mofeed-hassan_1PhD Student

Agile Knowledge Engineering and Semantic Web (AKSW)
University of Leipzig

Profiles: DBLP

Augustusplatz 10, 04109 Leipzig
mounir@informatik.uni-leipzig.de
Phone: +49-341-97-32260

Short CV


Mofeed Hassan is a PhD Student at the University of Leipzig. Mofeed’ research interests are in the area of Link Specification Learning.

Research Interests


  • Machine Learning
  • Link Specification Learning

Publications


2016

  • M. A. Sherif, M. Hassan, T. Soru, A. Ngonga Ngomo, and J. Lehmann, “Lion’s Den: Feeding the LinkLion,” in Proceedings of Ontology Matching Workshop, 2016.
    [BibTeX] [Download PDF]
    @InProceedings{lionsden16,
    Title = {Lion's Den: Feeding the LinkLion},
    Author = {Mohamed Ahmed Sherif and Mofeed Hassan and Tommaso Soru and Axel-Cyrille {Ngonga Ngomo} and Jens Lehmann},
    Booktitle = {Proceedings of Ontology Matching Workshop},
    Year = {2016},
    Keywords = {sherif hassan soru lehmann ngonga geoknow group_aksw SIMBA sys:relevantFor:infai sys:relevantFor:bis limes},
    Owner = {sherif},
    Timestamp = {2016.09.26},
    Url = {http://disi.unitn.it/~pavel/om2016/papers/om2016_poster5.pdf}
    }

  • U. U. Hassan, E. Curry, A. Zaveri, E. Marx, and J. Lehmann, “ACRyLIQ: Leveraging DBpedia for Adaptive Crowdsourcing in Linked Data Quality Assessment,” in 20th International Conference on Knowledge Engineering and Knowledge Management (EKAW), November 19-23, 2016, Bologna, Italy, 2016.
    [BibTeX]
    @InProceedings{umair/2016,
    Title = {{ACRyLIQ}: {L}everaging {DB}pedia for {A}daptive {C}rowdsourcing in {L}inked {D}ata {Q}uality {A}ssessment},
    Author = {Hassan, Umair Ul and Curry, Edward and Zaveri, Amrapali and Marx, Edgard and Lehmann, Jens},
    Booktitle = {20th International Conference on Knowledge Engineering and Knowledge Management (EKAW), November 19-23, 2016, Bologna, Italy},
    Year = {2016},
    Series = {EKAW 2016},
    Biburl = {http://www.bibsonomy.org/bibtex/2cbea4b8d22c87292c6e4405e7f1e60f2/aksw},
    Interhash = {e3b34694cb7f4c06ce1d782ff3d20d44},
    Intrahash = {cbea4b8d22c87292c6e4405e7f1e60f2},
    Keywords = {MOLE group_aksw lehmann marx mole simba zaveri}
    }

  • A. N. Ngomo and M. M. Hassan, “The Lazy Traveling Salesman – Memory Management for Large-Scale Link Discovery.,” in ESWC, 2016, pp. 423-438.
    [BibTeX] [Download PDF]
    @InProceedings{conf/esws/NgomoH16,
    Title = {The Lazy Traveling Salesman - Memory Management for Large-Scale Link Discovery.},
    Author = {Ngomo, Axel-Cyrille Ngonga and Hassan, Mofeed M.},
    Booktitle = {ESWC},
    Year = {2016},
    Editor = {Sack, Harald and Blomqvist, Eva and d'Aquin, Mathieu and Ghidini, Chiara and Ponzetto, Simone Paolo and Lange, Christoph},
    Pages = {423-438},
    Publisher = {Springer},
    Series = {Lecture Notes in Computer Science},
    Volume = {9678},
    Added-at = {2016-05-23T00:00:00.000+0200},
    Biburl = {http://www.bibsonomy.org/bibtex/2f10ed38832e989fbcfe16c38839518be/dblp},
    Crossref = {conf/esws/2016},
    Ee = {http://dx.doi.org/10.1007/978-3-319-34129-3_26},
    Interhash = {3538c8f01dbbdf2f585250f24901f740},
    Intrahash = {f10ed38832e989fbcfe16c38839518be},
    ISBN = {978-3-319-34128-6},
    Keywords = {dblp 2016 ngonga hassan SIMBA},
    Timestamp = {2016-05-24T11:43:38.000+0200},
    Url = {http://dblp.uni-trier.de/db/conf/esws/eswc2016.html#NgomoH16}
    }

