546 research outputs found

    Genetic and molecular biomarkers of Alzheimer's disease

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    [eng] Alzheimer’s disease (AD) is the leading cause of dementia worldwide. Research in the past decade has led to major progress in understanding the genetic etiology of the disease; since I started my PhD (2019), nearly 20 genetic risk factors have been associated with late onset AD. Among them, the Ԑ4 allele of the APOE gene was the first identified, and remains the major genetic risk factor for AD. Despite extensive genetic research, a large part of the disease heritability remains elusive, the disease mechanisms incomprehensible, and targeted preventive interventions or pharmacological treatments for AD unavailable at the time. In this context, the overarching aim of the studies included in this thesis was to contribute to the knowledge of AD identifying new genetic risk factors and to better understand the role played by the APOE gene in the development of the disease. Such information would allow us to gain new insights into the molecular and biological mechanisms underlaying the disease and ultimately find new targets for treatment. This thesis provides evidence of the possible effectiveness of the use of a polygenic risk scores in a clinical setting for diagnosis of AD and actively improves the knowledge of the genetic factors associated with AD through genome-wide association studies

    Learning Possibilistic Logic Theories

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    Vi tar opp problemet med å lære tolkbare maskinlæringsmodeller fra usikker og manglende informasjon. Vi utvikler først en ny dyplæringsarkitektur, RIDDLE: Rule InDuction with Deep LEarning (regelinduksjon med dyp læring), basert på egenskapene til mulighetsteori. Med eksperimentelle resultater og sammenligning med FURIA, en eksisterende moderne metode for regelinduksjon, er RIDDLE en lovende regelinduksjonsalgoritme for å finne regler fra data. Deretter undersøker vi læringsoppgaven formelt ved å identifisere regler med konfidensgrad knyttet til dem i exact learning-modellen. Vi definerer formelt teoretiske rammer og viser forhold som må holde for å garantere at en læringsalgoritme vil identifisere reglene som holder i et domene. Til slutt utvikler vi en algoritme som lærer regler med tilhørende konfidensverdier i exact learning-modellen. Vi foreslår også en teknikk for å simulere spørringer i exact learning-modellen fra data. Eksperimenter viser oppmuntrende resultater for å lære et sett med regler som tilnærmer reglene som er kodet i data.We address the problem of learning interpretable machine learning models from uncertain and missing information. We first develop a novel deep learning architecture, named RIDDLE (Rule InDuction with Deep LEarning), based on properties of possibility theory. With experimental results and comparison with FURIA, a state of the art method, RIDDLE is a promising rule induction algorithm for finding rules from data. We then formally investigate the learning task of identifying rules with confidence degree associated to them in the exact learning model. We formally define theoretical frameworks and show conditions that must hold to guarantee that a learning algorithm will identify the rules that hold in a domain. Finally, we develop an algorithm that learns rules with associated confidence values in the exact learning model. We also propose a technique to simulate queries in the exact learning model from data. Experiments show encouraging results to learn a set of rules that approximate rules encoded in data.Doktorgradsavhandlin

    Methods for improving entity linking and exploiting social media messages across crises

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    Entity Linking (EL) is the task of automatically identifying entity mentions in texts and resolving them to a corresponding entity in a reference knowledge base (KB). There is a large number of tools available for different types of documents and domains, however the literature in entity linking has shown the quality of a tool varies across different corpus and depends on specific characteristics of the corpus it is applied to. Moreover the lack of precision on particularly ambiguous mentions often spoils the usefulness of automated disambiguation results in real world applications. In the first part of this thesis I explore an approximation of the difficulty to link entity mentions and frame it as a supervised classification task. Classifying difficult to disambiguate entity mentions can facilitate identifying critical cases as part of a semi-automated system, while detecting latent corpus characteristics that affect the entity linking performance. Moreover, despiteless the large number of entity linking tools that have been proposed throughout the past years, some tools work better on short mentions while others perform better when there is more contextual information. To this end, I proposed a solution by exploiting results from distinct entity linking tools on the same corpus by leveraging their individual strengths on a per-mention basis. The proposed solution demonstrated to be effective and outperformed the individual entity systems employed in a series of experiments. An important component in the majority of the entity linking tools is the probability that a mentions links to one entity in a reference knowledge base, and the computation of this probability is usually done over a static snapshot of a reference KB. However, an entity’s popularity is temporally sensitive and may change due to short term events. Moreover, these changes might be then reflected in a KB and EL tools can produce different results for a given mention at different times. I investigated the prior probability change over time and the overall disambiguation performance using different KB from different time periods. The second part of this thesis is mainly concerned with short texts. Social media has become an integral part of the modern society. Twitter, for instance, is one of the most popular social media platforms around the world that enables people to share their opinions and post short messages about any subject on a daily basis. At first I presented one approach to identifying informative messages during catastrophic events using deep learning techniques. By automatically detecting informative messages posted by users during major events, it can enable professionals involved in crisis management to better estimate damages with only relevant information posted on social media channels, as well as to act immediately. Moreover I have also performed an analysis study on Twitter messages posted during the Covid-19 pandemic. Initially I collected 4 million tweets posted in Portuguese since the begining of the pandemic and provided an analysis of the debate aroud the pandemic. I used topic modeling, sentiment analysis and hashtags recomendation techniques to provide isights around the online discussion of the Covid-19 pandemic

