<html><head><style type='text/css'>p { margin: 0; }</style></head><body><div style='font-family: times new roman,new york,times,serif; font-size: 12pt; color: #000000'><p class="Titreprincipal" style="text-align: center; margin-bottom: 0.0001pt;"><span lang="EN-US" style="font-size:14.0pt;line-height:115%;mso-ansi-language:EN-US"><b>Call for applicants</b></span></p><p class="Titreprincipal" style="text-align: center; margin-bottom: 0.0001pt;"><span lang="EN-US" style="font-size:14.0pt;line-height:115%;mso-ansi-language:EN-US"><br></span></p><p class="Titreprincipal" style="text-align: center; margin-bottom: 0.0001pt;"><span lang="EN-US" style="font-size:14.0pt;line-height:115%;mso-ansi-language:EN-US">PhD
Topic: <o:p></o:p></span></p>
<p class="MsoSubtitle" style="margin-top:0cm"><div style="text-align: center;"><span style="font-size: 13pt; line-height: 115%;">Setting up and validating new
mining methods for the management </span></div><span lang="EN-US" style="font-size:
13.0pt;line-height:115%;mso-ansi-language:EN-US"><div style="text-align: center;"><span style="font-size: 13pt; line-height: 115%;">of incremental textual data and hybrid dynamic data</span></div><o:p></o:p></span></p>
<p class="Standard" align="center" style="margin-top:12.0pt;margin-right:0cm;
margin-bottom:0cm;margin-left:0cm;margin-bottom:.0001pt;text-align:center"><b><span style="mso-bidi-font-size:12.0pt;
line-height:115%">Manager</span></b><span style="mso-bidi-font-size:12.0pt;
line-height:115%">: Dr. Habil. Jean-Charles Lamirel.</span><o:p></o:p></p>
<p class="Standard" align="center" style="text-align:center"><b><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;
mso-ansi-language:EN-US">Research team</span></b><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;mso-ansi-language:EN-US">: SYNALP-LORIA</span><span lang="EN-US">, </span><b><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;
mso-ansi-language:EN-US">Universiy</span></b><span lang="EN-US" style="mso-bidi-font-size:
12.0pt;line-height:115%;mso-ansi-language:EN-US">: Université de Lorraine</span><span lang="EN-US"><o:p></o:p></span></p>
<h1 style="margin-top:18.0pt;margin-right:0cm;margin-bottom:6.0pt;margin-left:
17.85pt;text-align:justify;text-justify:inter-ideograph;text-indent:-17.85pt;
mso-list:l1 level1 lfo1;tab-stops:35.4pt 64.8pt 107.0pt 172.8pt"><!--[if !supportLists]--><span lang="EN-US" style="font-size:12.0pt;line-height:115%;font-family:"Times New Roman","serif";
mso-ansi-language:EN-US">1.<span style="font-weight: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';"> </span></span><!--[endif]--><span lang="EN-US" style="font-size:12.0pt;line-height:115%;font-family:"Times New Roman","serif";
mso-ansi-language:EN-US">Context<o:p></o:p></span></h1>
<p class="Standard" style="text-align:justify;text-justify:inter-ideograph"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;mso-ansi-language:
EN-US">The literature taking into account the chronological aspect in the flows
of information focuses on the "DataStream" whose main concern is the on-the-fly
management of non-initially stored data, likely to be changing in their nature.
