1. INEX 2009 XML Mining Track James Reed Jonathan McElroy Brian Clevenger

2. Introduction INEX is An initiative looking into use of XML retrieval The clustering task uses Information Retrieval, Data Mining, Machine Learning and XML fields Goal: To measure how well clustering methods work for retrieving collections from large sets of documents. Also to measure performance specifically for XML IR

3. Problem Task: to test the Jardine Hypothesis which states: “documents that cluster together have a similar relevance to a given query.” If (true) {a small fraction of clusters need to be searched, increasing the throughput of an IR system;}

4. Data Wikipedia is the source 60 Gigabytes with about 2.7 million documents in XML format Provide Complete and Subsets of the meta-data

5. Data Files Tags and trees: :... : 14052 0 0 15 1 2 3 -1 4 -1 5 -1 -1 6 7 -1 8 -1 -1 Links:... Entities: :... : Bag-of-Words (BOW...Wow!): –BOW File: :... : –Term Index File: 1472,bracelet 547,depend

6. Solution: A Two Pronged Approach First Prong: –Analyze Links to discover maximum flow communities –Using Ford-Fulkerson Algorithm Second Prong: –Use information from BOW and Entities to develop similarity measures between documents within clusters –Attempt to refine and develop more better clusters