Query-based sampling of text databases

By Jamie Callan, Margaret E. Connell. ACM Trans. Inf. Syst., 2001

416 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/99e3ad377c07659633d1cdd53077dc239ecf7baa

How researchers see this paper

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

In Computer Networks and Communications

1. Jayant Madhavan
2. David Ko
3. Alon Y. Halevy
4. Fabrizio Silvestri
5. Pavel Shvaiko
6. Jérôme Euzenat
7. Xin Luna Dong
8. Phokion G. Kolaitis

In Information Systems

1. Jayant Madhavan
2. Fabrizio Silvestri
3. Alon Y. Halevy
4. Jérôme Euzenat

In Signal Processing

1. Jayant Madhavan
2. Alon Y. Halevy
3. David Ko
4. Fabrizio Silvestri
5. Phokion G. Kolaitis
6. Michael Schmidt
7. Robert Stevens
8. Rachel Pottinger

Citations in the corpus

• Mining Query Logs: Turning Search Usage Data into Knowledge (2010, background): “non-web, Distributed IR systems has been proposed in the past [55, 58, 195, 196, 197].”
• Google's Deep Web crawl (2008, methodology): “In order to create keyword summaries, a probing approach was proposed in [4] where, starting from an initial set of keywords, more are extracted by repeatedly querying the text database with a known set of keywords.”
• DISTRIBUTED INFORMATION RETRIEVAL (2002, neutral): “Several diierent approaches to query term selection were tested, including selecting terms from the learned language model using frequency criteria, and selecting terms that appear important in other, presumably similar language models (Callan et al., 1999aa Callan and Connell, 1999).”