Raghav Kaushik

Computer Networks and Communications · 2000–2010

A researcher in the Science corpus: 6 papers; trusts 15 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Computer Networks and Communications — 10 citations into it
• Artificial Intelligence — 9 citations into it; #9,933 of 35,345 by trust here, #19,873 by citations
• Signal Processing — 9 citations into it; #4,044 of 7,572 by trust here, #5,340 by citations
• Management Science and Operations Research — 8 citations into it; #2,462 of 11,946 by trust here, #5,548 by citations
• Information Systems — 7 citations into it; #2,095 of 8,771 by trust here, #4,682 by citations
• Information Retrieval & Search — 5 citations into it; #301 of 1,022 by trust here, #663 by citations

Whom Raghav Kaushik trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Surajit Chaudhuri
2. Sunita Sarawagi
3. Brian F. Cooper
4. Venkatesh Ganti
5. Peter Buneman
6. Quanzhong Li
7. Alok Kirpal
8. Aristides Gionis
9. Rakesh Agrawal
10. Nick Koudas

Who trusts Raghav Kaushik overall

1. Anshumali Shrivastava
2. Ping Li
3. Jiaheng Lu
4. Xifeng Yan
5. Arvind Arasu
6. Parag Agrawal
7. Chuan Xiao
8. Rares Vernica
9. Philip S. Yu
10. Yiming Lu

Papers from Raghav Kaushik's perspective

Ordered by how strongly the researchers Raghav Kaushik trusts endorse each paper. Same corpus, a different order for every researcher.

1. On the resemblance and containment of documents
2. Robust and efficient fuzzy match for online data cleaning (ACM SIGMOD Conference)
3. Eliminating Fuzzy Duplicates in Data Warehouses (Very Large Data Bases Conference)
4. Efficient set joins on similarity predicates (ACM SIGMOD Conference)
5. Interactive deduplication using active learning (Knowledge Discovery and Data Mining)
6. Adaptive algorithms for set containment joins
7. A Primitive Operator for Similarity Joins in Data Cleaning
8. Record linkage: similarity measures and algorithms
9. Mining association rules between sets of items in large databases
10. Approximate String Joins in a Database (Almost) for Free (Very Large Data Bases Conference)

Their papers

• On indexing error-tolerant set containment (2010) — 59 citations
• A Primitive Operator for Similarity Joins in Data Cleaning (2006) — 631 citations
• Efficient exact set-similarity joins (2006) — 498 citations
• Exploiting local similarity for indexing paths in graph-structured data (2002) — 296 citations
• Covering indexes for branching path queries (2002) — 356 citations
• Set Containment Joins: The Good, The Bad and The Ugly (2000) — 91 citations