ieeexplore.ieee.org
Open in
urlscan Pro
2600:9000:26da:a000:1e:d873:7a00:93a1
Public Scan
URL:
https://ieeexplore.ieee.org/xpl/conhome/10675726/proceeding
Submission: On September 24 via manual from CH — Scanned from CH
Submission: On September 24 via manual from CH — Scanned from CH
Form analysis 4 forms found in the DOM
<form _ngcontent-rkg-c477="" novalidate="" role="search" class="search-bar-wrapper ng-untouched ng-pristine ng-valid">
<div _ngcontent-rkg-c477="" class="drop-down d-flex"><label _ngcontent-rkg-c477=""><select _ngcontent-rkg-c477="" aria-label="content type dropdown" name="searchType" class="pe-4 ng-untouched ng-pristine ng-valid">
<option _ngcontent-rkg-c477="" value="0: all">All</option>
<option _ngcontent-rkg-c477="" value="1: books">Books</option>
<option _ngcontent-rkg-c477="" value="2: conferences">Conferences</option>
<option _ngcontent-rkg-c477="" value="3: courses">Courses</option>
<option _ngcontent-rkg-c477="" value="4: periodicals">Journals & Magazines</option>
<option _ngcontent-rkg-c477="" value="5: standards">Standards</option>
<option _ngcontent-rkg-c477="" value="6: authors">Authors</option>
<option _ngcontent-rkg-c477="" value="7: citations">Citations</option><!---->
</select></label></div>
<div _ngcontent-rkg-c477="" class="search-field">
<div _ngcontent-rkg-c477="" class="search-field-icon-container">
<div _ngcontent-rkg-c477="" class="global-search-bar"><xpl-typeahead-migr _ngcontent-rkg-c477="" name="search-term" statsclassname="stats-Global_Search_Type_Dropdown" arialabel="main"
ulclass="search-within-results ui-autocomplete ui-front ui-menu ui-widget ui-widget-content ui-corner-all" minchars="3" _nghost-rkg-c75="">
<div _ngcontent-rkg-c75="" class="Typeahead text-sm-md-lh"><input _ngcontent-rkg-c75="" type="search" autocomplete="off" class="Typeahead-input ng-untouched ng-pristine ng-valid" placeholder="" aria-label="main"><!----></div>
</xpl-typeahead-migr></div><!----><!---->
<div _ngcontent-rkg-c477="" class="search-icon"><button _ngcontent-rkg-c477="" type="submit" aria-label="Search" class="fa fa-search stats-Global_Search_Icon"
data-tealium_data="{"searchTerm": "", "searchType": "all"}"></button></div><!---->
</div><!---->
</div>
</form><form _ngcontent-rkg-c271="" novalidate="" class="search-within-cmpt ng-untouched ng-pristine ng-valid">
<div _ngcontent-rkg-c271="" class="search-within-typeahead-container"><xpl-typeahead-migr _ngcontent-rkg-c271="" placeholder="Search within results" name="search-term" statsclassname="stats-Search_Within_Type_Dropdown"
ulclass="search-within-results ui-autocomplete ui-front ui-menu ui-widget ui-widget-content ui-corner-all" minchars="3" _nghost-rkg-c75="">
<div _ngcontent-rkg-c75="" class="Typeahead text-sm-md-lh"><input _ngcontent-rkg-c75="" type="search" autocomplete="off" class="Typeahead-input ng-untouched ng-pristine ng-valid" placeholder="Search within results"
aria-label="Enter search text"><!----></div>
</xpl-typeahead-migr></div><button _ngcontent-rkg-c271="" type="submit" aria-label="Search Within" class="search-within-submit-button fa fa-search stats-Search_Within_Icon" data-tealium_data="{"searchTerm": ""}"></button>
</form><form novalidate="" class="author-search u-mb-1 ng-untouched ng-pristine ng-valid"><xpl-typeahead-migr ulclass="items" _nghost-rkg-c75="">
<div _ngcontent-rkg-c75="" class="Typeahead text-sm-md-lh"><input _ngcontent-rkg-c75="" type="search" autocomplete="off" class="Typeahead-input ng-untouched ng-pristine ng-valid" placeholder="Enter Author Name"
aria-label="Enter search text"><!----></div>
</xpl-typeahead-migr></form><form novalidate="" class="author-search u-mb-1 ng-untouched ng-pristine ng-valid"><xpl-typeahead-migr ulclass="items" _nghost-rkg-c75="">
<div _ngcontent-rkg-c75="" class="Typeahead text-sm-md-lh"><input _ngcontent-rkg-c75="" type="search" autocomplete="off" class="Typeahead-input ng-untouched ng-pristine ng-valid" placeholder="Enter Affiliation"
aria-label="Enter search text"><!----></div>
</xpl-typeahead-migr></form>Text Content
IEEE Xplore - Conference Table of Contents
Skip to Main Content
* IEEE.org
* IEEE Xplore
* IEEE SA
* IEEE Spectrum
* More Sites
Subscribe
* * Donate
*
*
* Create Account
* Personal Sign In
* Browse
* My Settings
* Help
Institutional Sign In
Institutional Sign In
AllBooksConferencesCoursesJournals & MagazinesStandardsAuthorsCitations
Search within Publication
ADVANCED SEARCH
Browse Conferences >Swiss Conference on Data Scien... >2024 11th IEEE Swiss
Conferenc...
