Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 26 for “"Learning to Rank"”.
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Empower learning-to-rank with language models
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-12-01
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Using Learning to Rank Approach to Promoting Diversity for Biomedical Information Retrieval with Wikipedia
… the information need of one query may refer to different aspects. Promoting diversity in IR takes the relationship between documents into account. Unlike previous studies, we tackle this problem in the learning to rank perspective. The main challenges are how to find salient features for …
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NeuroYara: Learning to Rank for Yara Rules Generation through Deep Language Modeling & Discriminative N-gram Encoding
… and efficient. One of the most ubiquitous tools is Yara. It is a widely-used syntax for writing malware signatures. Compared to machine learning models, Yara rules have a lower false-positive rate and better maintainability of the rules to incorporate new variants of malware. To …
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Community Question Answering : an Investigation into the Influence of Question Expansion based on User's Explicit Information on Learning to Rank Q&A Models
… NLP scientists and developers propose approaches to help questioners find answers to their questions based on previously submitted similar questions. However, community questions are short and require additional textual information for automatic matching with the relevant long answers. Explicit …
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ONet: Search, explore, and visualize hierarchical topic summarization on Twitter using network-OLAP
… and publicly available data sources for people to access today. It forms hierarchy naturally(e.g., people publish posts about different topics or share information from various countries. Given a topic such as technology, it many form sub-topics like mobile devices and web news. Similarly, given …
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Neural network architectures for Prepositional Phrase attachment disambiguation
… language sentences, a PP may often be attached to several possible candidates. While humans can usually identify the correct candidate successfully, syntactic parsers are known to have high error rated on this kind of construction. This work explores the use of compositional models of meaning in …
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Enhancing Fault Localization with Cost Awareness
… software life-cycle. The focus of the thesis is to improve the accuracy of existing fault localization (FL) techniques. We experimented with several source code line level features such as line commit size, line recency, and line length to arrive at a new fault localization technique. Based on …
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Improving Web Search Ranking Using the Internet Archive
… only based on the latest content of web pages stored in their indices despite the fact that many web resources update frequently. We explore possible techniques and data sources for improving web search result ranking using web page historical content change. We compare web pages with previous …
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Query Expansion Study for Clinical Decision Support
… have focused on applying information retrieval to medical data. However, despite the vast developments in medical information retrieval and accompanying technologies, the actual promise of this area remains unfulfilled due to properties of medical data and the huge volume of medical literature. …
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Reinforced co-learning for semi-supervised ranking
"Learning to rank is vital to information retrieval and recommendation systems. Directly optimizing the listwise evaluation measure such as normalized discounted cumulative gain (NDCG) is an advanced way to learn a ranking model. However, this is only suited for training data with effective labels. …
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Analysis of Human Face Shape Abnormalities Using Machine Learning
… research has been done using computer-based automatic methods to study 3D facial characteristics. This study focuses on face abnormality, especially, children with cleft lip and/or palate. Cleft lip is a birth defect that results in deformity of the upper lip and nose. Its severity is widely …
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Graph Representation Learning for Social Networks
… about millions of users worldwide. However, due to sparsity and complex structure, analyzing these networks is quite challenging and expensive. Recently, graph embedding emerged to map networked data into low-dimensional representations, i.e. vector embeddings. These representations are fed into …
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Cumulative Distribution Networks: Inference, Estimation and Applications of Graphical Models for Cumulative Distribution Functions
… properties of directed, undirected and factor graph models, but include the conditional independence properties of bidirected graphical models. As a result, CDNs are a parameterization for bidirected models that allows us to represent complex statistical dependence relationships between …
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Explanation mining
… analysis of explanations. Explanations are used to provide an understanding of a concept, procedure or reasoning to others. Although explanations are present online ubiquitously within textbooks, videos, blogposts, discussion forums, and many more, there is no way to mine them automatically. As a …
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Object search: supporting structured queries in web search engines
… requisite semantics through structured queries into databases populated by information extraction (IE) techniques are expensive and not easily adaptable to new domains. This paper describes a methodology for rapidly developing search engines capable of answering structured queries over …
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A framework for finding and summarizing product defects, and ranking helpful threads from online customer forums through machine learning
… forums provide interactive platforms for users to exchange information and report problems. With the rapid growth of social networks and an ever increasing number of Internet users, online forums have accumulated a huge amount of valuable user-generated data and have accordingly become a major …
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Example weighting for deep representation learning
… derivative magnitude function can be considered to provide a weighting scheme from the viewpoint of example weighting. Therefore, example weighting is universal in deep learning. Partially arising from the recent work on the risky memorisation behaviours of deep neural networks (Arpit et al., …
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Using language similarities in retrieval for resource scarce languages: a study of several southern Bantu languages
… published in languages that are not accessible to many potential users who are only able to read and understand their local languages. Many of these local languages are Resources Scarce Languages (RSLs) and lack the necessary resources, such as machine translation tools, to make available …
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Log-Driven Robust Anomaly Detection and Root Cause Localisation for Distributed Computing Systems
… during incident response, yet they are difficult to use at scale. Message wording changes across releases, timestamps are not always comparable across hosts, and identifiers for forming sessions are sometimes missing or inconsistently propagated. Event-level labels are also scarce. This thesis …
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