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Dissertations / Theses on the topic 'MUSIC INFORMATION RETRIEVAL SYSTEMS'

Author: Grafiati

Published: 7 June 2025

Last updated: 16 July 2025

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1

Deng, Jie. "Emotion-based music retrieval and recommendation." HKBU Institutional Repository, 2014. https://repository.hkbu.edu.hk/etd_oa/82.

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The digital music industry has expanded dramatically during the past decades, which results in the generation of enormous amounts of music data. Along with the Internet, the growing volume of quantitative data about users (e.g., users’ behaviors and preferences) can be easily collected nowadays. All these factors have the potential to produce big data in the music industry. By utilizing big data analysis of music related data, music can be better semantically understood (e.g., genres and emotions), and the user’s high-level needs such as automatic recognition and annotation can be satisfied. F

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2

McEnnis, Daniel. "On-demand metadata extraction network (OMEN)." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99382.

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OMEN (On-demand Metadata Extraction Network) addresses a fundamental problem in Music Information Retrieval: the lack of universal access to a large dataset containing significant amounts of copyrighted music. This thesis proposes a solution to this problem that is accomplished by utilizing the large collections of digitized music available at many libraries. Using OMEN, libraries will be able to perform on-demand feature extraction on site, returning feature values to researchers instead of providing direct access to the recordings themselves. This avoids copyright difficulties, since the und

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Knopke, Ian. "Building a search engine for music and audio on the World Wide Web." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85177.

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The main contribution of this dissertation is a system for locating and indexing audio files on the World Wide Web. The idea behind this system is that the use of both web page and audio file analysis techniques can produce more relevant information for locating audio files on the web than is used in full-text search engines.<br>The most important part of this system is a web crawler that finds materials by following hyperlinks between web pages. The crawler is distributed and operates using multiple computers across a network, storing results to a database. There are two main component

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Lee, Kyogu. "A system for acoustic chord transcription and key extraction from audio using hidden Markov models trained on synthesized audio /." May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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5

Sanden, Christopher, and University of Lethbridge Faculty of Arts and Science. "An empirical evaluation of computational and perceptual multi-label genre classification on music / Christopher Sanden." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, c2010, 2010. http://hdl.handle.net/10133/2602.

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Automatic music genre classi cation is a high-level task in the eld of Music Information Retrieval (MIR). It refers to the process of automatically assigning genre labels to music for various tasks, including, but not limited to categorization, organization and browsing. This is a topic which has seen an increase in interest recently as one of the cornerstones of MIR. However, due to the subjective and ambiguous nature of music, traditional single-label classi cation is inadequate. In this thesis, we study multi-label music genre classi cation from perceptual and computational perspectives. F

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Fiebrink, Rebecca. "An exploration of feature selection as a tool for optimizing musical genre classification /." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99372.

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The computer classification of musical audio can form the basis for systems that allow new ways of interacting with digital music collections. Existing music classification systems suffer, however, from inaccuracy as well as poor scalability. Feature selection is a machine-learning tool that can potentially improve both accuracy and scalability of classification. Unfortunately, there is no consensus on which feature selection algorithms are most appropriate or on how to evaluate the effectiveness of feature selection. Based on relevant literature in music information retrieval (MIR) and machin

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Ferraro, Andrés. "Music recommender systems: taking into account the artists' perspective." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/672852.

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Music streaming platforms nowadays play an important role in music consumption and have a big influence on the musical taste of the listeners. Machine learning-based recommender systems are a fundamental part of such streaming platforms defining what music people listen to and when. As for many applications of machine learning, there is an increasing debate in academia, industry and governments about the effects that the recommender systems have in society and the ethical implications of such systems. The bias in music recommender systems towards the more popular items has been studied ex

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Kaufman, Jaime C. "A Hybrid Approach to Music Recommendation: Exploiting Collaborative Music Tags and Acoustic Features." UNF Digital Commons, 2014. http://digitalcommons.unf.edu/etd/540.