Swiss Conference on Data Science (SDS)
Copy Persistent Link
Browse Title List
Sign up for Conference Alerts
Proceedings
All Proceedings
Popular
2024 11th IEEE Swiss Conference on Data Science (SDS)
DOI: 10.1109/SDS60720.2024
30-31 May 2024
Items Per Page
10 25 50
Export
Email Selected Results
Showing 1-25 of 50
Filter
* SortSequenceSort
Sequence Most Cited [By Papers] Most Cited [By Patents]
* Email
REFINE
* AUTHOR
* Alfredo Cuzzocrea(3)
* Thilo Stadelmann(3)
* Benjamin F. Grewe(2)
* Joanna Weng(2)
* Ricardo Chavarriaga(2)
Show More…
Apply
* AFFILIATION
* Department of Mathematics, Universitas Indonesia, Depok, Indonesia(2)
* University of Calabria, Rende, Italy(2)
* Centre for Artificial Intelligence, ZHAW School of Engineering,
Winterthur, Switzerland(2)
* ECLT, European Centre for Living Technology, Venice, Italy(2)
* Dept. Electrical Engineering, University of Isfahan, Isfahan, Iran(1)
Show More…
Apply
QUICK LINKS
* Search for Upcoming Conferences
* IEEE Publication Recommender
* IEEE Author Center
PROCEEDINGS
The proceedings of this conference will be available for purchase through Curran
Associates.
60720 - SDS, 2024 (PRT)
* Print on DemandPurchase at Partner
Select All on Page
Sort BySequenceSort By
Sequence Most Cited [By Papers] Most Cited [By Patents]
TITLE PAGE I
Publication Year: 2024,Page(s):1 - 1
*
*
TITLE PAGE I
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
TITLE PAGE III
Publication Year: 2024,Page(s):3 - 3
*
*
TITLE PAGE III
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
COPYRIGHT
Publication Year: 2024,Page(s):4 - 4
*
*
COPYRIGHT
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
TABLE OF CONTENTS
Publication Year: 2024,Page(s):5 - 10
*
*
TABLE OF CONTENTS
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
MESSAGE FROM THE GENERAL CHAIRS
Publication Year: 2024,Page(s):11 - 11
*
*
MESSAGE FROM THE GENERAL CHAIRS
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
CONFERENCE ORGANIZATION
Publication Year: 2024,Page(s):12 - 13
*
*
CONFERENCE ORGANIZATION
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
SPONSORS, SUPPORTERS AND CONTRIBUTING ORGANIZATIONS
Publication Year: 2024,Page(s):14 - 14
*
*
SPONSORS, SUPPORTERS AND CONTRIBUTING ORGANIZATIONS
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
INTERVENTIONAL AND COUNTERFACTUAL INFERENCE WITH AUTOREGRESSIVE FLOW MODELS
Ruijing Cui;Jianbin Sun;Zituo Li;Bingyu He;Bingfeng Ge;Kewei Yang
Publication Year: 2024,Page(s):1 - 7
* Abstract
* HTML
*
*
Causal inference plays a crucial role in data science applications. To address
the issue of estimating the distributions of observational, interventional, and
counterfactual data. We present a normalizing flow-based model for capturing
causal mechanisms with known observational data and causal graphs under the
causal sufficiency assumption. Extant methods involve fitting structural causal
models (...Show More
INTERVENTIONAL AND COUNTERFACTUAL INFERENCE WITH AUTOREGRESSIVE FLOW MODELS
Ruijing Cui;Jianbin Sun;Zituo Li;Bingyu He;Bingfeng Ge;Kewei Yang
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
POLYNOMIAL REGRESSION HYPERPARAMETER SELECTION AND ANALYSIS USING RECONSTRUCTION
ERROR MINIMIZATION (REM)
Soosan Beheshti;Mahdi Shamsi;Younes Sadat-Nejad;Miaosen Zhou
Publication Year: 2024,Page(s):8 - 15
* Abstract
* HTML
*
*
Machine Learning algorithms in Regression modeling generally minimize the mean
square error (MSE) of estimation to find the optimum parameters. This MSE,
denoted by data error, however, can not be used in hyperparameters selection
(HPS) as it is a decreasing function of increasing the dimension of the