Research on "DataStream" was initiated in 1996 by DARPA through the
TDT project ([5] [6] [28]). The data usually considered are essentially
physical measures or Web use data (connection, browsing, etc.). Applications on
text (bibliographic databases, online journals, data issued from interaction streams
...), or hybrid data, mixing texts and numerical experimental results in a
temporal context, such as bioinformatics data, are still stammering. In
addition, the existing algorithms are designed to handle very large volumes of
data and are not optimum for tasks requiring more precise and accurate analysis
such as, the detection of emerging topics in research or technological survey,
the dynamic monitoring of the interaction with an end-user. In a static context,
such tasks also concern the analysis of heterogeneous data including multiple
topics or the study of data issued from complex processes, like the NLP data.<o:p></o:p></span></p>
<h1 style="margin-top:14.0pt;margin-right:0cm;margin-bottom:6.0pt;margin-left:
17.85pt;text-align:justify;text-justify:inter-ideograph;text-indent:-17.85pt;
mso-list:l1 level1 lfo1;tab-stops:35.4pt 64.8pt 107.0pt 172.8pt"><!--[if !supportLists]--><span lang="EN-US" style="font-size:12.0pt;line-height:115%;font-family:"Times New Roman","serif";
mso-ansi-language:EN-US">2.<span style="font-weight: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';"> </span></span><!--[endif]--><span lang="EN-US" style="font-size:12.0pt;line-height:115%;font-family:"Times New Roman","serif";
mso-ansi-language:EN-US">PhD goal<o:p></o:p></span></h1>
<p class="Standard" style="text-align:justify;text-justify:inter-ideograph"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;mso-ansi-language:
EN-US">The purpose of the PhD will be to explore several different approaches for
accurately mining and analyzing textual data with multiple components of static
or incremental nature. The dynamic or incremental framework will be preferred.<o:p></o:p></span></p><p class="Standard" style="text-align:justify;text-justify:inter-ideograph"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;mso-ansi-language:
EN-US"><br></span></p>
<p class="Standard" style="text-align:justify;text-justify:inter-ideograph"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;mso-ansi-language:
EN-US">A first approach which will have to be studied is the decomposition of
the analysis in time steps. The principle of this approach is to carry out the
static classifications of data groups associated with different time windows,
or time steps. Comparison of static classifications obtained for the different
groups is exploited to isolate changes appearing at each time period. This
approach could draw inspiration from the original principles proposed by the multiview
data analysis paradigm (MVDA) developed by the <b>SYNALP</b> team ([2] [3] [13] [15] [16] [17] [20]), such as intelligent
labeling, unsupervised Bayesian reasoning, online generalization, or unbiased
symbolico-numerical quality measures for classification. It will require to
compare the behavior of different usual static classification methods on
textual data, as well as to analyze the influence of the distances used in
these methods, and to propose new alternatives. The implemented approach will also
have to be compared or merged with alternative approaches, such as those based on
latent Dirichlet allocation processes [23], Independent Component Analysis (ICA)
or KL-divergence [1], or those based on novelty detection neural filters [12].<o:p></o:p></span></p><p class="Standard" style="text-align:justify;text-justify:inter-ideograph"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;mso-ansi-language:
EN-US"><br></span></p>
<p class="Standard" style="text-align:justify;text-justify:inter-ideograph"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;line-height:115%;mso-ansi-language:
EN-US">A second approach will be to develop unsupervised fine-grained
classification methods that should work on dynamic data. This flow-oriented approach
implies that the proposed methods should have the ability to react and to adapt
their results to the appearance of each new data. The implementation of such
approaches may be inspired by the classification methods showing the best
