Knowledge extraction from fictional texts

Knowledge extraction from text is a key task in natural language processing, which involves many sub-tasks, such as taxonomy induction, named entity recognition and typing, relation extraction, knowledge canonicalization and so on. By constructing structured knowledge from natural language text, knowledge extraction becomes a key asset for search engines, question answering and other downstream applications. However, current knowledge extraction methods mostly focus on prominent real-world entities with Wikipedia and mainstream news articles as sources. The constructed knowledge bases, therefore, lack information about long-tail domains, with fiction and fantasy as archetypes. Fiction and fantasy are core parts of our human culture, spanning from literature to movies, TV series, comics and video games. With thousands of fictional universes which have been created, knowledge from fictional domains are subject of search-engine queries - by fans as well as cultural analysts. Unlike the real-world domain, knowledge extraction on such specific domains like fiction and fantasy has to tackle several key challenges: - Training data: Sources for fictional domains mostly come from books and fan-built content, which is sparse and noisy, and contains difficult structures of texts, such as dialogues and quotes. Training data for key tasks such as taxonomy induction, named entity typing or relation extraction are also not available. - Domain characteristics and diversity: Fictional universes can be highly sophisticated, containing entities, social structures and sometimes languages that are completely different from the real world. State-of-the-art methods for knowledge extraction make assumptions on entity-class, subclass and entity-entity relations that are often invalid for fictional domains. With different genres of fictional domains, another requirement is to transfer models across domains. - Long fictional texts: While state-of-the-art models have limitations on the input sequence length, it is essential to develop methods that are able to deal with very long texts (e.g. entire books), to capture multiple contexts and leverage widely spread cues. This dissertation addresses the above challenges, by developing new methodologies that advance the state of the art on knowledge extraction in fictional domains. - The first contribution is a method, called TiFi, for constructing type systems (taxonomy induction) for fictional domains. By tapping noisy fan-built content from online communities such as Wikia, TiFi induces taxonomies through three main steps: category cleaning, edge cleaning and top-level construction. Exploiting a variety of features from the original input, TiFi is able to construct taxonomies for a diverse range of fictional domains with high precision. - The second contribution is a comprehensive approach, called ENTYFI, for named entity recognition and typing in long fictional texts. Built on 205 automatically induced high-quality type systems for popular fictional domains, ENTYFI exploits the overlap and reuse of these fictional domains on unseen texts. By combining different typing modules with a consolidation stage, ENTYFI is able to do fine-grained entity typing in long fictional texts with high precision and recall. - The third contribution is an end-to-end system, called KnowFi, for extracting relations between entities in very long texts such as entire books. KnowFi leverages background knowledge from 142 popular fictional domains to identify interesting relations and to collect distant training samples. KnowFi devises a similarity-based ranking technique to reduce false positives in training samples and to select potential text passages that contain seed pairs of entities. By training a hierarchical neural network for all relations, KnowFi is able to infer relations between entity pairs across long fictional texts, and achieves gains over the best prior methods for relation extraction.Wissensextraktion ist ein Schlüsselaufgabe bei der Verarbeitung natürlicher Sprache, und umfasst viele Unteraufgaben, wie Taxonomiekonstruktion, Entitätserkennung und Typisierung, Relationsextraktion, Wissenskanonikalisierung, etc. Durch den Aufbau von strukturiertem Wissen (z.B. Wissensdatenbanken) aus Texten wird die Wissensextraktion zu einem Schlüsselfaktor für Suchmaschinen, Question Answering und andere Anwendungen. Aktuelle Methoden zur Wissensextraktion konzentrieren sich jedoch hauptsächlich auf den Bereich der realen Welt, wobei Wikipedia und Mainstream- Nachrichtenartikel die Hauptquellen sind. Fiktion und Fantasy sind Kernbestandteile unserer menschlichen Kultur, die sich von Literatur bis zu Filmen, Fernsehserien, Comics und Videospielen erstreckt. Für Tausende von fiktiven Universen wird Wissen aus Suchmaschinen abgefragt – von Fans ebenso wie von Kulturwissenschaftler. Im Gegensatz zur realen Welt muss die Wissensextraktion in solchen spezifischen Domänen wie Belletristik und Fantasy mehrere zentrale Herausforderungen bewältigen: • Trainingsdaten. Quellen für fiktive Domänen stammen hauptsächlich aus Büchern und von Fans erstellten Inhalten, die spärlich und fehlerbehaftet sind und schwierige Textstrukturen wie Dialoge und Zitate enthalten. Trainingsdaten für Schlüsselaufgaben wie Taxonomie-Induktion, Named Entity Typing oder Relation Extraction sind ebenfalls nicht verfügbar. • Domain-Eigenschaften und Diversität. Fiktive Universen können sehr anspruchsvoll sein und Entitäten, soziale Strukturen und manchmal auch Sprachen enthalten, die sich von der realen Welt völlig unterscheiden. Moderne Methoden zur Wissensextraktion machen Annahmen über Entity-Class-, Entity-Subclass- und Entity- Entity-Relationen, die für fiktive Domänen oft ungültig sind. Bei verschiedenen Genres fiktiver Domänen müssen Modelle auch über fiktive Domänen hinweg transferierbar sein. • Lange fiktive Texte. Während moderne Modelle Einschränkungen hinsichtlich der Länge der Eingabesequenz haben, ist es wichtig, Methoden zu entwickeln, die in der Lage sind, mit sehr langen Texten (z.B. ganzen Büchern) umzugehen, und mehrere Kontexte und verteilte Hinweise zu erfassen. Diese Dissertation befasst sich mit den oben genannten Herausforderungen, und entwickelt Methoden, die den Stand der Kunst zur Wissensextraktion in fiktionalen Domänen voranbringen. • Der erste Beitrag ist eine Methode, genannt TiFi, zur Konstruktion von Typsystemen (Taxonomie induktion) für fiktive Domänen. Aus von Fans erstellten Inhalten in Online-Communities wie Wikia induziert TiFi Taxonomien in drei wesentlichen Schritten: Kategoriereinigung, Kantenreinigung und Top-Level- Konstruktion. TiFi nutzt eine Vielzahl von Informationen aus den ursprünglichen Quellen und ist in der Lage, Taxonomien für eine Vielzahl von fiktiven Domänen mit hoher Präzision zu erstellen. • Der zweite Beitrag ist ein umfassender Ansatz, genannt ENTYFI, zur Erkennung von Entitäten, und deren Typen, in langen fiktiven Texten. Aufbauend auf 205 automatisch induzierten hochwertigen Typsystemen für populäre fiktive Domänen nutzt ENTYFI die Überlappung und Wiederverwendung dieser fiktiven Domänen zur Bearbeitung neuer Texte. Durch die Zusammenstellung verschiedener Typisierungsmodule mit einer Konsolidierungsphase ist ENTYFI in der Lage, in langen fiktionalen Texten eine feinkörnige Entitätstypisierung mit hoher Präzision und Abdeckung durchzuführen. • Der dritte Beitrag ist ein End-to-End-System, genannt KnowFi, um Relationen zwischen Entitäten aus sehr langen Texten wie ganzen Büchern zu extrahieren. KnowFi nutzt Hintergrundwissen aus 142 beliebten fiktiven Domänen, um interessante Beziehungen zu identifizieren und Trainingsdaten zu sammeln. KnowFi umfasst eine ähnlichkeitsbasierte Ranking-Technik, um falsch positive Einträge in Trainingsdaten zu reduzieren und potenzielle Textpassagen auszuwählen, die Paare von Kandidats-Entitäten enthalten. Durch das Trainieren eines hierarchischen neuronalen Netzwerkes für alle Relationen ist KnowFi in der Lage, Relationen zwischen Entitätspaaren aus langen fiktiven Texten abzuleiten, und übertrifft die besten früheren Methoden zur Relationsextraktion

