Name
Abstract | ||
|---|---|---|
The SERF project at Stanford deals with the Entity Resolution (ER) problem, in which records deter- mined to represent the same real-life "entities" (such as people or products) are successively located and combined. The approach we pursue is "generic", in the sense that the specific functions used to match and merge records are viewed as black boxes, which permits efficient, expressive and extensible ER solutions. This paper motivates and introduces the principles of generic ER, and gives an overview of the research directions we have been exploring in the SERF project over the past two years. |
Year | Venue | Keywords |
|---|---|---|
2006 | IEEE Data Eng. Bull. | entity resolution |
Field | DocType | Volume |
Data mining,World Wide Web,Name resolution,Computer science,Black box,Merge (version control),Database | Journal | 29 |
Issue | Citations | PageRank |
2 | 17 | 1.85 |
References | Authors | |
4 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Omar Benjelloun | 1 | 1518 | 75.96 |
| Héctor García-Molina | 2 | 24359 | 5652.13 |
| Hideki Kawai | 3 | 73 | 13.43 |
| Tait Eliott Larson | 4 | 17 | 1.85 |
| David Menestrina | 5 | 518 | 22.23 |
| Qi Su | 6 | 135 | 19.10 |
| Sutthipong Thavisomboon | 7 | 37 | 3.56 |
| Jennifer Widom | 8 | 16150 | 2524.75 |