Title
Extending the power of datalog recursion
Abstract
Supporting aggregates in recursive logic rules represents a very important problem for Datalog. To solve this problem, we propose a simple extension, called DatalogFS (Datalog extended with frequency support goals), that supports queries and reasoning about the number of distinct variable assignments satisfying given goals, or conjunctions of goals, in rules. This monotonic extension greatly enhances the power of Datalog, while preserving (i) its declarative semantics and (ii) its amenability to efficient implementation via differential fixpoint and other optimization techniques presented in the paper. Thus, DatalogFS enables the efficient formulation of queries that could not be expressed efficiently or could not be expressed at all in Datalog with stratified negation and aggregates. In fact, using a generalized notion of multiplicity called frequency, we show that diffusion models and page rank computations can be easily expressed and efficiently implemented using DatalogFS .
Year
DOI
Venue
2013
10.1007/s00778-012-0299-1
VLDB J.
Keywords
Field
DocType
Query languages,Logic programming,Graph algorithms
Monotonic function,Simple extension,Query language,Computer science,Theoretical computer science,Fixed point,Logic programming,Rule of inference,Datalog,Database,Recursion
Journal
Volume
Issue
ISSN
22
4
1066-8888
Citations 
PageRank 
References 
19
0.69
27
Authors
3
Name
Order
Citations
PageRank
Mirjana Mazuran1509.26
Edoardo Serra26610.23
Carlo Zaniolo343051447.58