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Recommendation systems make it easier for an individual to navigate through large datasets by recommending information relevant to the user. Companies such as Facebook, LinkedIn, Twitter, Netflix, Amazon, Pandora, and others utilize these types of systems in order to increase revenue by providing personalized recommendations. Recommendation systems generally use one of the two techniques: collaborative filtering (i.e., collective intelligence) and content-based filtering. Systems using collaborative filtering recommend items based on a community of users, their preferences, and their browsing

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9

Celma, Herrada Òscar. "Music recommendation and discovery in the long tail." Doctoral thesis, Universitat Pompeu Fabra, 2009. http://hdl.handle.net/10803/7557.

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Avui en dia, la música està esbiaixada cap al consum d'alguns artistes molt populars. Per exemple, el 2007 només l'1% de totes les cançons en format digital va representar el 80% de les vendes. De la mateixa manera, només 1.000 àlbums varen representar el 50% de totes les vendes, i el 80% de tots els àlbums venuts es varen comprar menys de 100 vegades. Es clar que hi ha una necessitat per tal d'ajudar a les persones a filtrar, descobrir, personalitzar i recomanar música, a partir de l'enorme quantitat de contingut musical disponible. <br/>Els algorismes de recomanació de música actuals intent

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Senturk, Sertan. "Computational modeling of improvisation in Turkish folk music using Variable-Length Markov Models." Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42761.

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The thesis describes a new database of uzun havas, a non-metered structured improvisation form in Turkish folk music, and a system, which uses Variable-Length Markov Models (VLMMs) to predict the melody in the uzun hava form. The database consists of 77 songs, encompassing 10849 notes, and it is used to train multiple viewpoints, where each event in a musical sequence are represented by parallel descriptors such as Durations and Notes. The thesis also introduces pitch-related viewpoints that are specifically aimed to model the unique melodic properties of makam music. The predictability of the

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Oramas, Martín Sergio. "Knowledge extraction and representation learning for music recommendation and classification." Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/457709.

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In this thesis, we address the problems of classifying and recommending music present in large collections. We focus on the semantic enrichment of descriptions associated to musical items (e.g., artists biographies, album reviews, metadata), and the exploitation of multimodal data (e.g., text, audio, images). To this end, we first focus on the problem of linking music-related texts with online knowledge repositories and on the automated construction of music knowledge bases. Then, we show how modeling semantic information may impact musicological studies and helps to outperform purely text-bas

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Eriksson, Madeleine. "Att sjunga en fråga. En jämförelse av tre Query-by-Humming-system och deras användare." Thesis, Högskolan i Borås, Institutionen Biblioteks- och informationsvetenskap / Bibliotekshögskolan, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-16635.

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The aim of this study was to compare the Query-by-Humming systems Midomi, Musicline and Tunebot regarding their retrieval effectiveness. The aim was to see if there were differences between the systems but also between the user groups common users, musicians and singers. Query-by-Humming system means that the user sings a tune that the system then use to find the right melody.To compare the systems and their users, queries where collected from the different user groups and replayed for the systems. Mean Reciprocal Rank and Friedman test was used to do the comparison.The results showed that the

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Berglund, Fredrik. "Chatbots as Interaction Modality : An Explorative Design Study on Elderly Classical Music Concert Subscribers." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209685.

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This thesis is a pilot study aimed at exploring how a chatbot can be designed to be used as a tool to give elderly classical music concert subscribers information about concerts they are attending. Previous works have indicated chatbots to be useful as information retrieval systems. To test this theory, a chatbot called “BerwaldBoten” was created and tested on eight elderly concert subscribers. Apart from testing the chatbot in everyday settings during a week leading up to a concert, the users also answered questionnaires before and after the study for qualitative data. Data from the chats was

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Bonzi, Francesco. "Lyrics Instrumentalness: An Automatic System for Vocal and Instrumental Recognition in Polyphonic Music with Deep Learning." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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Human voice recognition is a crucial task in music information retrieval. In this master thesis we developed an innovative AI system, called Instrumental- ness, to address the instrumental song tagging. An extended pipeline was proposed to fit the Instrumentalness require- ments, w.r.t. the well known tasks of Singing Voice Detection and Singing Voice Segmentation. A deep research on the available datasets was made and two different approaches were tried. The first one involves strongly labeled datasets and tested different neural architectures, while the second one used an attention mechanis

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CHAOUCH, CHAKIB. "Cyber-physical systems in the framework of audio song recognition and reliability engineering." Doctoral thesis, Chakib Chaouch, 2021. http://hdl.handle.net/11570/3210939.