    Biaxial Nematic Order in Liver Tissue

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    Understanding how biological cells organize to form complex functional tissues is a question of key interest at the interface between biology and physics. The liver is a model system for a complex three-dimensional epithelial tissue, which performs many vital functions. Recent advances in imaging methods provide access to experimental data at the subcellular level. Structural details of individual cells in bulk tissues can be resolved, which prompts for new analysis methods. In this thesis, we use concepts from soft matter physics to elucidate and quantify structural properties of mouse liver tissue. Epithelial cells are structurally anisotropic and possess a distinct apico-basal cell polarity that can be characterized, in most cases, by a vector. For the parenchymal cells of the liver (hepatocytes), however, this is not possible. We therefore develop a general method to characterize the distribution of membrane-bound proteins in cells using a multipole decomposition. We first verify that simple epithelial cells of the kidney are of vectorial cell polarity type and then show that hepatocytes are of second order (nematic) cell polarity type. We propose a method to quantify orientational order in curved geometries and reveal lobule-level patterns of aligned cell polarity axes in the liver. These lobule-level patterns follow, on average, streamlines defined by the locations of larger vessels running through the tissue. We show that this characterizes the liver as a nematic liquid crystal with biaxial order. We use the quantification of orientational order to investigate the effect of specific knock-down of the adhesion protein Integrin ß-1. Building upon these observations, we study a model of nematic interactions. We find that interactions among neighboring cells alone cannot account for the observed ordering patterns. Instead, coupling to an external field yields cell polarity fields that closely resemble the experimental data. Furthermore, we analyze the structural properties of the two transport networks present in the liver (sinusoids and bile canaliculi) and identify a nematic alignment between the anisotropy of the sinusoid network and the nematic cell polarity of hepatocytes. We propose a minimal lattice-based model that captures essential characteristics of network organization in the liver by local rules. In conclusion, using data analysis and minimal theoretical models, we found that the liver constitutes an example of a living biaxial liquid crystal.:1. Introduction 1 1.1. From molecules to cells, tissues and organisms: multi-scale hierarchical organization in animals 1 1.2. The liver as a model system of complex three-dimensional tissue 2 1.3. Biology of tissues 5 1.4. Physics of tissues 9 1.4.1. Continuum descriptions 11 1.4.2. Discrete models 11 1.4.3. Two-dimensional case study: planar cell polarity in the fly wing 15 1.4.4. Challenges of three-dimensional models for liver tissue 16 1.5. Liquids, crystals and liquid crystals 16 1.5.1. The uniaxial nematic order parameter 19 1.5.2. The biaxial nematic ordering tensor 21 1.5.3. Continuum theory of nematic order 23 1.5.4. Smectic order 25 1.6. Three-dimensional imaging of liver tissue 26 1.7. Overview of the thesis 28 2. Characterizing cellular anisotropy 31 2.1. Classifying protein distributions on cell surfaces 31 2.1.1. Mode expansion to characterize distributions on the unit sphere 31 2.1.2. Vectorial and nematic classes of surface distributions 33 2.1.3. Cell polarity on non-spherical surfaces 34 2.2. Cell polarity in kidney and liver tissues 36 2.2.1. Kidney cells exhibit vectorial polarity 36 2.2.2. Hepatocytes exhibit nematic polarity 37 2.3. Local network anisotropy 40 2.4. Summary 41 3. Order parameters for tissue organization 43 3.1. Orientational order: quantifying biaxial phases 43 3.1.1. Biaxial nematic order parameters 45 3.1.2. Co-orientational order parameters 51 3.1.3. Invariants of moment tensors 52 3.1.4. Relation between these three schemes 53 3.1.5. Example: nematic coupling to an external field 55 3.2. A tissue-level reference field 59 3.3. Orientational order in inhomogeneous systems 62 3.4. Positional order: identifying signatures of smectic and columnar order 64 3.5. Summary 67 4. The liver lobule exhibits biaxial liquid-crystal order 69 4.1. Coarse-graining reveals nematic cell polarity patterns on the lobulelevel 69 4.2. Coarse-grained patterns match tissue-level reference field 73 4.3. Apical and basal nematic cell polarity are anti-correlated 74 4.4. Co-orientational order: nematic cell polarity is aligned with network anisotropy 76 4.5. RNAi knock-down perturbs orientational order in liver tissue 78 4.6. Signatures of smectic order in liver tissue 81 4.7. Summary 86 5. Effective models for cell and network polarity coordination 89 5.1. Discretization of a uniaxial nematic free energy 89 5.2. Discretization of a biaxial nematic free energy 91 5.3. Application to cell polarity organization in liver tissue 92 5.3.1. Spatial profile of orientational order in liver tissue 93 5.3.2. Orientational order from neighbor-interactions and boundary conditions 94 5.3.3. Orientational order from coupling to an external field 99 5.4. Biaxial interaction model 101 5.5. Summary 105 6. Network self-organization in a liver-inspired lattice model 107 6.1. Cubic lattice geometry motivated by liver tissue 107 6.2. Effective energy for local network segment interactions 110 6.3. Characterizing network structures in the cubic lattice geometry 113 6.4. Local interaction rules generate macroscopic network structures 115 6.5. Effect of mutual repulsion between unlike segment types on network structure 118 6.6. Summary 121 7. Discussion and Outlook 123 A. Appendix 127 A.1. Mean field theory fo the isotropic-uniaxial nematic transition 127 A.2. Distortions of the Mollweide projection 129 A.3. Shape parameters for basal membrane around hepatocytes 130 A.4. Randomized control for network segment anisotropies 130 A.5. The dihedral symmetry group D2h 131 A.6. Relation between orientational order parameters and elements of the super-tensor 134 A.7. Formal separation of molecular asymmetry and orientation 134 A.8. Order parameters under action of axes permutation 137 A.9. Minimal integrity basis for symmetric traceless tensors 139 A.10. Discretization of distortion free energy on cubic lattice 141 A.11. Metropolis Algorithm for uniaxial cell polarity coordination 142 A.12. States in the zero-noise limit of the nearest-neighbor interaction model 143 A.13. Metropolis Algorithm for network self-organization 144 A.14. Structural quantifications for varying values of mutual network segment repulsion 146 A.15. Structural quantifications for varying values of self-attraction of network segments 148 A.16. Structural quantifications for varying values of cell demand 150 Bibliography 152 Acknowledgements 17

