Parsimonious sensing with Active Learning: applications with context mining and environmental sensing

Bibliographic Details
Main Author: Frutuoso, Manuel Levi Lacerda Amaral Eirô
Publication Date: 2015
Format: Master thesis
Language: eng
Source: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Download full: http://hdl.handle.net/10316/35661
Summary: Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra.
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spelling Parsimonious sensing with Active Learning: applications with context mining and environmental sensingActive LearningBig DataContext SensingData MiningEvent IdentificationParsimonious SensingDissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra.The unprecedented success of Web 2.0, and with it, social media services, has resulted in massive amounts of user-generated data. Traditional techniques are no longer adequate to deal with this sheer amount of information. In an attempt to address this problem, new techniques that can be applied to big data, are being proposed in an increasingly frequent way. In this dissertation, the concept of parsimonious sensing and some of its applications are presented. Parsimonious sensing attempts to select the most relevant information from a large dataset, thus reducing the cost of its analysis. To do this, it employs different techniques such as active learning, also know as optimal experimental design in the field of statistics. We also explore some innovative methods of identifying relevant anomalies from a large dataset to be subsequently explored. This dissertation studies the application of parsimonious sensing on three unique datasets. The first main experience studies the employment of active learning in an environmental sensing network system with air quality parameters. The second experience depicts an attempt to predict the number of hits for a certain query related to events happening in Singapore, thus decreasing the number of required queries. The third and last experiment makes use of a dataset provided by a major taxi company in Singapore and tries to identify traffic anomalies and later, synthesize queries that are run through a search engine in order to identify the context of the anomalies. We found the application of parsimonious sensing to be successful when implemented in the context of environmental sensing. We have further developed a system capable of identifying traffic anomalies and returning a number of links that can potentially explain why they happened. The fully automated system has been shown to be better than a hybrid system, composed of information retrieved both automatically and manually. The findings from this dissertation can hopefully shed some light on the possible applications of parsimonious sensing to diverse contexts.2015-09-29info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10316/35661http://hdl.handle.net/10316/35661TID:201537664engFrutuoso, Manuel Levi Lacerda Amaral Eirôinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-05-25T04:33:47Zoai:estudogeral.uc.pt:10316/35661Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:54:24.875914Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Parsimonious sensing with Active Learning: applications with context mining and environmental sensing
title Parsimonious sensing with Active Learning: applications with context mining and environmental sensing
spellingShingle Parsimonious sensing with Active Learning: applications with context mining and environmental sensing
Frutuoso, Manuel Levi Lacerda Amaral Eirô
Active Learning
Big Data
Context Sensing
Data Mining
Event Identification
Parsimonious Sensing
title_short Parsimonious sensing with Active Learning: applications with context mining and environmental sensing
title_full Parsimonious sensing with Active Learning: applications with context mining and environmental sensing
title_fullStr Parsimonious sensing with Active Learning: applications with context mining and environmental sensing
title_full_unstemmed Parsimonious sensing with Active Learning: applications with context mining and environmental sensing
title_sort Parsimonious sensing with Active Learning: applications with context mining and environmental sensing
author Frutuoso, Manuel Levi Lacerda Amaral Eirô
author_facet Frutuoso, Manuel Levi Lacerda Amaral Eirô
author_role author
dc.contributor.author.fl_str_mv Frutuoso, Manuel Levi Lacerda Amaral Eirô
dc.subject.por.fl_str_mv Active Learning
Big Data
Context Sensing
Data Mining
Event Identification
Parsimonious Sensing
topic Active Learning
Big Data
Context Sensing
Data Mining
Event Identification
Parsimonious Sensing
description Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra.
publishDate 2015
dc.date.none.fl_str_mv 2015-09-29
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/35661
http://hdl.handle.net/10316/35661
TID:201537664
url http://hdl.handle.net/10316/35661
identifier_str_mv TID:201537664
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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