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Music Information Retrieval (MIR) is the interdisciplinary discipline of extracting information from music, and it is the topic of our research. The MIR system faces a significant issue in dealing with various genres of music. Music retrieval aims at helping end-users search and finds a desired piece of music from an extensive database. In other words, Music Information retrieval tries to make music information more accessible to listeners, musicians, and data scientists. The challenges and research problems that an audio recognition system faces in everyday use might come in a variety of form

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Lisena, Pasquale. "Knowledge-based music recommendation : models, algorithms and exploratory search." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS614.

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Représenter l'information décrivant la musique est une activité complexe, qui implique différentes sous-tâches. Ce manuscrit de thèse porte principalement sur la musique classique et étudie comment représenter et exploiter ses informations. L'objectif principal est l'étude de stratégies de représentation et de découverte des connaissances appliquées à la musique classique, dans des domaines tels que la production de base de connaissances, la prédiction de métadonnées et les systèmes de recommandation. Nous proposons une architecture pour la gestion des métadonnées de musique à l'aide des techn

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Monteiro, Adriano Claro 1984. "Criação e performance musical no contexto dos instrumentos musicais digitais." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/284418.

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Orientador: Jônatas Manzolli<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Artes<br>Made available in DSpace on 2018-08-20T07:47:37Z (GMT). No. of bitstreams: 1 Monteiro_AdrianoClaro_M.pdf: 4807040 bytes, checksum: 3fdb8b9f91d66c6551c1e540e753d2ef (MD5) Previous issue date: 2012<br>Resumo: Este trabalho apresenta um estudo sobre o computador como instrumento de performance musical. A partir deste estudo desenvolvemos processos de criação musical com base na representação algorítmica e no código computacional. Os dois principais recursos técnicos que utilizamos e

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18

Koenders, Michael. "FROM MUSIC INFORMATION RETRIEVAL (MIR) TO INFORMATION RETRIEVAL FOR MUSIC (IRM)." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/16914.

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This thesis reviews and discusses certain techniques from the domain of (Music) Information Retrieval, in particular some general data mining algorithms. It also describes their specific adaptations for use as building blocks in the CACE4 software application. The use of Augmented Transition Networks (ATN) from the field of (Music) Information Retrieval is, to a certain extent, adequate as long as one keeps the underlying tonal constraints and rules as a guide to understanding the structure one is looking for. However since a large proportion of algorithmic music, including music composed by t

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Bahceci, Oktay. "Deep Neural Networks for Context Aware Personalized Music Recommendation : A Vector of Curation." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210252.

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Information Filtering and Recommender Systems have been used and has been implemented in various ways from various entities since the dawn of the Internet, and state-of-the-art approaches rely on Machine Learning and Deep Learning in order to create accurate and personalized recommendations for users in a given context. These models require big amounts of data with a variety of features such as time, location and user data in order to find correlations and patterns that other classical models such as matrix factorization and collaborative filtering cannot. This thesis researches, implements an

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Bogdanov, Dmitry. "From music similarity to music recommendation : computational approaches based on audio features and metadata." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/123776.

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Aquest treball es centra en el modelatge d'usuari per la recomanació musical i desenvolupa algoritmes per la comprensió automàtica i visualització de preferències musicals. Primer, es proposa un model d'usuari construït a partir d'un conjunt de peces musicals. En segon lloc, s'estudien mètodes d’estimació de similitud musical, treballant exclusivament en el contingut d'àudio. Es proposen noves mètriques basades en la informació tímbrica, temporal, tonal i semàntica. En tercer lloc, es proposen diversos mètodes de recomanació musical que utilitzen aquestes mètriques i que milloren amb un filtr

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Sandrock, Trudie. "Multi-label feature selection with application to musical instrument recognition." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019/11071.

