Object Matching for Information Integration: A Profiler-Based Approach

  title={Object Matching for Information Integration: A Profiler-Based Approach},
  author={AnHai Doan and Ying Lu and Yoonkyong Lee and Jiawei Han},
Object matching is a fundamental problem that arises in numerous information integration scenarios. Virtually all existing solutions to this problem have assumed that the objects to be matched share the same set of attributes, and that they can be matched by comparing the similarities of the attributes. We consider the more general problem where the objects can also have disjoint attributes, such as matching tuples that come from relational tables with schemas (age,name) and (name,salary… CONTINUE READING
Highly Cited
This paper has 67 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 44 extracted citations

Scalable mining and link analysis across multiple database relations

SIGKDD Explorations • 2008
View 4 Excerpts
Highly Influenced

Searching Web 2.0 Data Through Entity-Based Aggregation

Trans. Computational Collective Intelligence • 2016
View 1 Excerpt

Semantical mapping of attribute values for data integration

2014 IEEE Conference on Norbert Wiener in the 21st Century (21CW) • 2014
View 2 Excerpts

68 Citations

Citations per Year
Semantic Scholar estimates that this publication has 68 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 24 references

Similar Papers

Loading similar papers…