19,185 research outputs found
DiffNodesets: An Efficient Structure for Fast Mining Frequent Itemsets
Mining frequent itemsets is an essential problem in data mining and plays an
important role in many data mining applications. In recent years, some itemset
representations based on node sets have been proposed, which have shown to be
very efficient for mining frequent itemsets. In this paper, we propose
DiffNodeset, a novel and more efficient itemset representation, for mining
frequent itemsets. Based on the DiffNodeset structure, we present an efficient
algorithm, named dFIN, to mining frequent itemsets. To achieve high efficiency,
dFIN finds frequent itemsets using a set-enumeration tree with a hybrid search
strategy and directly enumerates frequent itemsets without candidate generation
under some case. For evaluating the performance of dFIN, we have conduct
extensive experiments to compare it against with existing leading algorithms on
a variety of real and synthetic datasets. The experimental results show that
dFIN is significantly faster than these leading algorithms.Comment: 22 pages, 13 figure
Automatically Leveraging MapReduce Frameworks for Data-Intensive Applications
MapReduce is a popular programming paradigm for developing large-scale,
data-intensive computation. Many frameworks that implement this paradigm have
recently been developed. To leverage these frameworks, however, developers must
become familiar with their APIs and rewrite existing code. Casper is a new tool
that automatically translates sequential Java programs into the MapReduce
paradigm. Casper identifies potential code fragments to rewrite and translates
them in two steps: (1) Casper uses program synthesis to search for a program
summary (i.e., a functional specification) of each code fragment. The summary
is expressed using a high-level intermediate language resembling the MapReduce
paradigm and verified to be semantically equivalent to the original using a
theorem prover. (2) Casper generates executable code from the summary, using
either the Hadoop, Spark, or Flink API. We evaluated Casper by automatically
converting real-world, sequential Java benchmarks to MapReduce. The resulting
benchmarks perform up to 48.2x faster compared to the original.Comment: 12 pages, additional 4 pages of references and appendi
SecSip: A Stateful Firewall for SIP-based Networks
SIP-based networks are becoming the de-facto standard for voice, video and
instant messaging services. Being exposed to many threats while playing an
major role in the operation of essential services, the need for dedicated
security management approaches is rapidly increasing. In this paper we present
an original security management approach based on a specific vulnerability
aware SIP stateful firewall. Through known attack descriptions, we illustrate
the power of the configuration language of the firewall which uses the
capability to specify stateful objects that track data from multiple SIP
elements within their lifetime. We demonstrate through measurements on a real
implementation of the firewall its efficiency and performance
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