    The Role of Materiality in the Emergence and Development of Ch'ŏnghŏ Hyujŏng's Lineage at Pohyŏnsa and Taedunsa

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    학위논문(박사) -- 서울대학교대학원 : 인문대학 고고미술사학과(미술사학전공), 2023. 2. 이주형.본 연구는 조선후기 (17-19세기)에 일어난 불교계의 변화, 그리고 이 변화와 연결된 불교 물질성의 역할을 고찰한다. 조선시대 후기의 대표적인 특징은 선종의 부흥과 법통설의 설립과 전개라고 말할 수 있다. 법통설은 선사(禪師)를 불교의 종교적 경험의 핵심적인 요소로 만들었다. 결과적으로 불교계에 새로운 지도층이 등장하면서 조선 불교의 성격은 전반적으로 변화되었다. 조선후기에 다양한 종류의 선사 관련 물질문화가 대량으로 생산되고 널리 유포되었다. 승탑, 탑비, 진영, 가사, 발우 등, 다양한 매체를 포함한 이 물질문화는 본래 한반도에 알려져 있었으나 조선후기 불교계의 변화와 함께 그의 상징적인 의미와 용도가 크게 바뀌었다. 새로운 불교의 패러다임의 설립과 전개에 선사 관련 물질문화는 근본적·적극적인 열할을 맡았다. 논문은 두 부분으로 나눠져 있다. 1부는 법통설의 설립과 전개과정에 집중한다. 법통설은 조선 후기 불교의 새로운 패러다임이 되고 한반도의 불교를 혁명적으로 변화시켰다. 17세기 초반에 묘향산 보현사의 교단에 의해 본격적으로 설립된 법통설 개념의 전개는 지적 작업이었으나 이 개념이 성공하기 위해 필수적인 요소 중 하나는 선사 관련 물질 문화였다. 이 물질문화는 상징성이 높고 누구나 직접적으로 접근하기가 쉽다. 선사를 불교의 핵심으로 삼는 법통설은 이러한 물질 문화의 힘 덕분에 성공적으로 확산할 수 있었다고 해도 과언이 아니다. 법통설을 설립한 교단은 이미 한반도에 현존하던 다양한 물질적 매체의 의미를 사용하고 변경했다. 선사 관련 물질성은 문헌으로 시작한 이론적인 개념한테 누구에게나 직접 경험할 수 있는 확실한 모양새를 주었다. 제1장에서는 법통설의 이론적인 면을 검토하고 제2장에서는 법통설을 탄생시키기에 선사 관련 물질문화는 어떤 역할을 가졌는지에 대해 고찰하고 그 역할의 범위를 탐색했다. 당시 선사 관련 물질문화의 생산과 그의 의미 확정을 선도한 이들은 교단의 리더가 된 승려들이었다는 사실을 밝히고나서 그들의 원래 목표에 집중하고 보현사 교단의 맥락에 나타난 결과를 연구했다. 1부에 연구되는 물질문화는 주로 선사의 사리 그리고 이와 관계 있는 대형 유물 (승탑, 비석)이었다는 점이 중요한 특징이다. 2부에는 해남 대흥사/대둔사가 소유하던 다양한 선사 관련 유물의 해석과 이 유물들과 연결된 여러 사건의 예를 통해 법통설의 전국적인 확산, 그리고 이 확산과 함께 일어난 선사 관련 물질문화의 개념적인 변화를 해석해 보고자 한다. 초기 법통설은 명확한 지역에 활동하던 교단의 확실한 리더십의 문제를 해결하기 위해 설립되었다. 그런데 그 힘은 상당했기 때문에 법통설을 구체화시킨 물질문화와 함께 조금씩 변경되면서 조선의 다른 지역과 각 지역의 교단에 상당한 속도로 확산되었다. 물질문화는 이 확산 과정에 상당한 역할을 맡았는데 동시에 선사 관련 물질문화의 의미는 각 지역과 종교적 상황에 맞춰서 새로운 의미를 가지게 되었다. 2부는 연구 범위의 문제로 인해 대둔사의 사례에만 집중하지만 비슷한 상황을 조선후기 동안 번창한 거의 모든 사찰에서 찾을 수 있다. 선사 관련 물질문화의 연구를 통해 조선후기 교단 구성원들의 자기 인식, 교단과 후원 추구의 문제, 불교자들과 물질성의 복잡한 관계, 사찰의 물질적 재산에 대한 승려의 인식 등 다양한 흥미로운 주제를 탐구할 수 있고, 불교사에 대해 보다 깊은 이해를 얻을 수 있다. 1부에 등장한 유물에 비해 2부에 등장하는 선사 관련 물질문화는 형식적으로나 성격적으로나 보다 다양하다는 것이 특징이다. 이 점은 선사 관련 물질문화 용도의 다양화를 반영한다.This dissertation explores the role of materiality in the development of Korean Buddhism during the Late Chosŏn period, between the seventeenth and the nineteenth centuries. The Buddhism of this period is characterized by the introduction of newly developed Dharma lineage narratives, which put the figure of the Sŏn master at the center of the contemporary religious experience. From this, a new leadership emerged, reshaping the whole Korean monastic community. A large amount of materiality connected to Sŏn masters was produced and circulated in the Late Chosŏn