Mehwish Alam

Post Doctoral Researcher

mehwish

STLabers say about her

Nobody can stop Mehwish when she works! She always starts and ends what she has to do, with a focused look and a beaming smile.

Mehwish Alam is a Post-Doctoral Researcher at Consiglio Nazionale delle Ricerche (CNR)  and she is currently working between CNR Rome and University of Bologna, Bologna, Italy. The focus of her research is to use Data Mining methods for Semantic Web and Text processing. Recently she was a Post Doctotal Researcher in Laboratoire d’Informatique de Paris-Nord (LIPN). Before her Post-Doc, she was PhD student in the field of Computer Science (2011-2015) in LORIA, INRIA, Nancy Grand-Est, France. Her PhD thesis is supervised by Amedeo Napoli and Malika-Smail Tabbone. Her research interests include the amulgumation of Semantic Web and Data Mining which focus on the question that how semantic web can benefit from data mining and vice versa. Before she started her PhD, she completed her prestigious Erasmus Mundus Research Masters in Language Communication and Technology in the discipline of Natural Language Processing. She completed her Masters in collaboration with University of Groningen, Groningen, the Netherlands and University of Nancy 2, Nancy, France. Her publications are accessible on DBLP [1] and Google Scholar [2].

 

[1] http://dblp.uni-trier.de/pers/hd/a/Alam:Mehwish

[2] https://scholar.google.fr/citations?user=11qHPf0AAAAJ&hl=en

Publications


  • [11]
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    A Proposal for Classifying the Content of the Web of Data Based on FCA and Pattern Structures, , , , , In Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Warsaw, Poland, June 26-29, 2017, Proceedings, .
  • [12]
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    Framester: A Wide Coverage Linguistic Linked Data Hub, , , , , , In Knowledge Engineering and Knowledge Management - 20th International Conference, EKAW 2016, Bologna, Italy, November 19-23, 2016, Proceedings, .
  • [13]
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    Word Frame Disambiguation: Evaluating Linguistic Linked Data on Frame Detection, , , , In Proceedings of the Fourth International Workshop on Linked Data for Information Extraction co-located with 15th International Semantic Web Conference (ISWC 2016), Kobe, Japan, October 18, 2016., .
  • [14]
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    LatViz: A New Practical Tool for Performing Interactive Exploration over Concept Lattices, , , , In Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications, Moscow, Russia, July 18-22, 2016., .
  • [15]
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    Steps Towards Interactive Formal Concept Analysis with LatViz, , , , In Proceedings of the 5th International Workshop "What can FCA do for Artificial Intelligence"? co-located with the European Conference on Artificial Intelligence, FCA4AI@ECAI 2016, The Hague, the Netherlands, August 30, 2016., .
  • [16]
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    Interactive Knowledge Discovery over Web of Data. (Découverte interactive de connaissances dans le web des données), , PhD thesis, University of Lorraine, Nancy, France, .
  • [17]
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    RV-Xplorer: A Way to Navigate Lattice-Based Views over RDF Graphs, , , , In Proceedings of the Twelfth International Conference on Concept Lattices and Their Applications, Clermont-Ferrand, France, October 13-16, 2015., .
  • [18]
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    Revisiting Pattern Structures for Structured Attribute Sets, , , , , In Proceedings of the Twelfth International Conference on Concept Lattices and Their Applications, Clermont-Ferrand, France, October 13-16, 2015., .
  • [19]
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    Interactive exploration over RDF data using formal concept analysis, , , In 2015 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2015, Campus des Cordeliers, Paris, France, October 19-21, 2015, .
  • [20]
    view bibtex
    An Approach Towards Classifying and Navigating RDF data based on Pattern Structures, , , In Proceedings of the International Workshop on Formal Concept Analysis and Applications, FCA&A 2015, co-located with 13th International Conference on Formal Concept Analysis (ICFCA 2015), Nerja, Málaga, Spain, June 23-26, 2015., .
  • Projects

    HAPS

    Holistic Attack Prevention System