Clustering versus faceted categories for information exploration

By Marti A. Hearst. Communications of the ACM, 2006

445 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/9e526a04171ea6efe60a1a36d54d8f553ebad6c5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Qiaozhu Mei
2. Chengxiang Zhai
3. B. Liu
4. Hang Su
5. Giovanni Romano
6. Claudio Carpineto
7. Xu Ling
8. Matthew Wondra

In Information Systems

1. Qiaozhu Mei
2. Chengxiang Zhai
3. Hang Su
4. Giovanni Romano
5. Claudio Carpineto
6. Xu Ling
7. Matthew Wondra
8. Ryen W. White

Citations in the corpus

• Exploratory Search: Beyond the Query-Response Paradigm (2009, background): “The clustering procedure is fully automated, can be easily applied to any document collection, and can reveal interesting and unexpected trends in a group of documents (Hearst, 2006).”
• A survey of Web clustering engines (2009, background): “These kinds of errors are quite typical for clustering output, whereas users prefer coherent and relatively complete category systems [Hearst 2006].”
• Topic sentiment mixture: modeling facets and opinions in weblogs (2007, background): “On the other hand, researchers also use facets to categorize the latent topics in search results [8].”