Text Clustering using K-Medoids Algorithm
Hi All!
I'm new to RapidMiner. I have 1000+ online reviews generated from Tripadvisor.com. I want to apply K-Medoids algorithm to cluster those reviews into k cluster. The reason why I chose K-Medoids bcs I want to find the "medoid" for each cluster, which I believe is able to represent the contents of the entire cluster. I already applied some nodes such as:
- Read Excel
- Select Attributes
- Nominal to Text
- Process Documents from Data (Tokenization, Stemming, Stopwords Removal)
- and the Clustering node itself
But I can't seem to find the proporsional cluster. From 1000+ data with k = 2, the ratio of of members of clusters 1 and 2 is 99 : 1.
Please help mee!
Answers
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Hi,
have you tried to use
a) TF-IDF
b) cosine similarity as distance measure
Best,
Martin
1 -
I agree with @mschmitz suggestions. However, there is no guarantee when using any of the k-means family of clustering algorithms that the clusters will be of equal sizes. The algorithm isn't looking directly at the cluster sizes, but rather at intra-cluster similarity vs inter-cluster similarity. You may want to try X-Means which will test a large range of possible k values and suggest the best one based on BIC.
1
Altair Employee