H
Hector Garcia-Molina
Researcher at Stanford University
Publications - 574
Citations - 64387
Hector Garcia-Molina is an academic researcher from Stanford University. The author has contributed to research in topics: Web page & Query language. The author has an hindex of 127, co-authored 574 publications receiving 63390 citations. Previous affiliations of Hector Garcia-Molina include Princeton University & Xerox.
Papers
More filters
Proceedings ArticleDOI
The Eigentrust algorithm for reputation management in P2P networks
TL;DR: An algorithm to decrease the number of downloads of inauthentic files in a peer-to-peer file-sharing network that assigns each peer a unique global trust value, based on the peer's history of uploads is described.
Proceedings ArticleDOI
Similarity flooding: a versatile graph matching algorithm and its application to schema matching
TL;DR: This paper presents a matching algorithm based on a fixpoint computation that is usable across different scenarios and conducts a user study, in which the accuracy metric was used to estimate the labor savings that the users could obtain by utilizing the algorithm to obtain an initial matching.
Book
Database Systems: The Complete Book
TL;DR: This introduction to database systems offers a readable comprehensive approach with engaging, real-world examples, and users will learn how to successfully plan a database application before building it.
Book ChapterDOI
Combating web spam with trustrank
TL;DR: This paper proposes techniques to semi-automatically separate reputable, good pages from spam, and shows that they can effectively filter out spam from a significant fraction of the web, based on a good seed set of less than 200 sites.
The TSIMMIS project: Integration of heterogeneous information sources
Sudarshan S. Chawathe,Hector Garcia-Molina,Joachim Hammer,Kelly Ireland,Yannis Papakonstantinou,Jeffrey D. Ullman,Jennifer Widom +6 more
TL;DR: The Tsimmis project as mentioned in this paper is a joint project between Stanford and IBM Almaden Research Center to develop tools that facilitate the rapid integration of heterogeneous information sources that may include both structured and unstructured data.