potential for incremental classification, such as the neural methods ([10] [11]
[24] [25] [26] [27]) or the density‑based methods ([4] [6] [7]). Among others
things, it will consist in defining new rules for local learning that replace
the rules of global learning usually employed in static versions of these
methods. It will be possible, in this context, to draw inspiration from the promising
incremental techniques currently experienced in the SYNALP team, such as those
proposed in the IGNGF method [18] [19] [21], or in its recent extensions based
on contrast functions derived from the highly efficient feature maximization
metric [22].<o:p></o:p></span></p>
<h1 style="margin-top:13.0pt;margin-right:0cm;margin-bottom:6.0pt;margin-left:
17.85pt;text-align:justify;text-justify:inter-ideograph;text-indent:-17.85pt;
mso-list:l1 level1 lfo1;tab-stops:35.4pt 64.8pt 107.0pt 172.8pt"><!--[if !supportLists]--><span lang="EN-US" style="font-size:12.0pt;line-height:115%;font-family:"Times New Roman","serif";
mso-ansi-language:EN-US">3.<span style="font-weight: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';"> </span></span><!--[endif]--><span lang="EN-US" style="font-size:12.0pt;line-height:115%;font-family:"Times New Roman","serif";
mso-ansi-language:EN-US">Experimental data<o:p></o:p></span></h1>
<p class="Corpsdetexte21" style="text-align: justify;"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;
line-height:115%;mso-ansi-language:EN-US">The environment of development of the
methods will be the one of a collaborative research project, involving several
regional research teams, namely the Thomson Reuters Innovation platform (TRI). TRI
is a multidisciplinary platform giving access, in a coordinated manner, to a
very wide range of scientific publications, to a world reference collection of
patents, and the world reference Web of Science (WoS) citation network. It
includes powerful preprocessing tools permitting to easily build up
time-stamped test datasets and additional tools for validating the results.<o:p></o:p></span></p><p class="Corpsdetexte21" style="text-align: justify;"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;
line-height:115%;mso-ansi-language:EN-US"><br></span></p>
<p class="Corpsdetexte21" style="text-align: justify;"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;
line-height:115%;mso-ansi-language:EN-US">Once the methodology has been
stabilized, the main focus of study in the upcoming experiments will be the one
of bioinformatics. It will involve to manage in a coordinated way textual data
and numerical data issued from biological experiments on evolutionary
processes. Within this framework, we have partnered with the Taiwanese <b>IIR</b> (Intelligent Information Retrieval)
laboratory, attached to the National Science Council of Taiwan, and with the American
<b>NIEHS</b> (Intelligent Information
Retrieval) laboratory to set up a platform of intelligent gene annotation. The
latter will specifically involve the MVDA model that we developed for the management
of multiple sources, the syntactic‑semantic parsers developed by the <b>IIR</b> laboratory for management of the
textual data involved in the analysis, and numerical data issued from DNA
microarrays that will be normalized by the use of <b>NIEHS </b>laboratory protocols.<o:p></o:p></span></p><p class="Corpsdetexte21"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;
line-height:115%;mso-ansi-language:EN-US"><br></span></p>
<p class="Corpsdetexte21" style="text-align: justify;"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;
line-height:115%;mso-ansi-language:EN-US">Full-scale experiments, like those
already started by the <b>SYNALP</b> team
[9], should also be carried out in parallel way with the proposed methods for
the treatment of static linguistic data and for the one of dynamic interaction
data.<o:p></o:p></span></p><p class="Corpsdetexte21"><span lang="EN-US" style="mso-bidi-font-size:12.0pt;
line-height:115%;mso-ansi-language:EN-US"><br></span></p>
<p class="MsoListParagraph" style="margin-top:0cm;margin-right:0cm;margin-bottom:
8.0pt;margin-left:17.85pt;text-align:justify;text-justify:inter-ideograph;
