# HG changeset patch
# User Alpar Juttner <alpar@cs.elte.hu>
# Date 1480542335 -3600
# Node ID bdf97dafabfb447184dd93b2a6ed7ce4689b097d
# Parent  b098561f70fee728050d396e0e70dcc572b1d75f
New title and abstract

diff -r b098561f70fe -r bdf97dafabfb damecco.tex
--- a/damecco.tex	Wed Nov 30 21:51:10 2016 +0100
+++ b/damecco.tex	Wed Nov 30 22:45:35 2016 +0100
@@ -103,60 +103,46 @@
 %% \address{Address\fnref{label3}}
 %% \fntext[label3]{}
 
-\title{Improved Algorithms for Matching Biological Graphs}
+\title{VF2++ --- An Improved Subgraph Isomorphism Algorithm}
 
 %% use optional labels to link authors explicitly to addresses:
 %% \author[label1,label2]{}
 %% \address[label1]{}
 %% \address[label2]{}
 
-\author{Alp{\'a}r J{\"u}ttner and P{\'e}ter Madarasi}
-
-\address{Dept of Operations Research, ELTE}
+\author[egres,elte]{Alp{\'a}r J{\"u}ttner}
+\ead{alpar@cs.elte.hu}
+\author[elte]{P{\'e}ter Madarasi}
+\ead{madarasip@caesar.elte.hu}
+\address[egres]{MTA-ELTE Egerv{\'a}ry Research Group, Budapest, Hungary.}
+\address[elte]{Department of Operations Research, E{\"o}tv{\"o}s Lor{\'a}nd University, Budapest, Hungary.}
 
 \begin{abstract}
-Subgraph isomorphism is a well-known NP-Complete problem, while its
-special case, the graph isomorphism problem is one of the few problems
-in NP neither known to be in P nor NP-Complete. Their appearance in
-many fields of application such as pattern analysis, computer vision
-questions and the analysis of chemical and biological systems has
-fostered the design of various algorithms for handling special graph
-structures.
 
-This paper presents VF2++, a new algorithm based on the original VF2,
-which runs significantly faster on most test cases and performs
-especially well on special graph classes stemming from biological
-questions. VF2++ handles graphs of thousands of nodes in practically
-near linear time including preprocessing. Not only is it an improved
-version of VF2, but in fact, it is by far the fastest existing
-algorithm especially on biological graphs.
+  This paper presents a largely improved version of the VF2 algorithm
+  for the \emph{Subgraph Isomorphism Problem}. The improvements are
+  twofold. Firstly, it is based on a new approach for determining the
+  matching order of the nodes, and secondly, more efficient -
+  nevertheless easier to compute - cutting rules significantly
+  reducing the search space are applied.
 
-The reason for VF2++' superiority over VF2 is twofold. Firstly, taking
-into account the structure and the node labeling of the graph, VF2++
-determines a state order in which most of the unfruitful branches of
-the search space can be pruned immediately. Secondly, introducing more
-efficient - nevertheless still easier to compute - cutting rules
-reduces the chance of going astray even further.
+  In addition to the usual subgraph isomorphism, the paper also
+  presents specialized versions for the \emph{Induced Subgraph
+    Isomorphism} and for the \emph{Graph Isomorphism Problems}.
 
-In addition to the usual subgraph isomorphism, specialized versions
-for induced subgraph isomorphism and for graph isomorphism are
-presented. VF2++ has gained a runtime improvement of one order of
-magnitude respecting induced subgraph isomorphism and a better
-asymptotical behaviour in the case of graph isomorphism problem.
-
-After having provided the description of VF2++, in order to evaluate
-its effectiveness, an extensive comparison to the contemporary other
-algorithms is shown, using a wide range of inputs, including both real
-life biological and chemical datasets and standard randomly generated
-graph series.
-
-The work was motivated and sponsored by QuantumBio Inc., and all the
-developed algorithms are available as the part of the open source
-LEMON graph and network optimization library
-(http://lemon.cs.elte.hu).
+  Finally, an extensive experimental evaluation is provided using a
+  wide range of inputs, including both real life biological and
+  chemical datasets and standard randomly generated graph series. The
+  results show major and consistent running time improvements over the
+  other known methods.
+ 
+  The C++ implementations of the algorithms are available open source as
+  the part of the LEMON graph and network optimization library.
+  
 \end{abstract}
 
 \begin{keyword}
+  Computational Biology, Subgraph Isomorphism Problem
 %% keywords here, in the form: keyword \sep keyword
 
 %% PACS codes here, in the form: \PACS code \sep code