period. While most of the media forming this complex corpus (including stupas, funerary/hagiographic steles, portraits, monastic robes, alms bowls) were already known in the Korean peninsula in the previous historical periods, the new developments in Buddhism since the seventeenth century attributed to the materiality of Sŏn masters new meanings and functions. Crucially, this reinvented materiality had a fundamental, active role in the development and diffusion of the new Buddhist paradigm. This dissertation is divided in two sections, each one exploring the events at two of the key Buddhist sites of the Late Chosŏn period, Pohyŏnsa on Mount Myohyang, and Taedunsa (or Taehŭnsa, as it is currently known) on Mount Turyun. Part One thus focusses on the early phases of lineage narratives in connection with the community centered around master Chŏnghŏ Hyujŏng at the Pohyŏnsa monastery. Here, I argue that lineage narratives, and the related reinvention of Sŏn master materiality, were first implemented as tools to settle local issues of succession after Hyujŏng death. I first introduce the textual sources that contributed to the creation of lineage narratives and those that supported the affirmation of Sŏn masters as the central figure of Late Chosŏn Buddhism. I then attempt to demonstrate the role of materiality in the creation of these texts, as well as its practical implementation (especially through the construction of steles and stupas) in the processes of monastic succession and leadership assessment at Pohyŏnsa. In due time, I conclude, these tools proved so powerful and adaptable that the forms of Buddhism they promoted spread to all the regions of the country, transforming the nature of Korean Buddhism in its entirety. Part Two discusses the expansion and transformation of the new forms of Buddhism, focusing on the Sŏn master related material production of Taedunsa monastery through a series of interconnected case studies. In it, I attempt to demonstrate how the community of Taedunsa adopted and adapted the paradigms of the materiality of Sŏn masters discussed in Part One. Through the adoption of these new paradigms, Taedunsa, once a minor monastery, quickly rose to prominence to a national level. This was achieved through creative and manifold adaptations of Sŏn master materiality, which allowed the monastery to grow a solid and stable leading group, to negotiate its social and economic role on a par with the state and the Confucian community, and to maintain a lasting influence on the Buddhist community of the