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Thesis (PhD)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: An area of data mining and statistics that is currently receiving considerable attention is the field of multi-label learning. Problems in this field are concerned with scenarios where each data case can be associated with a set of labels instead of only one. In this thesis, we review the field of multi-label learning and discuss the lack of suitable benchmark data available for evaluating multi-label algorithms. We propose a technique for simulating multi-label data, which allows good control over different data characteristics

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Herrera, Boyer Perfecto. "MIRages: an account of music audio extractors, semantic description and context-awareness, in the three ages of MIR." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/666953.

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This tesis reports on research carried out and published during the last twenty years on different problems of Music Information Retrieval (MIR). We organize the text as a personal account and critical reflection along four hypothesized ages that have shaped the evolution of MIR. In the age of feature extractors, we present work on features to describe sounds and music, especially timbre and tonal aspects. In the age of semantic descriptors work on describing music with high-level concepts, such as mood, instruments, similarities, cover versions or genres, usually inferred with machine learnin

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Shao, Bo. "User-centric Music Information Retrieval." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/416.

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The rapid growth of the Internet and the advancements of the Web technologies have made it possible for users to have access to large amounts of on-line music data, including music acoustic signals, lyrics, style/mood labels, and user-assigned tags. The progress has made music listening more fun, but has raised an issue of how to organize this data, and more generally, how computer programs can assist users in their music experience. An important subject in computer-aided music listening is music retrieval, i.e., the issue of efficiently helping users in locating the music they are looking for

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Zapata, González José Ricardo. "Comparative evaluation and combination of automatic rhythm description systems." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/123822.

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The automatic analysis of musical rhythm from audio, and more specifically tempo and beat tracking, is one of the fundamental open research problems in Music Information Retrieval (MIR) research. Automatic beat tracking is a valuable tool for the solution of other MIR problems, as it enables beat- synchronous analysis of different music tasks. Even though automatic rhythm description is a relatively mature research topic in MIR tempo estimation and beat tracking remain an unsolved problem. We describe a new method for the extraction of beat times with a confidence value from music audio, b

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Boland, Daniel. "Engaging with music retrieval." Thesis, University of Glasgow, 2015. http://theses.gla.ac.uk/6727/.

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Music collections available to listeners have grown at a dramatic pace, now spanning tens of millions of tracks. Interacting with a music retrieval system can thus be overwhelming, with users offered ‘too-much-choice’. The level of engagement required for such retrieval interactions can be inappropriate, such as in mobile or multitasking contexts. Music recommender systems are widely employed to address this issue, however tend toward the opposite extreme of disempowering users and suffer from issues of subjectivity and confounds, such as the equalisation of tracks. This challenge and the styl

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Page, Stephen Dowland. "Computer tools for music information retrieval." Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.293399.

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Pérez-Sancho, Carlos. "Stochastic language models for music information retrieval." Doctoral thesis, Universidad de Alicante, 2009. http://hdl.handle.net/10045/14217.

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Romano, Nicholas C., Dmitri G. Roussinov, Jay F. Nunamaker, and Hsinchun Chen. "Collaborative Information Retrieval Environment: Integration of Information Retrieval with Group Support Systems." HICSS, 1999. http://hdl.handle.net/10150/105688.

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Artificial Intelligence Lab, Department of MIS, University of Arizona<br>Observations of Information Retrieval (IR) system user experiences reveal a strong desire for collaborative search while at the same time suggesting that collaborative capabilities are rarely, and then only in a limited fashion, supported by current searching and visualization tools. Equally interesting is the fact that observations of user experiences with Group Support Systems (GSS) reveal that although access to external information and the ability to search for relevant material is often vital to the progress

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Al-Maskari, Azzah. "Evaluation of interactive information retrieval systems." Thesis, University of Sheffield, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538079.