Diffusiophoresis of a Nonuniformly Charged Sphere in an Electrolyte Solution

[[abstract]]The diffusiophoresis of a rigid, nonuniformly charged spherical particle in an electrolyte solution is analyzed theoretically focusing on the influences of the thickness of double layer, the surface charge distribution, the effect of electrophoresis, and the effect of double-layer polarization. We show that the nonuniform charge distribution on the particle surface yields complicated effect of double-layer polarization, leading to interesting diffusiophoretic behaviors. For example, if the sign of the middle part of the particle is different from that of its left- and right-hand parts, then depending upon the charge density and the fraction of the middle part, the particle can move either to the high-concentration side or to the low-concentration side. Both the diffusiophoretic velocity and its direction can be manipulated by the distribution of the surface charge density. In particular, if the electrophoresis effect is significant, then those properties are governed by the averaged surface charge density of the particle. A dipolelike particle, where its left- (right-) hand half is negatively (positively) charged, always migrates toward the low-concentration (left-hand) side, that is, it has a negative diffusiophoretic velocity. In addition, that diffusiophoretic velocity has a negative local minimum as the thickness of double layer varies.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙

Stabilization for equal-order polygonal finite element method for high fluid velocity and pressure gradient

This paper presents an adapted stabilisation method for the equal-order mixed scheme of finite elements on convex polygonal meshes to analyse the high velocity and pressure gradient of incompressible fluid flows that are governed by Stokes equations system. This technique is constructed by a local pressure projection which is extremely simple, yet effective, to eliminate the poor or even non-convergence as well as the instability of equal-order mixed polygonal technique. In this research, some numerical examples of incompressible Stokes fluid flow that is coded and programmed by MATLAB will be presented to examine the effectiveness of the proposed stabilised method

An FPGA-based Convolution IP Core for Deep Neural Networks Acceleration

The development of machine learning has made a revolution in various applications such as object detection, image/video recognition, and semantic segmentation. Neural networks, a class of machine learning, play a crucial role in this process because of their remarkable improvement over traditional algorithms. However, neural networks are now going deeper and cost a significant amount of computation operations. Therefore they usually work ineffectively in edge devices that have limited resources and low performance. In this paper, we research a solution to accelerate the neural network inference phase using FPGA-based platforms. We analyze neural network models, their mathematical operations, and the inference phase in various platforms. We also profile the characteristics that affect the performance of neural network inference. Based on the analysis, we propose an architecture to accelerate the convolution operation used in most neural networks and takes up most of the computations in networks in terms of parallelism, data reuse, and memory management. We conduct different experiments to validate the FPGA-based convolution core architecture as well as to compare performance. Experimental results show that the core is platform-independent. The core outperforms a quad-core ARM processor functioning at 1.2 GHz and a 6-core Intel CPU with speed-ups of up to 15.69× and 2.78×, respectivel

