News Clustering

I am trying to automatically cluster news articles based on their content. I need this algorithm to be online and simply group news articles related to the same story as they arrive. The common ...
3
votes
0answers
37 views

The Effect of Stopword Filtering prior to Word Embedding Training

Recently I have played with the pretrained GLOVE word embedding model for Twitter http://nlp.stanford.edu/projects/glove/ I notice that common stopwords are existing in the model. That is, there is ...
3
votes
0answers
52 views

Heuristics streaming data matching

I have an index composed by thousands of documents. Slightly modified copies of those documents are sent to my application in small chunks, and I need to check, from those chunks, which document has ...
3
votes
0answers
296 views

Learning to Rank: query-dependent vs. query-independent features

I've been doing some reading about learning to rank - specifically lambdaMART - and one thing I am confused about is the role of features. When training a model, should one only use query-dependent ...
3
votes
0answers
347 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, ...
2
votes
2answers
846 views

KL divergence calculation

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

Explaining the steps of a visualization tool

this is my first post on CrossValidated. I've done, for academic purpose, a web tool doing this process: web scraping from various sites pre-process the responses (cleaning, error and redundance ...
2
votes
2answers
106 views

Weighting words based on position in text

I'm currently working on semantic analysis and had a question about text organization and structure. Are there any algorithms, or statistical / machine-learning models that weight the importance of a ...
2
votes
1answer
3k views

“Mean average precision” (MAP) evaluation statistic - understanding good/bad/chance values

I'm evaluating a multilabel classifier. I'm familiar with the Area Under the Curve statistic, which has some nice properties (e.g. chance level is always 50%). But for some applications, it's more ...
2
votes
1answer
518 views

What is the difference between accuracy and agreement?

According to Manning et al. (p. 155) accuracy is the sum of the diagonal in the confusion matrix divided by the sum of all items. On the other hand, following Artstein and Poesio (p . 558) precisely ...
2
votes
2answers
493 views

Other documents features than tf-idf for clustering?

What are other feature representations for documents that are used for clustering textual documents? The only representation I'm aware of is tf-idf. Are there other ones?
2
votes
0answers
54 views

Is there an algorithm for determining scoring function (Utility function) in ranking instances?

So while going through the topic of Preference learning, I came to know about "instance ranking". Since the problem which I'm working on requires me to rank the instances (data point), is there any ...
2
votes
0answers
101 views

Search in a graph of medical records

I have a hierarchical order of a disease list. Just for example: Respiratory system disease 1.1. Asphyxia neonatorum 1.2. Croup 1.3. Lower respiratory tract disease 1.4. Bronchial disease ...
2
votes
0answers
34 views

Evaluation of a semi-supervised ranking model

I learned ranking model with graph-based semi-supervised approach, while labeled (just positive) and unlabeled (positive and negative) data is both used in training. With the model, all of the data ...
2
votes
0answers
556 views

Why are ERR (Expected Reciprocal Ranking) scores not normalized?

It seems to me that normalized ERR (Expected Reciprocal Ranking) scores (ERR scores of your ranking algorithm divided by ERR score calculated for the ground truth ranking) are more useful than the ...
2
votes
0answers
101 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 ...
2
votes
0answers
186 views

How to to calculate the topic distribution of a document

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

Create a matrix of tf-idf values from documents

I have a set of documents like: D1 = "The sky is blue." D2 = "The sun is bright." D3 = "The sun in the sky is bright." and a ...
1
vote
1answer
101 views

Average precision when not all the relevant documents are found

I can't find on the Internet a proper source that explains this. I have built a search engine that for a particular query retrieves 5 relevant document out of the 10 relevant documents. When I ...
1
vote
2answers
666 views

What is the best algorithm to find similar text documents?

I have many text documents and I would like to find similar documents to each document within my data set. Is Latent Dirichlet Allocation (LDA) the best way to do that, or are there other algorithms ...
1
vote
2answers
372 views

Most important journals in data mining/ML, NLP and IR?

Can you please provide with me with the names of the most important journals in data mining, machine learning, natural language processing and information retrieval?
1
vote
2answers
585 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 ...
1
vote
0answers
31 views

Where did sublinear tf-idf originate?

I have often come across this weighting scheme for tf-idf (term frequency - inverse document frequency) in text mining. I am wondering where it came from (for citations). I've searched very ...
1
vote
0answers
12 views

How to decide what is the relevant group in a precision and recall computation?

One of the most famous measurements for an information retrieval system is to compute its precision and recall. For both cases, we need to compute the number of total relevant documents and compare it ...
1
vote
0answers
27 views

Is this ordering of examples redundant in Rank SVM?

I was studying RankSVM[1] and I was observing the ranking pairs listed in the example here. Formulation can be seen on page 4 of this paper. One of the ordering ...
1
vote
0answers
20 views

Normalised score for BM25

BM25 provides a function that assigns a score that is a function of a query and a document. The score is computed for each document in the collection and can be used to rank documents, but this score ...
1
vote
0answers
17 views

Information retrieval performance measures for unknown test collection?

I am evaluating a web search relevance feedback algorithm. The algorithm uses Bing API as source for its result sets. To evaluate the algorithm I will be conducting a user study. In the end I will ...
1
vote
1answer
48 views

How do I perform an IDF calculation?

How do I perform an IDF calculation? I am uncertain as to whether IDF should be calculated in per-class level or for the entire document set (that contains multiple classes).
1
vote
1answer
37 views

“Exotic” text representations methods?

I'm looking to the different methods of representing a text into a machine-readable format. However, until now, I only found "Bag of Words" approachs with a lot of variations (boolean BoW, weighted ...
1
vote
0answers
93 views

Mutual Information for clustering

I'm working on a document clustering application and decided to use Normalized Mutual Information as one of the measures of effectivenes. But I don't really understand how to implement this in that ...
1
vote
0answers
69 views

MAE/MSE with or without square root

I read some papers about recommender systems and information retrieval, where Mean Absolut Error and Mean Squared Error are mentioned. But I've found some differences between the formal definition of ...
1
vote
0answers
118 views

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 ...
1
vote
0answers
162 views

Using sentiment lexicons or all words processing for sentiment analysis?

I am learning sentiment analysis to apply it to twitter real time data to predict user's mood. I ponder about using which alternative way to do that data mining job. Use all words to process and ...