hyperparameters. Well-known validation methods split the data into training and
validation sets f...Show More
POLYNOMIAL REGRESSION HYPERPARAMETER SELECTION AND ANALYSIS USING RECONSTRUCTION
ERROR MINIMIZATION (REM)
Soosan Beheshti;Mahdi Shamsi;Younes Sadat-Nejad;Miaosen Zhou
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
ANALYZING NON-LINEAR NETWORK EFFECTS IN THE EUROPEAN INTERBANK MARKET
Edoardo Filippi-Mazzola;Federica Bianchi;Ernst C. Wit
Publication Year: 2024,Page(s):16 - 22
* Abstract
* HTML
*
*
The European interbank market has been a crucial component of the financial
system where European banks engage in short-term borrowing and lending amongst
themselves. This market primarily facilitates the redistribution of liquidity
within the financial system, allowing banks with surplus funds to lend to those
experiencing shortfalls. The sheer number of interactions has prevented until
now a det...Show More
ANALYZING NON-LINEAR NETWORK EFFECTS IN THE EUROPEAN INTERBANK MARKET
Edoardo Filippi-Mazzola;Federica Bianchi;Ernst C. Wit
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
MINING AND FORECASTING ENERGY CONSUMPTION BASED ON WEATHER DATA
Nathaniel Giesbrecht;Owen A. Hnylycia;Carson K. Leung;Junyi Lu;Thanh Huy Daniel
Mai;Fan Jiang;Alfredo Cuzzocrea
Publication Year: 2024,Page(s):23 - 30
* Abstract
* HTML
*
*
For a modern grid to be reliable, energy efficiency and identifying consistent
energy consumption patterns are becoming essential. In this paper, we present a
data science solution that analyzes and predicts temporal energy consumption
patterns using techniques like frequent pattern mining, traditional machine
learning and deep learning. Specifically, our data science solution mines and
forecasts ...Show More
MINING AND FORECASTING ENERGY CONSUMPTION BASED ON WEATHER DATA
Nathaniel Giesbrecht;Owen A. Hnylycia;Carson K. Leung;Junyi Lu;Thanh Huy Daniel
Mai;Fan Jiang;Alfredo Cuzzocrea
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
SENTIMENT ANALYSIS OF ARABIC TWEETS USING ARABERT AS A FINE TUNER AND FEATURE
EXTRACTORS
Athir Mohammed Alsugair;Norah Saleh Alghamdi
Publication Year: 2024,Page(s):31 - 36
* Abstract
* HTML
*
*
The influence of social media platforms on our daily lives is significant, and
Twitter is one such platform that can serve as a valuable source for gathering
public opinion on various products, services, and events. Sentiment analysis is
a technique that involves analysing the emotions and attitudes expressed by the
public toward specific topics, which can be categorized as positive, negative,
or ...Show More
SENTIMENT ANALYSIS OF ARABIC TWEETS USING ARABERT AS A FINE TUNER AND FEATURE
EXTRACTORS
Athir Mohammed Alsugair;Norah Saleh Alghamdi
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
MLOPS AS ENABLER OF TRUSTWORTHY AI
Yann Billeter;Philipp Denzel;Ricardo Chavarriaga;Oliver Forster;Frank-Peter
Schilling;Stefan Brunner;Carmen Frischknecht-Gruber;Monika Reif;Joanna Weng
Publication Year: 2024,Page(s):37 - 40
* Abstract
* HTML
*
*
As Artificial Intelligence (AI) systems are becoming ever more capable of
performing complex tasks, their prevalence in industry, as well as society, is
increasing rapidly. Adoption of AI systems requires humans to trust them,
leading to the concept of trustworthy AI which covers principles such as
fairness, reliability, explainability, or safety. Implementing AI in a
trustworthy way is encouraged...Show More
MLOPS AS ENABLER OF TRUSTWORTHY AI
Yann Billeter;Philipp Denzel;Ricardo Chavarriaga;Oliver Forster;Frank-Peter
Schilling;Stefan Brunner;Carmen Frischknecht-Gruber;Monika Reif;Joanna Weng