text-indent:-17.85pt;mso-list:l1 level1 lfo1"><!--[if !supportLists]--><span lang="EN-US">4.<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><b><span lang="EN-US">Programming languages</span></b><span lang="EN-US">: Matlab, Java, C, C++. <o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin-top:0cm;margin-right:0cm;margin-bottom:
8.0pt;margin-left:17.85pt;text-align:justify;text-justify:inter-ideograph;
text-indent:-17.85pt;mso-list:l1 level1 lfo1"><!--[if !supportLists]--><span lang="EN-US">5.<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><b><span lang="EN-US">Funding: </span></b><span lang="EN-US">3 years funding is offered if the challenging
student is selected by the LORIA laboratory PhD board.<o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin-top:0cm;margin-right:0cm;margin-bottom:
8.0pt;margin-left:17.85pt;text-align:justify;text-justify:inter-ideograph;
text-indent:-17.85pt;mso-list:l1 level1 lfo1"><!--[if !supportLists]--><b>6.<span style="font-weight: normal; font-size: 7pt; font-family: 'Times New Roman';"> </span></b><b>Contact: </b>Jean-Charles Lamirel - <b>email</b>: <a href="mailto:lamirel@loria.fr"><span style="color:windowtext;mso-bidi-font-weight:
bold;text-decoration:none;text-underline:none">lamirel@loria.fr</span></a> – <b>gsm</b>: +33824365491<b> <o:p></o:p></b></p>
<p class="MsoListParagraph" style="margin-left:18.0pt;text-align:justify;
text-justify:inter-ideograph;text-indent:-18.0pt;mso-list:l1 level1 lfo1"><!--[if !supportLists]--><span lang="EN-US">7.<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><b><span lang="EN-US">Submission deadline</span></b><span lang="EN-US">: May 28th, 2013.<o:p></o:p></span></p><p class="MsoListParagraph" style="margin-left:18.0pt;text-align:justify;
text-justify:inter-ideograph;text-indent:-18.0pt;mso-list:l1 level1 lfo1"><span lang="EN-US"><br></span></p>
<p class="MsoListParagraph" style="margin-left:18.0pt;text-align:justify;
text-justify:inter-ideograph;text-indent:-18.0pt;mso-list:l1 level1 lfo1"><!--[if !supportLists]--><span lang="EN-US">8.<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><!--[endif]--><b><span lang="EN-US">Documents to be provided for application </span></b><span lang="EN-US">(electronic version)<o:p></o:p></span></p><p class="MsoListParagraph" style="margin-left:18.0pt;text-align:justify;
text-justify:inter-ideograph;text-indent:-18.0pt;mso-list:l1 level1 lfo1"><span lang="EN-US"><br></span></p>
<p class="MsoListParagraph" style="margin: 0cm 0cm 6pt 17.85pt; text-indent: -18pt;"><!--[if !supportLists]--><span lang="EN-US" style="mso-bidi-font-size:12.0pt;font-family:Symbol;mso-fareast-font-family:
Symbol;mso-bidi-font-family:Symbol;mso-ansi-language:EN-US">·<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><span lang="EN-US">A full motivation letter arguing why you choose the topic and
which are you skills for a success story related to that topic.<o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin: 0cm 0cm 6pt 17.85pt; text-indent: -18pt;"><!--[if !supportLists]--><span lang="EN-US" style="mso-bidi-font-size:12.0pt;font-family:Symbol;mso-fareast-font-family:
Symbol;mso-bidi-font-family:Symbol;mso-ansi-language:EN-US">·<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><span lang="EN-US">Recommendation letters from our former teachers
(mandatory) and from your company managers (optional). Three letters would be
nice.<o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin: 0cm 0cm 6pt 17.85pt; text-indent: -18pt;"><!--[if !supportLists]--><span lang="EN-US" style="mso-bidi-font-size:12.0pt;font-family:Symbol;mso-fareast-font-family:
Symbol;mso-bidi-font-family:Symbol;mso-ansi-language:EN-US">·<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><span lang="EN-US">Copy of diplomas and rates with a special focus on our
Bachelor and Master degrees.<o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin: 0cm 0cm 6pt 17.85pt; text-indent: -18pt;"><!--[if !supportLists]--><span lang="EN-US" style="mso-bidi-font-size:12.0pt;font-family:Symbol;mso-fareast-font-family:
Symbol;mso-bidi-font-family:Symbol;mso-ansi-language:EN-US">·<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><span lang="EN-US">Master report if it is in English.<o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin: 0cm 0cm 6pt 17.85pt; text-indent: -18pt;"><!--[if !supportLists]--><span lang="EN-US" style="mso-bidi-font-size:12.0pt;font-family:Symbol;mso-fareast-font-family:
