We tackle the containment problem for conjunctive queries with negation, which takes two queries q1 and q2 as input and asks if q1 is contained in q2. A general approach for solving this problem consists of considering all completions of q1 (intuitively these completions represent all canonical databases that satisfy q1) and checking if each completion yields the same answer on q2. Since the to...

Contention tree algorithm is initially invented as a solution to improve the stable throughput problem of Slotted ALOHA in multiple access schemes. Even though the throughput is stabilized in tree algorithms, the delay of requests may grow to infinity with respect to the arrival rate of the system. Delay depends heavily on the exploration of the tree structure, i.e., breadth search, or depth se...

The algorithm selection problem asks to select the best algorithm for a given problem. In the companion paper Everitt and Hutter (2015b), expected runtime was approximated as a function of search depth and probabilistic goal distribution for tree search versions of breadth-first search (BFS) and depth-first search (DFS). Here we provide an analogous analysis of BFS and DFS graph search, derivin...

Abstract Many systems have been developed for creating syntactically annotated corpora. However, they mainly focus on interface usability and hardly pay attention to knowledge sharing among annotators in the task. In order to incorporate the functionality of knowledge sharing, we emphasized the importance of normalizing the annotation process. As a first step toward knowledge sharing, this pape...

The association rule discovery problem consists in identifying frequent itemsets in a database and, then, forming conditional implication rules among them. The algorithmically most difficult part of this task is finding all frequent sets. There exists a wealth of algorithms both for the problem as such and for variations, particular cases, and generalizations. Except for some recent, fully diff...

In this work we propose techniques for efficient reachability analysis of the state space (e.g., detection of bad states) using a combination of partial order and symmetry based reductions in a distributed setting. The proposed techniques are focused towards explicit state space enumeration based model-checkers like SPIN. We consider variants for both depth-first as well as breadth-first based ...

Mining frequent itemsets is one of the main problems in data mining. Much effort went into developing efficient and scalable algorithms for this problem. When the support threshold is set too low, however, or the data is highly correlated, the number of frequent itemsets can become too large, independently of the algorithm used. Therefore, it is often more interesting to mine a reduced collecti...

Rippling is a form of rewriting that guides search by only performing steps that reduce the syntactic differences between formulae. Termination is normally ensured by a measure that is decreases with each rewrite step. Because of this restriction, rippling will fail to prove theorems about, for example, mutual recursion as steps that temporarily increase the differences are necessary. Best-firs...

In recent years several frequent subgraph miners were proposed. The authors of these new algorithms typically compared the runtimes of their implementations with those of previous implementations to confirm the efficiency of their methods. To get a better perspective on the mutual benefits of the algorithms, Wörlein et al. [9] performed an experimental evaluation of re-implementations of severa...

Strategies are proposed for combining different kinds of constraints in declarative grammars with a detachable layer of control information. The added control information is the basis for parametrized dynamically controlled linguistic deduction, a form of linguistic processing that permits the implementation of plausible linguistic performance models without giving up the declarative formulatio...