Výsledky vyhledávání - "Daniele Sartiano"

Akademický článek

Natural language processing in clinical neuroscience and psychiatry: A review

Autor: Claudio Crema, Giuseppe Attardi, Daniele Sartiano, Alberto Redolfi

Publikováno v: Frontiers in Psychiatry, Vol 13 (2022)

Natural language processing (NLP) is rapidly becoming an important topic in the medical community. The ability to automatically analyze any type of medical document could be the key factor to fully exploit the data it contains. Cutting-edge artificia

Externí odkaz: https://doaj.org/article/f58f477d90304bf9a7656528edae6802

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Using DPI and Statistical Analysis in Encrypted Network Traffic Monitoring

Autor: Daniele Sartiano, Luca Deri

Publikováno v: International Journal for Information Security Research. 10:932-943

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::700f57dedec810366f24a5c1b546d7d7
https://doi.org/10.20533/ijisr.2042.4639.2020.0107

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Biaffine Dependency and Semantic Graph Parsing for Enhanced Universal Dependencies

Autor: Daniele Sartiano, Giuseppe Attardi, Maria Simi

This paper presents the system used in our submission to the IWPT 2021 Shared Task. This year the official evaluation metrics was ELAS, therefore dependency parsing might have been avoided as well as other pipeline stages like POS tagging and lemmati

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1228dd16c8aade864c538378cd79b1e7
http://hdl.handle.net/11568/1109319

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Monitoring IoT Encrypted Traffic with Deep Packet Inspection and Statistical Analysis

Autor: Luca Deri, Daniele Sartiano

Publikováno v: ICITST
6th International Conference for Internet Technology and Secured Transactions (ICITST-2020), London, UK, 08/12/2020
info:cnr-pdr/source/autori:L. Deri; D. Sartiano/congresso_nome:6th International Conference for Internet Technology and Secured Transactions (ICITST-2020)/congresso_luogo:London, UK/congresso_data:08%2F12%2F2020/anno:2020/pagina_da:/pagina_a:/intervallo_pagine

The pervasive use of encrypted protocols and new communication paradigms based on mobile and home IoT devices has obsoleted traffic analysis techniques that relied on clear text analysis. This has required new monitoring metrics being able to charact

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::744b7314594a6accef59dbd0a10b9e73
https://doi.org/10.23919/icitst51030.2020.9351330

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Suspicious Network Event Recognition Leveraging on Machine Learning

Autor: Maurizio Martinelli, Daniele Sartiano, Luca Deri, Giuseppe Attardi

Publikováno v: IEEE BigData
IEEE BigData 2019, pp. 5915–5920, Los Angeles, 09-12/12/2019
info:cnr-pdr/source/autori:Sartiano D. (1); Attardi G. (2); Deri L. (1); Martinelli M (1)/congresso_nome:IEEE BigData 2019/congresso_luogo:Los Angeles/congresso_data:09-12%2F12%2F2019/anno:2019/pagina_da:5915/pagina_a:5920/intervallo_pagine:5915–5920

Network log events produced by network probes are used by security analyzers to detect traffic anomalies and threats. While it is relatively trivial for a probe to mark specific events as suspicious, it is much more challenging for log analyzers to c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1e2edce3eec059c0687493cad3125e6
http://hdl.handle.net/11568/1013724

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Bidirectional LSTM models for DGA classification

Autor: Giuseppe Attardi, Daniele Sartiano

Publikováno v: Communications in Computer and Information Science ISBN: 9789811358258
SSCC

The paper describes our submission to the shared task on DGA classification at DMD 2018. The approach is based on a Deep Learning architecture using bidirectional LSTM neural networks. Similar models are used in both the tasks, the first one is to id

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::125a9fadd9c45714a589ef3acf39dc5b
http://hdl.handle.net/11568/926408

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Using Embeddings for Both Entity Recognition and Linking in Tweets

Autor: Daniele Sartiano, Maria Simi, Irene Sucameli, Giuseppe Attardi

Publikováno v: CLiC-it/EVALITA

The paper describes our submissions to the task on Named Entity rEcognition and Linking in Italian Tweets (NEEL-IT) at Evalita 2016. Our approach relies on a technique of Named Entity tagging that exploits both character-level and word-level embeddin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f40d10b70f59774c8d0100b3af2e5bd2
http://books.openedition.org/aaccademia/1946

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Detecting the scope of negations in clinical notes

Autor: Daniele Sartiano, Giuseppe Attardi, Vittoria Cozza

Publikováno v: Proceedings of the Second Italian Conference on Computational Linguistics CLiC-it 2015 ISBN: 9788899200008

We address the problem of automatically detecting the scope of negations and speculations in clinical notes, by proposing a machine-learning algorithm that analyzes the dependency tree of a sentence. Given a negative/speculative cue, the algorithm tr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70ba369b20bb5296023b6cfdc3460e22
http://books.openedition.org/aaccademia/1286

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UniPI at SemEval-2016 Task 4: Convolutional Neural Networks for Sentiment Classification

Autor: Daniele Sartiano, Giuseppe Attardi

Publikováno v: SemEval@NAACL-HLT

The paper describes our submission to the task on Sentiment Analysis on Twitter at SemEval 2016. The approach is based on a Deep Learning architecture using convolutional neural networks. The approach used only word embeddings as features. The submis

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3067f5c112bae92dd53c5ceb4c82a29e
https://doi.org/10.18653/v1/s16-1033

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