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
ESTIMATING PARCEL DELIVERY DAY VIA QUANTILE REGRESSION
Antonio Rueda-Toicen;Allan A. Zea
Publication Year: 2024,Page(s):41 - 46
* Abstract
* HTML
*
*
The problem of delivery time estimation consists in accurately predicting how
long it will take for a parcel to be delivered to a customer. These predictions
have traditionally been computed by analyzing large collections of carrier,
parcel and customer data (e.g., shipping method, carrier performance along a
given route, parcel size/weight, buyer/seller address, GPS location, among
others). In th...Show More
ESTIMATING PARCEL DELIVERY DAY VIA QUANTILE REGRESSION
Antonio Rueda-Toicen;Allan A. Zea
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
CAWA-NERF: INSTANT LEARNING OF COMPRESSION-AWARE NERF FEATURES
Omnia Mahmoud;Théo Ladune;Matthieu Gendrin
Publication Year: 2024,Page(s):47 - 54
* Abstract
* HTML
*
*
Modeling 3D scenes by volumetric features is one of the promising directions of
neural approximations to improve Neural Radiance Field (NeRF) models.
Instant-NGP (INGP) introduced multi-resolution hash encoding from a lookup table
of trainable feature grids which enabled learning high-quality neural graphics
primitives in a matter of seconds. However, this improvement came at the cost of
higher st...Show More
CAWA-NERF: INSTANT LEARNING OF COMPRESSION-AWARE NERF FEATURES
Omnia Mahmoud;Théo Ladune;Matthieu Gendrin
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
NAVIGATING THE DIGITAL LANDSCAPE: ENHANCING SMALL AND MEDIUM BUSINESS’S SECURITY
THROUGH ASSET MANAGEMENT AND DATA CLASSIFICATION
Siddharth Dua;Pooja Shah;Eslam G. AbdAllah
Publication Year: 2024,Page(s):55 - 61
* Abstract
* HTML
*
*
Small and Medium Enterprises (SMEs) account for 90% of businesses globally and
contribute to 50% employment worldwide. Despite many widely acclaimed
cybersecurity standards or frameworks that exist in the industry, SMEs are most
vulnerable to cyberattacks and have a high chance of losing their existence if
they undergo a successful cyberattack by cybercriminals. SMEs are rapidly
adopting latest te...Show More
NAVIGATING THE DIGITAL LANDSCAPE: ENHANCING SMALL AND MEDIUM BUSINESS’S SECURITY
THROUGH ASSET MANAGEMENT AND DATA CLASSIFICATION
Siddharth Dua;Pooja Shah;Eslam G. AbdAllah
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
SECBOX: A LIGHTWEIGHT DATA MINING PLATFORM FOR DYNAMIC AND REPRODUCIBLE MALWARE
ANALYSIS
Chao Feng;Jan Von Der Assen;Alberto Huertas Celdran;Raffael Mogicato;Adrian
Zermin;Vichhay Ok;Gerome Bovet;Burkhard Stiller
Publication Year: 2024,Page(s):62 - 67
* Abstract
* HTML
*
*
In the era of digitalization, the availability of data is paramount for any
scenario that requires informed decision-making. In the cybersecurity world,
this is no different. This is especially the case for malware since, even though
malware samples share common ancestors, implementations are commonly adapted
into many strains, requiring frequent execution and analysis to implement
appropriate det...Show More
SECBOX: A LIGHTWEIGHT DATA MINING PLATFORM FOR DYNAMIC AND REPRODUCIBLE MALWARE
ANALYSIS
Chao Feng;Jan Von Der Assen;Alberto Huertas Celdran;Raffael Mogicato;Adrian
Zermin;Vichhay Ok;Gerome Bovet;Burkhard Stiller
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
CIML-R: CAUSALLY INFORMED MACHINE LEARNING BASED ON FEATURE RELEVANCE
Martin Surner;Abdelmajid Khelil
Publication Year: 2024,Page(s):68 - 75
* Abstract
* HTML
*
*
Applications relying on machine learning and statistical learning techniques,
such as neural networks, have significantly grown over the past decade.