2015

  • M. M. Hassan, R. Speck, and A. Ngonga Ngomo, “Using Caching for Local Link Discovery on Large Data Sets,” in Engineering the Web in the Big Data Era, Springer International Publishing, 2015, vol. 9114, pp. 344-354. doi:10.1007/978-3-319-19890-3_22
    [BibTeX] [Download PDF]
    @InCollection{mofeedCaching,
    Title = {Using Caching for Local Link Discovery on Large Data Sets},
    Author = {Hassan, Mofeed M. and Speck, Ren{\'e} and Ngonga Ngomo, Axel-Cyrille},
    Booktitle = {Engineering the Web in the Big Data Era},
    Publisher = {Springer International Publishing},
    Year = {2015},
    Pages = {344-354},
    Series = {Lecture Notes in Computer Science},
    Volume = {9114},
    Bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-319-19890-3_22},
    Doi = {10.1007/978-3-319-19890-3_22},
    ISBN = {978-3-319-19889-7},
    Keywords = {2015 hassan speck ngonga SIMBA sys:relevantFor:geoknow geoknow},
    Language = {English},
    Url = {http://dx.doi.org/10.1007/978-3-319-19890-3_22}
    }

  • M. Hassan, J. Lehmann, and A. N. Ngomo, “Interlinking: Performance Assessment of User Evaluation vs. Supervised Learning Approaches,” in Proceedings of the 8th Workshop on Linked Data on the Web (LDOW2015), Florence, Italy, 2015.
    [BibTeX] [Abstract] [Download PDF]
    Interlinking knowledge bases are widely recognized as an important, but challenging problem. A significant amount of research has been undertaken to provide solutions to this problem with varying degrees of automation and user involvement. In this paper, we present a two-staged experiment for the creation of gold standards that act as benchmarks for several interlinking algorithms. In the first stage the gold standards are generated through manual validation process highlighting the role of users. Using the gold standards obtained from this stage, we assess the performance of human evaluators in addition to supervised interlinking algorithms. We evaluate our approach on several data interlinking tasks with respect to precision, recall and F-measure. Additionally we perform a qualitative analysis on the types of errors made by humans and machines.

    @InProceedings{mofeedHuman15,
    Title = {Interlinking: Performance Assessment of User Evaluation vs. Supervised Learning Approaches},
    Author = {Mofeed Hassan and Jens Lehmann and Axel-C. Ngonga Ngomo},
    Booktitle = {Proceedings of the 8th Workshop on Linked Data on the Web (LDOW2015), Florence, Italy},
    Year = {2015},
    Abstract = {Interlinking knowledge bases are widely recognized as an important, but challenging problem. A significant amount of research has been undertaken to provide solutions to this problem with varying degrees of automation and user involvement. In this paper, we present a two-staged experiment for the creation of gold standards that act as benchmarks for several interlinking algorithms. In the first stage the gold standards are generated through manual validation process highlighting the role of users. Using the gold standards obtained from this stage, we assess the performance of human evaluators in addition to supervised interlinking algorithms. We evaluate our approach on several data interlinking tasks with respect to precision, recall and F-measure. Additionally we perform a qualitative analysis on the types of errors made by humans and machines.},
    Keywords = {2015 group_aksw group_mole MOLE mole hassan lehmann ngonga MOLE sys:relevantFor:geoknow geoknow},
    Owner = {mofeed},
    Timestamp = {2015.07.31},
    Url = {http://svn.aksw.org/papers/2015/LDOW_Human/public.pdf}
    }