Symbol;mso-bidi-font-family:Symbol;mso-ansi-language:EN-US">·<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><span lang="EN-US">Copy of published papers if they are in English.<o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin: 0cm 0cm 6pt 17.85pt; text-indent: -18pt;"><!--[if !supportLists]--><span lang="EN-US" style="mso-bidi-font-size:12.0pt;font-family:Symbol;mso-fareast-font-family:
Symbol;mso-bidi-font-family:Symbol;mso-ansi-language:EN-US">·<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><span lang="EN-US">Detailed resume including full contact address,
birthdate and full diploma storyboard. Also including our experience in
research, all internships, jobs, and skill in programming.<o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin: 0cm 0cm 6pt 17.85pt; text-indent: -18pt;"><!--[if !supportLists]--><span lang="EN-US" style="mso-bidi-font-size:12.0pt;font-family:Symbol;mso-fareast-font-family:
Symbol;mso-bidi-font-family:Symbol;mso-ansi-language:EN-US">·<span style="font-size: 7pt; font-family: 'Times New Roman';"> </span></span><span lang="EN-US">A special focus on our experience in machine learning,
statistics, and NLP domains would be useful.<o:p></o:p></span></p>
<p class="MsoListParagraph" style="margin: 0cm 0cm 0.0001pt 18pt;"><span lang="EN-US"> </span></p>
<p class="MsoListParagraph" style="margin-left:18.0pt;text-align:justify;
text-justify:inter-ideograph;text-indent:-18.0pt;mso-list:l1 level1 lfo1"><!--[if !supportLists]--><b><span lang="EN-US">9.<span style="font-weight: normal; font-size: 7pt; font-family: 'Times New Roman';">
</span></span></b><!--[endif]--><b><span lang="EN-US">References<o:p></o:p></span></b></p><p class="MsoListParagraph" style="margin-left:18.0pt;text-align:justify;
text-justify:inter-ideograph;text-indent:-18.0pt;mso-list:l1 level1 lfo1"><b><span lang="EN-US"><br></span></b></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[1] Aksoy C. (2010). Novelty Detection in Topic
Tracking, Master Thesis (Advisor Kan F.), Bilkent University, Turkey, July
2010. <o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span style="font-size:11.0pt;line-height:115%">[2] Al-Shehabi
S., Lamirel J.-C. (2004). </span><span lang="EN-GB" style="font-size:11.0pt;
line-height:115%;mso-ansi-language:EN-GB">Inference Bayesian Network for
Multi-topographic neural network communication: a case study in documentary
data. Proceedings of ICTTA, Damas, Syria.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-US" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-US">[3] Al-Shehabi S., Lamirel J.-C. (2005). </span><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-GB">Multi-Topographic
Neural Network Communication and Generalization for Multi-Viewpoint Analysis.
International Joint Conference on Neural Networks – IJCNN'05, Montreal, Canada.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-US" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-US">[4] Al Shehabi S., Lamirel J.-C. (2006). </span><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-GB">A
new hyperbolic visualization method for displaying the results of a neural gas
model: application to webometrics. Proceedings of the 14th European Symposium
on Artificial Neural Networks (ESANN), Brugges, Belgia, April.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[5] Allan J., Carbonell J., Doddington, G.,. Yamron
J., Yang Y. (1998). Topic detection and tracking pilot study, final report.
Proceedings of the DARPA Broadcast News Transcription and Understanding
Workshop, Lansdowne, Virginia.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[6] Batagelj, V. and Zaversnik, M. (2002). An O(m)
algorithm for cores decomposition of networks, University of Ljubljana,
Preprint: IMFM 797.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB;mso-bidi-font-style:italic">[7]<i> </i></span><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-GB">Ester,
M., Kriegel, H.-P., Sander, J., and Xu, X. (1996). A Density-Based Algorithm
for Discovering Clusters in Large Spatial Databases with Noise, In Proc. 2nd
Int. Conf. on Knowledge Discovery and Data Mining (KDD'96): 226-231, AAAI
Press, Menlo Park, CA.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[8] Gaber M., Zaslavsky A. and Krishnaswamy S. (2005).
