Research Topics

My research interests lie in scalable data analytics. This spans topics in database systems, distributed computing and machine learning. My current focus is designing scalable similarity search techniques for massive collections of high-dimensional vectors and exploiting them to achieve similarity-based data integration.

Publications

Below is a list of selected publications. A more complete publication record can be found here.

Tutorials

  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. New Trends in High-D Vector Similarity Search: AI-driven, Progressive, and Distributed. International Conference on Very Large Data Bases (VLDB), Copenhagen, Denmark, August 2021.
    (summary, PDF, PPTX, video)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. High-Dimensional Similarity Search for Scalable Data Science. IEEE International Conference on Data Engineering (ICDE), Chania, Greece, April 2021.
    (summary, PDF, PPTX, video)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. Big Sequence [a.k.a. time series, or data series] Management: Scaling Up and Out. International Conference on Extending Database Technology (EDBT), Nicosia, Cyprus, March 2021.
    (summary, poster, PDF, PPTX, video)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. Big Sequence [a.k.a. time series, or data series] Management: on Scalability. IEEE International Conference on Big Data (IEEE BigData), virtual conference, December 2020.
    (summary, PDF, PPTX)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. Big Sequence [a.k.a. time series, or data series] Management. IEEE Symposium on Computers and Communications (ISCC), Rennes, France, July 2020.
    (summary, PDF, PPTX)
Journals
  • Wissam Maamar Kouadri, Mourad Ouziri, Salima Benbernou, Karima Echihabi, Themis Palpanas, Iheb Ben Amor. Quality of Sentiment Analysis Tools: The Reasons of Inconsistency. Proceedings of the VLDB Endowment (PVLDB) Journal, 2021.
    (PDF)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim. Return of the Lernaean Hydra: Experimental Evaluation of Data Series [a.k.a. time series, or sequences] Approximate Similarity Search. Proceedings of the VLDB Endowment (PVLDB) Journal, 2019.
    (PDF, supporting material)
  • Karima Echihabi, ostas Zoumpatianos, Themis Palpanas, Houda Benbrahim. The Lernaean Hydra of Data Series [a.k.a. time series, or sequences] Similarity Search: An Experimental Evaluation of the State of the Art. Proceedings of the VLDB Endowment (PVLDB) Journal, 2018.
    (PDF, supporting material)
Conference Articles
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. Scalable Machine Learning on High-Dimensional Vectors: From Data Series to Deep Network Embeddings. International Conference on Web Intelligence, Mining and Semantics (WIMS), Biarritz, France, June 2020.
    (PDF)
  • Anna Gogolou, Theophanis Tsandilas, Karima Echihabi, Anastasia Bezerianos, Themis Palpanas. Data Series [a.k.a. time series, or sequences] Progressive Similarity Search with Probabilistic Quality Guarantees. ACM SIG International conference on Management of Data / Principles of Database Systems (SIGMOD/PODS), Portland, OR, USA, June 2020.
    (PDF, supporting material)
  • Karima Echihabi (supervised by Themis Palpanas and Houda Benbrahim). Truly Scalable Data Series [a.k.a. time series, or sequences] Similarity Search. Very Large Data Bases (VLDB) PhD Workshop, Los Angeles, CA, USA, August 2019.
    (PDF)

 

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