Capturing and anticipating user intents in complex analytics workflows

In today's data-driven world, the ability to extract meaningful information from data is becoming essential for businesses, organizations and researchers alike. For that purpose, a wide range of tools and systems exist involving data-related tasks, from data integration, preprocessing and model...

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Detalles Bibliográficos
Autor: Pons Recasens, Gerard|||0000-0003-2225-3255
Tipo de recurso: tesis de maestría
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/398992
Acceso en línea:https://hdl.handle.net/2117/398992
Access Level:acceso abierto
Palabra clave:Data mining
mineria de dades
graf de coneixement
anàlisi d'intencions
data mining
knowledge graphs
intent analytics
knowledge graph embeddings
Mineria de dades
Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació
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spelling Capturing and anticipating user intents in complex analytics workflowsPons Recasens, Gerard|||0000-0003-2225-3255Data miningmineria de dadesgraf de coneixementanàlisi d'intencionsdata miningknowledge graphsintent analyticsknowledge graph embeddingsMineria de dadesÀrees temàtiques de la UPC::Informàtica::Sistemes d'informacióIn today's data-driven world, the ability to extract meaningful information from data is becoming essential for businesses, organizations and researchers alike. For that purpose, a wide range of tools and systems exist involving data-related tasks, from data integration, preprocessing and modeling, to the interpretation and evaluation of the results. As data continues to grow in volume, variety, and complexity, there is an increasing need for advanced but user-friendly tools that facilitate the user's interaction with them. This is relevant for end users who may not have technical knowledge but still need to take advantage of these powerful tools to make informed decisions. To this end, the primary goal of this Master's Thesis is to investigate and develop methods for capturing and anticipating user intents within complex analytics workflows, focusing on making these systems more intuitive for inexperienced users. This is, the aim is to assist end users when they express their preferences, constraints and/or intentions over analytics workflows, in hopes to enhance their ability to effectively engage with these systems. To achieve this objective, this thesis explores the use of Knowledge Graphs as the basic framework for capturing and anticipating user intentions. First, a Knowledge Graph capable of capturing data mining processes as a whole, from the different workflow steps to the user's inputs and feedback, has been designed by creating new concepts to extend and link other existing ontologies. Then, the graph has been leveraged for anticipation by knowledge extraction through queries. Additionally, the usage of Knowledge Graph Embeddings for recommendation tasks with Link Prediction has been explored.Universitat Politècnica de CatalunyaBilalli, BesimQueralt Calafat, Anna20232023-06-2920242024-01-10master thesishttp://purl.org/coar/resource_type/c_bdccNAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/2117/398992reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3989922026-05-27T15:37:01Z
dc.title.none.fl_str_mv Capturing and anticipating user intents in complex analytics workflows
title Capturing and anticipating user intents in complex analytics workflows
spellingShingle Capturing and anticipating user intents in complex analytics workflows
Pons Recasens, Gerard|||0000-0003-2225-3255
Data mining
mineria de dades
graf de coneixement
anàlisi d'intencions
data mining
knowledge graphs
intent analytics
knowledge graph embeddings
Mineria de dades
Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació
title_short Capturing and anticipating user intents in complex analytics workflows
title_full Capturing and anticipating user intents in complex analytics workflows
title_fullStr Capturing and anticipating user intents in complex analytics workflows
title_full_unstemmed Capturing and anticipating user intents in complex analytics workflows
title_sort Capturing and anticipating user intents in complex analytics workflows
dc.creator.none.fl_str_mv Pons Recasens, Gerard|||0000-0003-2225-3255
author Pons Recasens, Gerard|||0000-0003-2225-3255
author_facet Pons Recasens, Gerard|||0000-0003-2225-3255
author_role author
dc.contributor.none.fl_str_mv Bilalli, Besim
Queralt Calafat, Anna
dc.subject.none.fl_str_mv Data mining
mineria de dades
graf de coneixement
anàlisi d'intencions
data mining
knowledge graphs
intent analytics
knowledge graph embeddings
Mineria de dades
Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació
topic Data mining
mineria de dades
graf de coneixement
anàlisi d'intencions
data mining
knowledge graphs
intent analytics
knowledge graph embeddings
Mineria de dades
Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació
description In today's data-driven world, the ability to extract meaningful information from data is becoming essential for businesses, organizations and researchers alike. For that purpose, a wide range of tools and systems exist involving data-related tasks, from data integration, preprocessing and modeling, to the interpretation and evaluation of the results. As data continues to grow in volume, variety, and complexity, there is an increasing need for advanced but user-friendly tools that facilitate the user's interaction with them. This is relevant for end users who may not have technical knowledge but still need to take advantage of these powerful tools to make informed decisions. To this end, the primary goal of this Master's Thesis is to investigate and develop methods for capturing and anticipating user intents within complex analytics workflows, focusing on making these systems more intuitive for inexperienced users. This is, the aim is to assist end users when they express their preferences, constraints and/or intentions over analytics workflows, in hopes to enhance their ability to effectively engage with these systems. To achieve this objective, this thesis explores the use of Knowledge Graphs as the basic framework for capturing and anticipating user intentions. First, a Knowledge Graph capable of capturing data mining processes as a whole, from the different workflow steps to the user's inputs and feedback, has been designed by creating new concepts to extend and link other existing ontologies. Then, the graph has been leveraged for anticipation by knowledge extraction through queries. Additionally, the usage of Knowledge Graph Embeddings for recommendation tasks with Link Prediction has been explored.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-06-29
2024
2024-01-10
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/398992
url https://hdl.handle.net/2117/398992
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya
publisher.none.fl_str_mv Universitat Politècnica de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300724

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