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Pearce, Alastair T. P. "MAP : a computer program for music information retrieval." Thesis, King's College London (University of London), 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264938.

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Martinek, Václav. "Rozpoznávání hudebních coververzí pomocí technik Music Information Retrieval." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442587.

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This master’s thesis deals with designs and implementation of systems for music cover recognition. The introduction part is devoted to the calculation parameters from audio signal using Music Information Retrieval techniques. Subsequently, various forms of cover versions and musical aspects that cover versions share are defined. The thesis also deals in detail with the creation and distribution of a database of cover versions. Furthermore, the work presents methods and techniques for comparing and processing the calculated parameters. Attention is then paid to the OTI method, CSM calculation a

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Mills, Timothy J. "Content modelling in multimedia information retrieval systems : the Cobra retrieval system." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.442405.

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Liu, Chi-Cheng. "Implementation of parallel intelligent information retrieval systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq30509.pdf.

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Revutska, H. I., and V. L. Malinkina. "Automated information retrieval systems to the internet." Thesis, КНУТД, 2016. https://er.knutd.edu.ua/handle/123456789/5039.

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Agbele, Kehinde Kayode. "Context-awareness for adaptive information retrieval systems." Thesis, University of the Western Cape, 2014. http://hdl.handle.net/11394/3845.

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Philosophiae Doctor - PhD<br>This research study investigates optimization of IRS to individual information needs in order of relevance. The research addressed development of algorithms that optimize the ranking of documents retrieved from IRS. In this thesis, we present two aspects of context-awareness in IR. Firstly, the design of context of information. The context of a query determines retrieved information relevance. Thus, executing the same query in diverse contexts often leads to diverse result rankings. Secondly, the relevant context aspects should be incorporated in a way that support

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Zemánková, Šárka. "Rozpoznávání hudebního žánru za pomoci technik Music Information Retrieval." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-401988.

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This diploma work deals with music genre recognition using the techniques of Music Information Retrieval. It contains a brief description of the principle of this research area and its subfield called Music Genre Recognition. The following chapter includes selection of the most suitable parameters for describing music genres. This work further characterizes machine learning methods used in this field of research. The next chapter deals with the descriptions of music datasets created for genre classification studies. Subsequently, there is a draft and evaluation of the system for music genre re

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Gómez, Luis Alfonso. "A two-level model for information retrieval systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/mq24469.pdf.

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Zhao, Dianguo. "Information retrieval in digital libraries : the systems aspect." Thesis, De Montfort University, 1997. http://hdl.handle.net/2086/4124.

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Gerber, Howard L. "Optimization information retrieval from disparate menu driven systems." Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/61052.

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Williams, Michael J. "Training Aviation Maintenance Technicians with Information Retrieval Systems." NSUWorks, 2000. http://nsuworks.nova.edu/gscis_etd/924.

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The goal of this dissertation has been to examine changes in computing technology skills possessed by aircraft maintenance technicians. The perspective of this project has been from that of a Federal Aviation Administration (FAA) approved Aviation Maintenance Technician School (AMTS). Specifically, the AMTS curriculum at Embry-Riddle Aeronautical University (ERAU) in Daytona Beach, Florida, provided participants for the study. Recommendations for integrating computing technology training into the AMTS curriculum at ERAU are being proposed for planned changes to the existing curriculum. With th

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Maleki-Dizaji, Saeedeh. "Evolutionary learning multi-agent based information retrieval systems." Thesis, Sheffield Hallam University, 2003. http://shura.shu.ac.uk/6856/.

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The volume and variety of information available on the Internet has experienced exponential growth, presenting a difficulty to users wishing to obtain information that accurately matches their interests. A number of factors affect the accuracy of matching user interests and the retrieved documents. First, is the fact that users often do not present queries to information retrieval systems in the form that optimally represents the information they want. Secondly, the measure of a document's relevance is highly subjective and variable between different users. This thesis addresses this problem w

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CATENA, MATTEO. "Energy efficiency in large scale information retrieval systems." Doctoral thesis, Gran Sasso Science Institute, 2017. http://hdl.handle.net/20.500.12571/9645.