Nevertheless, as these techniques learn only from observational data, they
suffer from spurious correlations that may limit their performance in domain
shifts. In this paper, we address this issue. We propose an approach that guides
neural networks d...Show More
CIML-R: CAUSALLY INFORMED MACHINE LEARNING BASED ON FEATURE RELEVANCE
Martin Surner;Abdelmajid Khelil
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
LIGHTWEIGHT STOCHASTIC CONFIGURATION NETWORKS
Dianhui Wang;Matthew J. Felicetti
Publication Year: 2024,Page(s):76 - 83
* Abstract
* HTML
*
*
Stochastic configuration networks (SCNs) are a class of randomized learner model
that ensure the universal approximation property at an algorithmic level, where
random parameters are assigned in the light of a supervisory mechanism. This
paper further develops SCN concept for industrial AI applications that require
low-bit learner models for computing resource-limited environments. By
restricting ...Show More
LIGHTWEIGHT STOCHASTIC CONFIGURATION NETWORKS
Dianhui Wang;Matthew J. Felicetti
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
TOWARDS THE CERTIFICATION OF AI-BASED SYSTEMS
Philipp Denzel;Stefan Brunner;Yann Billeter;Oliver Forster;Carmen
Frischknecht-Gruber;Monika Reif;Frank-Peter Schilling;Joanna Weng;Ricardo
Chavarriaga;Amin Amini;Marco Repetto;Arman Iranfar
Publication Year: 2024,Page(s):84 - 91
* Abstract
* HTML
*
*
Certifying the trustworthiness of Artificial Intelligence (AI)-based systems
based on dimensions including reliability and transparency is crucial given
their increased uptake. Likewise, as regulatory requirements are established,
actionable guidelines for certification will be useful for developers and
certification bodies to ensure trustworthiness of AI. Here, we present an
ongoing effort to dev...Show More
TOWARDS THE CERTIFICATION OF AI-BASED SYSTEMS
Philipp Denzel;Stefan Brunner;Yann Billeter;Oliver Forster;Carmen
Frischknecht-Gruber;Monika Reif;Frank-Peter Schilling;Joanna Weng;Ricardo
Chavarriaga;Amin Amini;Marco Repetto;Arman Iranfar
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
ALGORITHMIC TRADING USING TECHNICAL INDICATORS AND EXTEREME GRADIENT BOOSTING
Seyed Mohammad Rahimpour;Rouzbeh Goudarzi;Vahid Shahparifard;Seyed Navid
Mirpoorian
Publication Year: 2024,Page(s):92 - 98
* Abstract
* HTML
*
*
The essence of profitable trading is navigating the perilous balance between
minimising risk and maximising consistent returns. Success hinges on precise
timing in choosing the suitable buy and sell signals. This paper proposes a
novel approach that treats this decision-making process as a classification
problem. We introduce a unique method for labelling training data, enabling an
XGBClassifier t...Show More
ALGORITHMIC TRADING USING TECHNICAL INDICATORS AND EXTEREME GRADIENT BOOSTING
Seyed Mohammad Rahimpour;Rouzbeh Goudarzi;Vahid Shahparifard;Seyed Navid
Mirpoorian
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
OPTIMAL PRICING OF CONFIGURABLE PRODUCTS USING MACHINE LEARNING
Angel C. Hernandez;David Masaryk;Juraj Mecir;Siamak Saliminejad
Publication Year: 2024,Page(s):99 - 106
* Abstract
* HTML
*
*
In this paper, we proposed a Machine Learning (ML) based methodology to
optimally price configurable products. The methodology uses an ensemble of ML
models to forecast the demand; along with an optimization framework to find the
prices and upgrades that achieve highest business goals. The novelty of proposed
methodology is providing an intuitive upgrade pricing experience for customers
while targ...Show More