whole Chosŏn kingdom.INTRODUCTION 1 1. Relevance of the Materiality of Sŏn Masters in the Late Chosŏn Period 1 2. The Historical Context 5 3. Terminology and Methodological Approach 10 4. Previous Research 21 5. Structure of the Thesis 26 PART ONE 30 CHAPTER ONE - THE DEVELOPMENT OF LINEAGE NARRATIVE(S) IN LATE CHOSON BUDDHISM 31 1. Introduction 31 2. Lineage in Chinese Chan 35 3. The Korean Approach to Lineage before the Late Chosŏn Period 40 4. Lineage Narratives of the Late Chosŏn 51 4.1) Lineage Narratives in the Writings of Hyujŏng 51 4.2) Lineage Narratives Developed by Hyujŏngs Disciples 59 4.3) Textual Sources Connected with Lineage Narratives 67 a. Collections of Writings and Funerary Steles 68 b. Manuals for Funerary Rituals 84 c. Lineage Charts and Texts 91 d. Monastic Gazetteers 101 5. Conclusion 105 CHAPTER TWO – ISSUES OF LEGITIMACY IN HYUJŎNGS LINEAGE AND THE ROLE OF MATERIAL CULTURE IN ITS EARLY DEVELOPMENTS 109 1. Introduction 109 2. Hyujŏngs Community and the Centrality of Pohyŏnsa Monastery 115 3. Early Lineage Narratives in connection with the Materiality of Sŏn Masters 118 4. Ŏngis Steles at Pohyŏnsa and Paekhwaam 133 5. The Monk Stupas at Pohyŏnsa 139 6. Conclusion 155 PART TWO 158 CHAPTER THREE – THE MONK STUPAS AT TAEDUNSA: THE NATIONAL EXPANSION OF HYUJŎNGS LINEAGE NARRATIVE AND THE INFLUENCE OF MATERIALITY IN THE SELF CONSCIOUSNESS OF A MONASTERYS COMMUNITY 159 1. Introduction 159 2. The Stupa Group at Taedunsa 163 3. The History of Taedunsa and its Association with Hyujŏng 173 4. The Stupa Group at Taedunsa 182 5. Conclusion 198 CHAPTER FOUR – PYOCHUNGSA SHRINE AT TAEDUNSA: THE ROLE OF MATERIALITY IN ITS CREATION AND ITS LEGACY IN THE LATTER HISTORY OF THE MONASTERY 200 1. Introduction 200 2. Issues of Sponsorship in Korean Buddhist Art 205 3. Confucian Shrines in Late Chosŏn 210 4. The Intermingling of Confucian and Buddhist Ideals at Taedunsa 216 5. The Foundation of Pyochungsa Shrine at Taedunsa 219 6. Later Issues of Materiality connected to the Taedunsa Pyochungsa 229 7. Conclusion 235 CHAPTER FIVE – THE MATERIALITY OF SŎN MASTERS IN THE TAEDUNSAJI 237 1. Introduction 237 2. Overview of the Text 243 3. The Materiality of Sŏn Masters in Books One and Two 248 4. The Materiality of Sŏn Masters in Book Three 267 5. Conclusion 273 CONCLUSION 274 GLOSSARY 283 FREQUENTLY CITED MASTERS REFERENCE TABLE 290 BIBLIOGRAPHY 292 a. Primary Sources 292 b. Secondary sources in Asian languages 294 c. Secondary Sources in Western Languages 326 Tables 338 Figures 339 국문 초록 426 ACKNOWLEDGEMENTS 429박