Mining Data Streams: A Review. SIGMOD Record, 34(2).<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[9] Falk, I., Lamirel J.-C, Gardent C. (2012).
Classifying French Verbs Using French and English Lexical Resources,
International Conference on Computational Linguistic (ACL 2012), Jeju Island,
Korea, July 2012.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[10] Frizke B. (1995). A growing neural gas network learns
topologies, Tesauro G., Touretzky D. S., leen T. K., Eds., Advances in neural
Information processing Systems 7, pp 625-632, MIT Press, Cambridge MA.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[11] Hamza H., Belaïd Y., Belaîd. A, Chaudhuri B. B.
(2008). Incremental classification of invoice documents, 19th International
Conference on Pattern Recognition - ICPR 2008.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span style="font-size:11.0pt;line-height:115%">[12] Kassab
R., Lamirel J.-C. (2007). </span><span lang="EN-GB" style="font-size:11.0pt;
line-height:115%;mso-ansi-language:EN-GB">Towards a synthetic analysis of
user’s information need for more effective personalized filtering services,
Proceedings of the 22th Annual ACM Symposium on Applied Computing (SAC-IAR
2007), Seoul, Korea,, March 2007.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span style="font-size:11.0pt;line-height:115%">[13] Kassab
R., Lamirel J.-C., (2007). </span><span lang="EN-GB" style="font-size:11.0pt;
line-height:115%;mso-ansi-language:EN-GB">Feature Based Cluster Validation for
High Dimensional Data, IASTED International Conference on Artificial
Intelligence and Applications (AIA), Innsbruck, Austria, February 2008.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[14] Kohonen T. (1982). Self-organized formation of
topologically correct feature maps, Biological Cybernetics, vol. 43, pp 56-59.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span style="font-size:11.0pt;line-height:115%">[15] Lamirel
J.-C., Al-Shehabi S., François C., Hoffmann M. (2004). </span><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-GB">New
classification quality estimators for analysis of documentary information:
application to patent analysis and web mapping. Scientometrics, 60(3).<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-US" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-US">[16] Lamirel J.-C., Ta A.P., Attik M. (2007). </span><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-GB">Novel
Labeling Strategies for Hierarchical Representation of Multidimensional Data
Analysis Results, IASTED International Conference on </span><span lang="EN-US" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-US">Artificial
Intelligence and Applications </span><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-GB">(AIA),
Innsbruck, Austria, February 2008.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span style="font-size:11.0pt;line-height:115%">[17] Lamirel
J.-C. (2010). Vers une approche systémique et multivues pour l’analyse de
données et la recherche d’information : un nouveau paradigme, HDR Report,
University of Nancy 2, December 2010.<o:p></o:p></span></p>
<p class="MsoNormal" style="margin-top:6.0pt;text-align:justify;text-justify:
inter-ideograph;line-height:13.0pt;tab-stops:34.05pt 76.65pt 153.35pt"><span style="font-family:"Times New Roman","serif"">[18] </span><span style="font-family:"Times New Roman","serif";mso-fareast-font-family:Times">Lamirel
J.-C., Boulila Z., </span><span style="font-family:"Times New Roman","serif"">Ghribi
M., </span><span style="font-family:"Times New Roman","serif";mso-fareast-font-family:
Times">Cuxac P. (2010).</span><span style="font-family:"Times New Roman","serif"">
</span><span lang="EN-GB" style="font-family:"Times New Roman","serif";
mso-fareast-font-family:Times;mso-ansi-language:EN-GB">A new incremental
growing neural gas algorithm based on clusters labeling maximization:
application to clustering of heterogeneous textual data,</span><span lang="EN-US" style="font-family:"Times New Roman","serif";mso-ansi-language:EN-US">
Proceedings of</span><span lang="EN-GB" style="font-family:"Times New Roman","serif";
mso-fareast-font-family:Times;mso-ansi-language:EN-GB"> the 23<sup>rd</sup>
International Conference on Industrial, Engineering & Other Applications of
