1 code implementation • 28 Sep 2023 • Catherine Kosten, Philippe Cudré-Mauroux, Kurt Stockinger
With the recent spike in the number and availability of Large Language Models (LLMs), it has become increasingly important to provide large and realistic benchmarks for evaluating Knowledge Graph Question Answering (KGQA) systems.
1 code implementation • Proceedings of the VLDB Endowment (PVLDB) 2020 • Mourad Khayati, Ines Arous, Zakhar Tymchenko, Philippe Cudré-Mauroux
In this paper, we introduce a new online recovery technique to recover multiple time series streams in linear time.
1 code implementation • Proceedings of the VLDB Endowment 2020 • Mourad Khayati, Alberto Lerner, Zakhar Tymchenko, Philippe Cudré-Mauroux
Recording sensor data is seldom a perfect process.
1 code implementation • 17 Dec 2019 • Artem Lutov, Dingqi Yang, Philippe Cudré-Mauroux
Graph embedding has become a key component of many data mining and analysis systems.
Ranked #1 on Node Classification on Eximtradedata (Macro F1 metric)
1 code implementation • Big Data 2019 • Abdelouahab Khelifati, Mourad Khayati, Philippe Cudré-Mauroux
In this work, we demonstrate how one can leverage the correlation across several related time series streams to both drastically improve the compression efficiency and reduce the accuracy loss. We present a novel compression algorithm for time series streams called CORAD (CORelation-Aware compression of time series streams based on sparse Dictionary coding).
no code implementations • 2 Dec 2019 • Akansha Bhardwaj, Jie Yang, Philippe Cudré-Mauroux
Such approaches are, however, limited as they fail to reliably estimate the informativeness of a keyword and its expectation for model training.
1 code implementation • 19 Sep 2019 • Artem Lutov, Mourad Khayati, Philippe Cudré-Mauroux
Clustering is a crucial component of many data mining systems involving the analysis and exploration of various data.
no code implementations • 5 Sep 2019 • Laura Rettig, Julien Audiffren, Philippe Cudré-Mauroux
We address the problem of tuning word embeddings for specific use cases and domains.
1 code implementation • 35th IEEE International Conference on Data Engineering (ICDE) 2019 • Ines Arous, Mourad Khayati, Philippe Cudré-Mauroux, Ying Zhang, Martin Kersten, Svetlin Stalinlov
In this paper, we also compare the efficiency and accuracy of RECOVDB against state-of-the-art recovery systems.
3 code implementations • TACL 2019 • Sebastian Arnold, Rudolf Schneider, Philippe Cudré-Mauroux, Felix A. Gers, Alexander Löser
From our extensive evaluation of 20 architectures, we report a highest score of 71. 6% F1 for the segmentation and classification of 30 topics from the English city domain, scored by our SECTOR LSTM model with bloom filter embeddings and bidirectional segmentation.
1 code implementation • 2018 IEEE International Conference on Data Mining Workshops (ICDMW) 2018 • Artem Lutov, Mourad Khayati, Philippe Cudré-Mauroux
There is a great diversity of clustering and community detection algorithms, which are key components of many data analysis and exploration systems.