Type Classification of Semi-Structured Documents
Summary: Experimental vector-space classifier for automatic type inference of semi-structured documents; provides explicit typing to support object-oriented techniques. Targets high recall/precision, fast speed, and extensibility, with empirical evaluation of accuracy and performance. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Markus Tresch
- 2. Neal Palmer
- 3. Allen Luniewski
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 393 | From Structured Documents to Novel Query Facilities | 1994 | SIGMOD | 0.00024506032 |
| 2,296 | The Rufus System: Information Organization for Semi-Structured Data | 1993 | VLDB | 9.0814726e-05 |
| 2,572 | Optimizing Queries on Files | 1994 | SIGMOD | 8.5141353e-05 |
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