Applied Intelligent Systems (IEA-AIE 2010), Cordoba, Spain, June 2010.</span><span lang="EN-US" style="font-family:"Times New Roman","serif";mso-ansi-language:EN-US"><o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[19] Lamirel, J.-C, Mall R., Mall R., Cuxac P., Safi
G. (2011). Variations to incremental growing neural gas algorithm based on
label maximization, Proceedings of IJCNN 2011, San Jose, CA, USA, August 2011.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[20] Lamirel J.-C. (2012). A new diachronic
methodology for automatizing the analysis of research topics dynamics : an
example of application on optoelectronics research, Scientometrics Special issue on 7th International
Conference on Webometrics, Informetrics and Scientometrics and 12th COLLNET,
Scientometrics 93(1): 151-166 (2012).<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[21] Lamirel J.-C., Reymond D. (2013). Automatic
websites classification and retrieval using websites communication signatures, Proceedings
of 8th International Conference on Webometrics, Informetrics and Scientometrics
(WIS), Seoul, Korea, October 2012. To be pubished in: Journal of Information
Management and Scientometrics (JIMS), Special issue on 8th International
Conference on Webometrics, Informetrics and Scientometrics and 13th COLLNET.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[22] Lamirel J.-C., Cuxac P., Chivukula A.S., Hajlaoui
K. (2013). A new feature selection and feature contrasting approach based on
quality metric: application to efficient classification of complex textual
data,</span><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-US"> </span><span lang="EN-GB" style="font-size:11.0pt;
line-height:115%;mso-ansi-language:EN-GB">QIMIE 2013: 3nd International PAKDD
Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data
Mining Models, Brisbane, Australia, April 2013.</span><span lang="EN-US" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-US"><o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-GB">[22] Li W., Huang Y. (2011). New Event Detect
Based on LDA and Correlation of Subject Terms International Conference on </span><a href="http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6005185"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;color:windowtext;
mso-ansi-language:EN-GB;text-decoration:none;text-underline:none">Internet
Technology and Applications (iTAP), Wuhan, China, August 2011. </span></a><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-GB"><o:p></o:p></span></p>
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inter-ideograph"><span style="font-size:11.0pt;line-height:115%">[23] Martinetz
T. et Schulten K. (1991). </span><span lang="EN-GB" style="font-size:11.0pt;
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editors, Articial Neural Networks, pp 397-402. Elsevier Amsterdam.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
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inter-ideograph"><span style="font-size:11.0pt;line-height:115%">[25] Prudent
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<p class="Standard" style="margin-bottom:3.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-US" style="font-size:11.0pt;line-height:115%;
mso-ansi-language:EN-US">[26] Prudent Y., Ennaji, A. (2005). An Incremental
Growing Neural Gas learns Topology, ESANN2005, 13th European Symposium on Ar</span><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;mso-ansi-language:EN-GB">tificial
Neural Networks, Bruges, Belgium, 27-29April 205, published in Neural Networks,
2005. IJCNN apos;05. Proceedings. 2005 IEEE International Joint Conference ,
vol. 2, no. 31 pp 1211 - 1216, July-4 Aug. 2005.<o:p></o:p></span></p>
<p class="Standard" style="margin-bottom:14.0pt;text-align:justify;text-justify:
inter-ideograph"><span lang="EN-GB" style="font-size:11.0pt;line-height:115%;
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(TDT): Overview & perspective. Proceedings of the DARPA Broadcast News
Transcription and Understanding Workshop, Lansdowne, Virginia.<o:p></o:p></span></p><br><div><span name="x"></span>Dr habil. Jean-Charles LAMIREL<br>Maître de Conférences, Habilité à Diriger des Recherches<br>Université de Strasbourg<br>Projet INRIA TALARIS - LORIA - Nancy<br>GSM : 0624365491<br><span name="x"></span><br></div><br></div></body></html>