2013

  • A. Zaveri, J. Lehmann, S. Auer, M. M. Hassan, M. A. Sherif, and M. Martin, “Publishing and Interlinking the Global Health Observatory Dataset,” Semantic Web Journal, vol. Special Call for Linked Dataset descriptions, iss. 3, pp. 315-322, 2013.
    [BibTeX] [Abstract] [Download PDF]
    The improvement of public health is one of the main indicators for societal progress. Statistical data for monitoring public health is highly relevant for a number of sectors, such as research (e.g. in the life sciences or economy), policy making, health care, pharmaceutical industry, insurances etc. Such data is meanwhile available even on a global scale, e.g. in the Global Health Observatory (GHO) of the United Nations’s World Health Organization (WHO). GHO comprises more than 50 different datasets, it covers all 198 WHO member countries and is updated as more recent or revised data becomes available or when there are changes to the methodology being used. However, this data is only accessible via complex spreadsheets and, therefore, queries over the 50 different datasets as well as combinations with other datasets are very tedious and require a significant amount of manual work. By making the data available as RDF, we lower the barrier for data re-use and integration. In this article, we describe the conversion and publication process as well as use cases, which can be implemented using the GHO data.

    @Article{zaveri-gho,
    Title = {Publishing and Interlinking the Global Health Observatory Dataset},
    Author = {Amrapali Zaveri and Jens Lehmann and S{\"o}ren Auer and Mofeed M. Hassan and Mohamed A. Sherif and Michael Martin},
    Journal = {Semantic Web Journal},
    Year = {2013},
    Number = {3},
    Pages = {315-322},
    Volume = {Special Call for Linked Dataset descriptions},
    Abstract = {The improvement of public health is one of the main indicators for societal progress. Statistical data for monitoring public health is highly relevant for a number of sectors, such as research (e.g. in the life sciences or economy), policy making, health care, pharmaceutical industry, insurances etc. Such data is meanwhile available even on a global scale, e.g. in the Global Health Observatory (GHO) of the United Nations's World Health Organization (WHO). GHO comprises more than 50 different datasets, it covers all 198 WHO member countries and is updated as more recent or revised data becomes available or when there are changes to the methodology being used. However, this data is only accessible via complex spreadsheets and, therefore, queries over the 50 different datasets as well as combinations with other datasets are very tedious and require a significant amount of manual work. By making the data available as RDF, we lower the barrier for data re-use and integration. In this article, we describe the conversion and publication process as well as use cases, which can be implemented using the GHO data. },
    Bdsk-url-1 = {http://www.semantic-web-journal.net/system/files/swj433.pdf},
    Date-modified = {2013-07-11 19:43:06 +0000},
    Ee = {http://dx.doi.org/10.3233/SW-130102},
    Keywords = {2013 MOLE group_aksw zaveri martin lehmann auer hassan sherif sys:relevantFor:infai sys:relevantFor:bis sys:relevantFor:lod2 lod2page peer-reviewed gho},
    Owner = {micha},
    Url = {http://www.semantic-web-journal.net/system/files/swj433.pdf}
    }

  • A. N. Ngomo, J. Lehmann, and M. Hassan, “Transfer Learning of Link Specifications,” in Seventh IEEE International Conference on Semantic Computing (ICSC), 2013.
    [BibTeX] [Download PDF]
    @InProceedings{tl-icsc,
    Title = {Transfer Learning of Link Specifications},
    Author = {Axel-Cyrille Ngonga Ngomo and Jens Lehmann and Mofeed Hassan},
    Booktitle = {Seventh IEEE International Conference on Semantic Computing (ICSC)},
    Year = {2013},
    Bdsk-url-1 = {http://svn.aksw.org/papers/2013/ICSC_TransferLearning/public.pdf},
    Keywords = {2013 group_aksw group_mole MOLE SIMBA lehmann ngonga hassan sys:relevantFor:infai sys:relevantFor:bis sys:relevantFor:lod2 sys:relevantFor:geoknow topic_Interlinking peer-reviewed},
    Url = {http://svn.aksw.org/papers/2013/ICSC_TransferLearning/public.pdf}
    }