2,768 research outputs found
Efficient Multistriding of Large Non-deterministic Finite State Automata for Deep Packet Inspection
Multistride automata speed up input matching because each multistriding transformation halves the size of the input string, leading to a potential 2x speedup. However, up to now little effort has been spent in optimizing the building process of multistride automata, with the result that current algorithms cannot be applied to real-life, large automata such as the ones used in commercial IDSs, because the time and the memory space needed to create the new automaton quickly becomes unfeasible. In this paper, new algorithms for efficient building of multistride NFAs for packet inspection are presented, explaining how these new techniques can outperform the previous algorithms in terms of required time and memory usag
DESQ: Frequent Sequence Mining with Subsequence Constraints
Frequent sequence mining methods often make use of constraints to control
which subsequences should be mined. A variety of such subsequence constraints
has been studied in the literature, including length, gap, span,
regular-expression, and hierarchy constraints. In this paper, we show that many
subsequence constraints---including and beyond those considered in the
literature---can be unified in a single framework. A unified treatment allows
researchers to study jointly many types of subsequence constraints (instead of
each one individually) and helps to improve usability of pattern mining systems
for practitioners. In more detail, we propose a set of simple and intuitive
"pattern expressions" to describe subsequence constraints and explore
algorithms for efficiently mining frequent subsequences under such general
constraints. Our algorithms translate pattern expressions to compressed finite
state transducers, which we use as computational model, and simulate these
transducers in a way suitable for frequent sequence mining. Our experimental
study on real-world datasets indicates that our algorithms---although more
general---are competitive to existing state-of-the-art algorithms.Comment: Long version of the paper accepted at the IEEE ICDM 2016 conferenc
Improved Approximate String Matching and Regular Expression Matching on Ziv-Lempel Compressed Texts
We study the approximate string matching and regular expression matching
problem for the case when the text to be searched is compressed with the
Ziv-Lempel adaptive dictionary compression schemes. We present a time-space
trade-off that leads to algorithms improving the previously known complexities
for both problems. In particular, we significantly improve the space bounds,
which in practical applications are likely to be a bottleneck
Fast and Tiny Structural Self-Indexes for XML
XML document markup is highly repetitive and therefore well compressible
using dictionary-based methods such as DAGs or grammars. In the context of
selectivity estimation, grammar-compressed trees were used before as synopsis
for structural XPath queries. Here a fully-fledged index over such grammars is
presented. The index allows to execute arbitrary tree algorithms with a
slow-down that is comparable to the space improvement. More interestingly,
certain algorithms execute much faster over the index (because no decompression
occurs). E.g., for structural XPath count queries, evaluating over the index is
faster than previous XPath implementations, often by two orders of magnitude.
The index also allows to serialize XML results (including texts) faster than
previous systems, by a factor of ca. 2-3. This is due to efficient copy
handling of grammar repetitions, and because materialization is totally
avoided. In order to compare with twig join implementations, we implemented a
materializer which writes out pre-order numbers of result nodes, and show its
competitiveness.Comment: 13 page
Path Queries on Compressed XML
Central to any XML query language is a path language such as XPath which operates on the tree structure of the XML document. We demonstrate in this paper that the tree structure can be e#ectively compressed and manipulated using techniques derived from symbolic model checking . Specifically, we show first that succinct representations of document tree structures based on sharing subtrees are highly e#ective. Second, we show that compressed structures can be queried directly and e#ciently through a process of manipulating selections of nodes and partial decompression
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