KELLOU-MENOUER Kenza

Schema discovery for Semantic Web data;

Data mining, recommendation and prediction: Unsupervised machine learning (Clustering), Supervised machine learning (Classification) and Association rules;

Search Optimization and Big Data

Semantic Web: RDF(S)/OWL, SPARQL, Protected, etc;

Database design and analysis: UML, SQL, Oracle, SQL Developer, PostgreSQL, SQL Server, EasyPHP, WampServer;

Data mining, recommendation and prediction: Unsupervised machine learning (Clustering), Supervised machine learning (Classification) and Association rules;

Algorithms and Data Structures;

Object-Oriented Programming: Java, C++, C#;

Other programming languages: C

Organization of a tutorial on the theme of my doctoral thesis (schema discovery for Semantic Web data): Tutorial on Semantic Schema Discovery. The 21st International Semantic Web Conference (ISWC) 2022

Publications with proceedings and reading committee

[1] K. Kellou-Menouer, N. Kardoulakis, G. Troullinou, Z. Kedad, D. Plexousakis and H
Kondylakis. A Survey on Semantic Schema Discovery. Very Large Data Base Journal (VLDB)
Journal) 2022;

2] K. Kellou-Menouer, N. Kardoulakis, G. Troullinou, Z. Kedad, D. Plexousakis and H
Kondylakis. Tutorial on Semantic Schema Discovery. The 21st International Semantic Web
Conference (ISWC) 2022;

[3] N. Kardoulakis, K. Kellou-Menouer, G. Troullinou, Z. Kedad, D. Plexousakis and H
Kondylakis. Demo on Hybrid and Incremental Type Discovery for Large RDF Data Sources.
The 21st International Semantic Web Conference (ISWC) 2022;

[4] N. Kardoulakis, K. Kellou-Menouer, G. Troullinou, Z. Kedad, D. Plexousakis and H
Kondylakis. HInT: Hybrid and Incremental Type Discovery for Large RDF Data Sources. Tea
33rd International Conference on Scientific and Statistical Database Management (SSDBM)
2021;

[5] K. Kellou-Menouer and Z. Kedad. SchemaDecrypt++: Parallel On-line Versioned Schema
Inference for Large Semantic Web Data Sources. Information Systems Journal, 2020;

[6] R. Bouhamoum, K. Kellou-Menouer, Z. Kedad and Stéphane Lopes. Scaling Up Schema
Discovery for RDF Datasets. 9th workshop on Data Engineering meets the Semantic Web
(DESWeb) in conjunction with 34th International Conference on Data Engineering, ICDE,
2018;

[7] K. Kellou-Menouer, Z. Kedad. Online Versioned Schema Inference for Large Semantics
Web Data Sources. 29th International Conference on Scientific and Statistical Database
Management, SSDBM, 1-12, 2017;

[8] K. Kellou-Menouer and Z. Kedad. A Self-Adaptive and Incremental Approach for Data
Proling in the Semantic Web. International Journal for Transactions on Large-Scale Data
and Knowledge-Centered Systems, TLDKS, 108-133, 2016;

[9] K. Kellou-Menouer and Z. Kedad. Class Annotation Using Linked Open Data. OTM
Conferences, 709-726, 2016;

[10] K. Kellou-Menouer and Z. Kedad. Schema Discovery in RDF Data Sources. International
Conference on Conceptual Modeling, ER, 481-495, 2015;

[11] K. Kellou-Menouer and Z. Kedad. Evaluating the Gap between a Dataset and Its Schema.
Workshop Quality of Models and Models of Quality in conjunction with the International
Conference on Conceptual Modeling (ER), QMMQ, 283-292, 2015;

[12] K. Kellou-Menouer and Z. Kedad. Discovering Types in RDF Datasets. Extended Semantics
Web Conference, ESWC, 77-81, 2015;

[13] K. Kellou-Menouer and Z. Kedad. A Clustering Based Approach for Type discovery in
RDF Data Sources. International Conference on Knowledge Extraction and Management,
EGC, 471-472, 2015;

[14] K. Kellou-Menouer and Z. Kedad. Using Clustering for Type Discovery in the Semantic
Web. Complex Data Mining Workshop, FDC, 2015
*Very Large Data Base Journal (VLDBJ), Information Systems Journal and the ICDE conference
are A* rated; SSDBM, ER and ESWC are A rated conferences. (CORE Conference
Ranking)

Short research internships;

PFE/Master Thesis