Tree clustering for constraint networks (research note)
Artificial Intelligence
Introduction to algorithms
Computationally Manageable Combinational Auctions
Management Science
On the consecutive ones property
Discrete Applied Mathematics - Special volume on computational molecular biology DAM-CMB series volume 2
On the Desirability of Acyclic Database Schemes
Journal of the ACM (JACM)
Degrees of acyclicity for hypergraphs and relational database schemes
Journal of the ACM (JACM)
Syntactic Characterization of Tree Database Schemas
Journal of the ACM (JACM)
Towards a universal test suite for combinatorial auction algorithms
Proceedings of the 2nd ACM conference on Electronic commerce
Synthesizing constraint expressions
Communications of the ACM
A simple test for the consecutive ones property
Journal of Algorithms
BOB: improved winner determination in combinatorial auctions and generalizations
Artificial Intelligence
Constraint Processing
Combinatorial Auctions
On the complexity of combinatorial auctions: structured item graphs and hypertree decomposition
Proceedings of the 8th ACM conference on Electronic commerce
Combinatorial auctions with structured item graphs
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Why AC-3 is almost always better than AC-4 for establishing arc consistency in CSPs
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Consistency and set intersection
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Journal of Computer and System Sciences
Feedback vertex sets on restricted bipartite graphs
Theoretical Computer Science
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A collection of sets may have some interesting properties which help identify efficient algorithms for constraint satisfaction problems and combinatorial auction problems. One of the properties is tree convexity. A collection S of sets is tree convex if we can find a tree T whose nodes are the union of the sets of S and each set of S is the nodes of a subtree of T. This concept extends that of row convex sets each of which is an interval over a total ordering of the elements of the union of these sets. An interesting problem is to find efficient algorithms to test whether a collection of sets is tree convex. It is not known before if there exists a linear time algorithm for this test. In this paper, we review the materials that are the key to a linear algorithm: hypergraphs, a characterization of tree convex sets and the acyclic hypergraph test algorithm. Some typos in the original paper of the acyclicity test are corrected here. Some experiments show that the linear algorithm is significantly faster than a well-known existing algorithm. © 2012 Wiley Periodicals, Inc.