The Stack Overflow podcast is back! Listen to an interview with our new CEO.

Questions tagged [information-retrieval]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
32
votes
6answers
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 ...
21
votes
2answers
9k 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 ...
5
votes
1answer
3k views

Difference between Log Entropy Model and TF-IDF Model?

I would like to understand what are the differences/advantages in using TF-IDF or the Log Entropy model for represeting documents and queries in an information retrieval system using diferent weights. ...
8
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 ...
10
votes
1answer
11k views

Mean Average Precision vs Mean Reciprocal Rank

I am trying to understand when it is appropriate to use the MAP and when MRR should be used. I found this presentation that states that MRR is best utilised when the number of relevant results is less ...
8
votes
1answer
459 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 $\log\left(\frac{\text{numDocs}}{...
3
votes
2answers
837 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
470 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
2answers
75 views

Is there a ranking metric based on percentages that favors larger magnitudes?

I have two groups, "in" and "out," and item categories that can be split up among the groups. For example, I can have item category A that is 99% "in" and 1% "out," and item B that is 98% "in" and 2% "...
2
votes
0answers
2k views

Typical range of values for TFIDF

I am working on a text corpus. Each line contains between 10 and 50 words. There are around 25 000 words in the whole text and 1 000 000 lines. I turned this corpus into its tf-idf representation. I ...
0
votes
0answers
11 views

Metric for ranked keyword identification

I am trying to determine which metric(s) to use to evaluate the "coverage" of several lexicons (lists of words) with respect to a ranked list of significant keywords I have extracted from two ...