0
votes
0answers
26 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 ...
0
votes
1answer
70 views

Clustering structured data: Assessing the similarity of documents that appear in tree structure

Usually when performing text document clustering, similarities across documents are assessed based on the lexical content of documents. But, in my problem, I wish to consider both the lexical content ...
0
votes
0answers
41 views

Algorithms for keyphrase clustering

Are there any standard algorithms for keyphrase clustering. There are several algorithms for keyphrase extraction from a corpus. For e.g. this publication reviews some of the popular keyphrase ...
1
vote
1answer
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 ...
2
votes
2answers
242 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?
1
vote
0answers
63 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 ...
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 ...
4
votes
2answers
426 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 ...