OPTIMAL PRICING OF CONFIGURABLE PRODUCTS USING MACHINE LEARNING
Angel C. Hernandez;David Masaryk;Juraj Mecir;Siamak Saliminejad
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
REIMAGINING ENTERPRISE DATA MANAGEMENT USING GENERATIVE ARTIFICIAL INTELLIGENCE
Sandeep Varma;Shivam Shivam;Biswarup Ray;Snigdha Biswas
Publication Year: 2024,Page(s):107 - 114
* Abstract
* HTML
*
*
Enterprise Data Management (EDM) is a comprehensive approach encompassing data
acquisition, profiling, standardization, quality assurance, and transformation,
along with governance, to optimize the lifecycle of an organization’s data
assets and facilitate meaningful analysis. The recent rise of Large Language
Models (LLMs) and Generative Artificial Intelligence has fundamentally
transformed data-r...Show More
REIMAGINING ENTERPRISE DATA MANAGEMENT USING GENERATIVE ARTIFICIAL INTELLIGENCE
Sandeep Varma;Shivam Shivam;Biswarup Ray;Snigdha Biswas
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
A DEEP LEARNING APPROACH FOR TRAFFIC CIRCLE DETECTION
Raphael Brunold;Beat Brändli;Leandro Gregorini;Andre Glatzl;Alexander Van
Schie;Michael Burch
Publication Year: 2024,Page(s):115 - 122
* Abstract
* HTML
*
*
Traffic circles, also known as roundabouts, are a modern way to improve traffic
situations and in particular, the traffic flow which leads to a decrease in the
number of accidents and air pollution. Due to these benefits there is an
increasing number of traffic circles in the world with various properties,
forms, shapes, colors, and several other visual features and enhancements, even
multi-lane v...Show More
A DEEP LEARNING APPROACH FOR TRAFFIC CIRCLE DETECTION
Raphael Brunold;Beat Brändli;Leandro Gregorini;Andre Glatzl;Alexander Van
Schie;Michael Burch
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
SUPERCHARGING DOCUMENT COMPOSITION WITH GENERATIVE AI: A SECURE, CUSTOM
RETRIEVAL-AUGMENTED GENERATION APPROACH
Andre Chen;Sieu Tran
Publication Year: 2024,Page(s):123 - 130
* Abstract
* HTML
*
*
Recent advancements in Retrieval Augmented Generation (RAG) provide
opportunities for more efficient composition of long-form, domain-specific
documents. However, few user-friendly applications leverage RAG for this
specific use case. Additionally, existing RAG frameworks reliant on cloud-based,
closed-source solutions pose challenges such as transparency and data privacy
concerns. To address this...Show More
SUPERCHARGING DOCUMENT COMPOSITION WITH GENERATIVE AI: A SECURE, CUSTOM
RETRIEVAL-AUGMENTED GENERATION APPROACH
Andre Chen;Sieu Tran
2024 11th IEEE Swiss Conference on Data Science (SDS)
Year: 2024
Load More
* 1
* 2
* >
*
QUICK LINKS
* Search for Upcoming Conferences
* IEEE Publication Recommender
* IEEE Author Center
PROCEEDINGS
The proceedings of this conference will be available for purchase through Curran
Associates.
60720 - SDS, 2024 (PRT)
* Print on DemandPurchase at Partner
IEEE ACCOUNT
* Change Username/Password
* Update Address
PURCHASE DETAILS
* Payment Options
* Order History
* View Purchased Documents
PROFILE INFORMATION
* Communications Preferences
* Profession and Education
* Technical Interests
NEED HELP?
* US & Canada: +1 800 678 4333
* Worldwide: +1 732 981 0060
* Contact & Support
* About IEEE Xplore
* Contact Us
* Help
* Accessibility
* Terms of Use
* Nondiscrimination Policy
* Sitemap
* Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical
professional organization dedicated to advancing technology for the benefit of
humanity.
© Copyright 2024 IEEE - All rights reserved. Use of this web site signifies your
agreement to the terms and conditions.