Searched for: subject%3A%22Information%255C%2BRetrieval%22
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Hacipoğlu, Sara (author)
The complexity of deep neural rankers and large datasets make it increasingly more challenging to understand why a document is predicted as relevant to a given query. A growing body of work focuses on interpreting ranking models with different explainable AI methods. Instance attribution methods aim to explain individual predictions of machine...
master thesis 2023
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ZHUANG, XUANYU (author)
In the task of music style transfer, the symbolic music representation based on Musical Instrument Digital Interface (MIDI) files has always been a popular research medium. By using such representation, some mature models for image style transfer can also be applied to this scenario, such as Cycle-consistent Generative Adversarial Networks ...
master thesis 2023
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Qiu, Ziang (author)
Recently, a few children-centered recommendation systems have been created and evaluated. How- ever, these systems required user interaction to cre- ate ground truth to evaluate the result. This research aims to compare some of the traditional recommen- dation models and explore which trait could impact the recommendation process most for...
bachelor thesis 2023
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Chaudhary, Shivam (author), Prasad Miyapuram, Krishna (author), Lomas, J.D. (author)
Entrainment is a phenomenon of phase or temporal matching of one system with that of another system. Human neural activity has been shown to resonate with external auditory stimuli. When we enjoy a piece of music, there is a resonance of brain responses with auditory signals. The crux of music cognition is based on this resonance of musical...
conference paper 2023
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Leonhardt, L.J.L. (author), Rudra, Koustav (author), Anand, A. (author)
Neural document ranking models perform impressively well due to superior language understanding gained from pre-Training tasks. However, due to their complexity and large number of parameters these (typically transformer-based) models are often non-interpretable in that ranking decisions can not be clearly attributed to specific parts of the...
journal article 2023
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Landoni, Monica (author), Murgia, Emiliana (author), Huibers, Theo (author), Pera, M.S. (author)
Informed by existing literature, in addition to lessons learned from ongoing research work pertaining to online information seeking, in this contribution, we discuss our view of how information pollution affects a critical yet understudied user group: children. We first highlight the need to take into account the unique characteristics of...
journal article 2023
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Anand, A. (author), Sen, Procheta (author), Saha, Sourav (author), Verma, Manisha (author), Mitra, Mandar (author)
This tutorial presents explainable information retrieval (ExIR), an emerging area focused on fostering responsible and trustworthy deployment of machine learning systems in the context of information retrieval. As the field has rapidly evolved in the past 4-5 years, numerous approaches have been proposed that focus on different access modes,...
conference paper 2023
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Theodorakopoulos, Dimitris (author)
In the field of Information Retrieval (IR), the reliable evaluation of systems is a key component in order to progress the state-of-the-art. Much of IR research focuses on optimizing the various aspects of evaluation. Stochastic simulation is one technique that can be used to assist this kind of research. It allows researchers to overcome...
master thesis 2022
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Visser, Maaike (author)
As the amount of information available in the world grows, Information Retrieval (IR) systems have become an integral part of day to day life. They determine what subset of the large pool of information is shown to people. IR algorithms determine which items should be returned in response to a query and rank the results in a ranked list.<br/...
master thesis 2022
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Salarian, Borna (author)
Working with trustworthy classifier models is important to the field of music information retrieval. However studies have shown some of the classifier models may not be as trustworthy as they appear. In this paper, we examine three of such classifiers available in the Essentia toolkit that have been evaluated using cross-validation, and measure...
bachelor thesis 2022
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Hulleman, Sjoerd (author)
Music Information Retrieval (MIR) is a field of research that focusses on extracting information from music related data. This includes the genre of music and the beats per minute (BPM) of a song. Pipelines that extract this information from music are called feature extractors. Essentia is a library for such feature extraction. Often, the audio...
bachelor thesis 2022
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Roy, N. (author), Maxwell, D.M. (author), Hauff, C. (author)
The Search Engine Results Page (SERP) has evolved significantly over the last two decades, moving away from the simple ten blue links paradigm to considerably more complex presentations that contain results from multiple verticals and granularities of textual information. Prior works have investigated how user interactions on the SERP are...
conference paper 2022
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Lan, Yunshi (author), He, G. (author), Jiang, Jinhao (author), Jiang, Jing (author), Xin Zhao, Wayne (author), Wen, Ji Rong (author)
Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Early studies mainly focused on answering simple questions over KBs and achieved great success. However, their performances on complex questions are still far from satisfactory. Therefore, in recent years, researchers propose a large number of novel...
journal article 2022
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Murgia, Emiliana (author), Landoni, Monica (author), Huibers, Theo (author), Pera, M.S. (author)
In this manuscript, we discuss the findings from an introductory survey conducted with more than 50 teachers in Italy. We inquired about teachers’ opinions of educational technology used in the classroom, in particular search tools. Qualitative and quantitative data inferred from collected responses provide us with a multifaceted picture of...
conference paper 2022
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Struharová, Natália (author)
Audio fingerprinting is one of the standard solutions for music identification. The underlying technique is designed to be robust to signal degradation such that music can be identified despite its presence. One of the newly emerged applications of a possibly challenging nature is music identification in movies. This paper examines the audio...
bachelor thesis 2021
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Wang, Yiran (author)
In order determine when we can show direct answer module to user queries in web search engine, an independent classifier is designed in this study to assess the answerability of each user query. Real user queries are sampled from MS MARCO Question Answering and Natural Langauge Generation dataset \cite{MSMARCO} and manually labelled with query...
bachelor thesis 2021
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Kim, Jaehun (author)
Machine learning (ML) has become a core technology for many real-world applications. Modern ML models are applied to unprecedentedly complex and difficult challenges, including very large and subjective problems. For instance, applications towards multimedia understanding have been advanced substantially. Here, it is already prevalent that...
doctoral thesis 2021
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Roy, N. (author), Câmara, Arthur (author), Maxwell, D.M. (author), Hauff, C. (author)
Models developed to simulate user interactions with search interfaces typically do not consider the visual layout and presentation of a Search Engine Results Page (SERP). In particular, the position and size of interfacewidgets ---such as entity cards and query suggestions---are usually considered a negligible constant. In contrast, in this work...
conference paper 2021
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Agres, Kat R. (author), Schaefer, Rebecca S. (author), Volk, Anja (author), van Hooren, Susan (author), Holzapfel, Andre (author), Dalla Bella, Simone (author), Müller, Meinard (author), de Witte, Martina (author), Neerincx, M.A. (author)
The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop “Music, Computing, and Health” was held to discuss best practices and state-of-the-art at the...
journal article 2021
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Hauff, C. (author), Kiseleva, Julia (author), Sanderson, Mark (author), Zamani, Hamed (author), Zhang, Yongfeng (author)
An introduction to the special issue on conversational search and recommendation is presented in this article. While conversational search and recommendation has roots in early Information Retrieval (IR) research, the recent advances in automatic voice recognition and conversational agents have created increasing interest in this area. In...
review 2021
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