    Associations of the 2018 World Cancer Research Fund/American Institute of Cancer Research (WCRF/AICR) cancer prevention recommendations with stages of colorectal carcinogenesis

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    Background: While adherence to cancer prevention recommendations is linked to lower risk of colorectal cancer (CRC), few have studied associations across the entire spectrum of colorectal carcinogenesis. Here, we studied the relationship of the standardized 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) Score for cancer prevention recommendations with detection of colorectal lesions in a screening setting. As a secondary objective, we examined to what extent the recommendations were being followed in an external cohort of CRC patients. Methods: Adherence to the seven-point 2018 WCRF/AICR Score was measured in screening participants receiving a positive fecal immunochemical test and in CRC patients participating in an intervention study. Dietary intake, body fatness and physical activity were assessed using self-administered questionnaires. Multinomial logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for screen-detected lesions. Results: Of 1486 screening participants, 548 were free from adenomas, 524 had non-advanced adenomas, 349 had advanced lesions and 65 had CRC. Adherence to the 2018 WCRF/AICR Score was inversely associated with advanced lesions; OR 0.82 (95% CI 0.71, 0.94) per score point, but not with CRC. Of the seven individual components included in the score, alcohol, and BMI seemed to be the most influential. Of the 430 CRC patients included in the external cohort, the greatest potential for lifestyle improvement was seen for the recommendations concerning alcohol and red and processed meat, where 10% and 2% fully adhered, respectively. Conclusions: Adherence to the 2018 WCRF/AICR Score was associated with lower probability of screen-detected advanced precancerous lesions, but not CRC. Although some components of the score seemed to be more influential than others (i.e., alcohol and BMI), taking a holistic approach to cancer prevention is likely the best way to prevent the occurrence of precancerous colorectal lesions

    Learning Logical Rules from Knowledge Graphs

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    Ph.D. (Integrated) ThesisExpressing and extracting regularities in multi-relational data, where data points are interrelated and heterogeneous, requires well-designed knowledge representation. Knowledge Graphs (KGs), as a graph-based representation of multi-relational data, have seen a rapidly growing presence in industry and academia, where many real-world applications and academic research are either enabled or augmented through the incorporation of KGs. However, due to the way KGs are constructed, they are inherently noisy and incomplete. In this thesis, we focus on developing logic-based graph reasoning systems that utilize logical rules to infer missing facts for the completion of KGs. Unlike most rule learners that primarily mine abstract rules that contain no constants, we are particularly interested in learning instantiated rules that contain constants due to their ability to represent meaningful patterns and correlations that can not be expressed by abstract rules. The inclusion of instantiated rules often leads to exponential growth in the search space. Therefore, it is necessary to develop optimization strategies to balance between scalability and expressivity. To such an end, we propose GPFL, a probabilistic rule learning system optimized to mine instantiated rules through the implementation of a novel two-stage rule generation mechanism. Through experiments, we demonstrate that GPFL not only performs competitively on knowledge graph completion but is also much more efficient then existing methods at mining instantiated rules. With GPFL, we also reveal overfitting instantiated rules and provide detailed analyses about their impact on system performance. Then, we propose RHF, a generic framework for constructing rule hierarchies from a given set of rules. We demonstrate through experiments that with RHF and the hierarchical pruning techniques enabled by it, significant reductions in runtime and rule size are observed due to the pruning of unpromising rules. Eventually, to test the practicability of rule learning systems, we develop Ranta, a novel drug repurposing system that relies on logical rules as features to make interpretable inferences. Ranta outperforms existing methods by a large margin in predictive performance and can make reasonable repurposing suggestions with interpretable evidence
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