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Web search engines are large scale information retrieval systems, which provide easy access to information on the Web. High performance query processing is fundamental for the success of such systems. In fact, web search engines can receive billions of queries per day. Additionally, the issuing users are often impatient and expect sub-second response times to their queries (e.g., 500 ms). For such reasons, search companies adopt distributed query processing strategies to cope with huge volumes of incoming queries and to provide sub-second response times. Web search engines perform distr

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Reed, Jeremy T. "Acoustic segment modeling and preference ranking for music information retrieval." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37189.

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This dissertation focuses on improving content-based recommendation systems for music. Specifically, progress in the development in music content-based recommendation systems has stalled in recent years due to some faulty assumptions: 1. most acoustic content-based systems for music information retrieval (MIR) assume a bag-of-frames model, where it is assumed that a song contains a simplistic, global audio texture 2. genre, style, mood, and authors are appropriate categories for machine-oriented recommendation 3. similarity is a universal construct and does not vary among different users The

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Hitland, Håkon Haugdal. "Using the Signature Quadratic Form Distance for Music Information Retrieval." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-14472.

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This thesis is an investigation into how the signature quadratic form distance can be used to search in music.Using the method used for images by Beecks, Uysal and Seidl as a starting point,I create feature signatures from sound clips by clustering features from their frequency representations.I compare three different feature types, based on Fourier coefficients, mel frequency cepstrum coefficients (MFCCs), and the chromatic scale.Two search applications are considered.First, an audio fingerprinting system, where a music file is located by a short recorded clip from the song.I run experiments

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Paradzinets, Aliaksandr V. "Variable resolution transform-based music feature extraction and their applications for music information retrieval." Ecully, Ecole centrale de Lyon, 2007. http://www.theses.fr/2007ECDL0047.

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Dans le secteur de loisirs il y a un nombre considérable d’enregistrements numériques musicaux produits, diffusés et échangés qui favorise la demande croisante de services intelligents de recherche de musique. La navigation par contenu devient cruciale pour permettre aux professionnels et également aux amateurs d’accéder facilement aux quantités de données musicales disponibles. Ce travail présente les nouveaux descripteurs de contenu musical et mesures de similarité qui permettent l’organisation automatique de données musicales (recherche par similarité, génération automatique des playlistes)

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RAMOS, Andryw Marques. "Explorando as relações entre os aspectos de novidades musicais e as preferências pelos ouvintes." Universidade Federal de Campina Grande, 2014. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/350.

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Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-04-09T19:37:26Z No. of bitstreams: 1 ANDRYW MARQUES RAMOS - DISSERTAÇÃO PPGCC 2014..pdf: 16053506 bytes, checksum: fdeece58c13c7b38ceb6c8b06f9d516b (MD5)<br>Made available in DSpace on 2018-04-09T19:37:26Z (GMT). No. of bitstreams: 1 ANDRYW MARQUES RAMOS - DISSERTAÇÃO PPGCC 2014..pdf: 16053506 bytes, checksum: fdeece58c13c7b38ceb6c8b06f9d516b (MD5) Previous issue date: 2014-09-05<br>Abuscapornovidadesmusicais,sejamelasmúsicas,álbunsouartistas,éumaspectocentral no hábito das pessoas quando se trata de música. E esta proc

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Bae, Soo Hyun. "Information retrieval via universal source coding." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26573.

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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Juang, Biing-Hwang; Committee Member: Al-Regib, Ghassan; Committee Member: Linda Wiils; Committee Member: Mersereau, Russell; Committee Member: Pappas, Thrasyvoulos. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Betts, M. P. "Coordinated information retrieval for building contractors' tendering." Thesis, London South Bank University, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.378209.

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Pollitt, A. S. "An expert systems approach to document retrieval." Thesis, University of Huddersfield, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.372852.

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Marinheiro, Rui Miguel Neto. "Using context to integrate hypermedia with information retrieval systems." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390725.

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