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About Clustering Web Search Results: Iwona Białynicka-Birula
The document discusses clustering web search results to organize similar pages into groups to help users find relevant information more easily. It covers what clustering is, why it is useful for web search, example algorithms like K-means and hierarchical clustering, and systems that have implemented search result clustering like Scatter/Gather, Grouper and Carrot2. The key challenges are clustering large and changing web datasets efficiently while grouping pages to aid the user's search goals.
Detailed Information
| Author: | ['Brinda BM'] |
|---|---|
| Publication Year: | 2015 |
| Pages: | 25 |
| Language: | English |
| Format: | |
| Price: | FREE |
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