BASIC CHARACTERISTICS IN THE TRADITIONAL CULTURE OF ETHNIC MINORITIES IN THE CENTRAL HIGHLANDS – THE CASE STUDY OF THE BA NA ETHNIC GROUP, KON TUM PROVINCE, VIETNAM

Kon Tum is not only a countryside with many revolutionary traditions but also a land of multi-ethnic cultural identities with 28 ethnic groups living together, in which ethnic minorities account for over 53% with 7 ethnic groups in the locality, including Xo Dang, Ba Na, Gia Rai, Gie Trieng, Brau, Ro Mam, Hre (Hre) [2, p.1]. Each ethnic group has its own traditional cultural identity, which has been handed down through generations. Cultural values such as language, writing, festivals, architecture, traditional costumes, etc. create the unique value of each community, are the link that connects each individual in the community, and also are the door to exchange, develop and integrate with other communities. Ba Na ethnic culture is an important component in the rich Kon Tum culture, imbued with national identity. Through the process of researching and surveying the opinions of artisans, village elders and experts on the Ba Na ethnic group in Kon Tum province, we found that the culture of ethnic minorities in the Central Highlands in general and Ba Na ethnic group in Kon Tum province has the basic characteristics of forest culture, upland farming culture, and gong culture. Those characteristics have created the unique and the charming in their traditional culture. Article visualizations

A study on the effects of plasma spraying parameters on the adhesion strength of Cr3C2-NiCr coating on 16Mn steel

This paper experimentally studied the adhesion strength of Cr3C2-30 %NiCr coating created on 16Mn steel substrate by plasma thermal coating technique in relation to spraying parameters. Experiments were carried out according to the central composite design (CCD) experimental matrix with three parameters: current intensity, powder feeding rate, and spray distance. Samples consisting of an annular disc and a latch made of 16Mn were fabricated according to the JIS H8664-1977 standard. Cr3C2-30 %NiCr coating was then created on the top surface of the disc including end of the latch. Adhesion strength of the coating to the substrate was measured through the tensile test. ANOVA analysis of variance was performed to evaluate the influence of the spraying parameters on adhesion strength and to build an empirical regression function representing the relationship between those parameters and the adhesion. Optimization problem was solved by ANOVA method and genetic algorithm (GA) to determine the value of the spraying parameters at which the coating has the greatest adhesion strength to the substrate. The results showed that the spraying parameters greatly affected the adhesion of the Cr3C2-30 %NiCr coating to the 16Mn substrate. Among them the spray distance has the greatest influence while the powder feeding rate has the least. Secondly, the regression function was well reflected the relationship between the three parameters and adhesion strength of the coating on the substrate. Using the values of spray parameter obtained from the GA optimization to create Cr3C2-30 %NiCr coating on 16Mn steel, the adhesion strength of the coating to the substrate reached a value of 98.4 % compared to the predictio

Правові та організаційні особливості планування законотворчої діяльності органів виконавчої влади за кордоном (на прикладі Соціалістичної Республіки В’єтнам)

This article analyses the laws of the Socialistic Republic of Vietnam in the context of defining the specifics of the involvement of public administration bodies (namely, the central executive authorities) in the process of public law-making planning in general and departmental law-making planning in particular. It contains positive aspects of foreign experience, which should be realised in the Ukrainian law-making process.В статье приведен анализ законодательства Социалистической Республики Вьетнам в контексте определения специфики участия органов публичной администрации (а именно, центральных органов исполнительной власти) в процессе планирования государственного законотворчества в целом и ведомственного законотворческого планирования в частности. Указаны положительные черты зарубежного опыта, заслуживающие внимания при внедрении в украинское законотворчество.У статті наведений аналіз законодавства Соціалістичної Республіки В’єтнам в контексті визначення специфіки участі органів публічної адміністрації (а саме, центральних органів виконавчої влади) в процесі планування державної законотворчості загалом, та відомчого законотворчого планування зокрема. Вказані позитивні риси зарубіжного досвіду, що заслуговують уваги та втілення в українську законотворчість

PREPARATION OF POLYMER COMPOSITES BASED ON UNSATURATED POLYESTER REINFORCED BY NATURAL FIBER AND CELLULOSE MICROFIBER FROM LUNG WASTE IN NGHE AN

Unsaturated polyester composites reinforced by glass fiber and by hybrid reinforcementglass fiber - lung fiber with cellulose microfiber (MFC) were prepared and investigated. Tensileand flexural strengths of material reached the highest value at polymer composite with 48 %wglass fiber mat and 0.3 %w MFC (208.33 MPa and 243.6 0 MPa), while the highest impactstrength reached 212.48 kJ/m2 at composite containing 48 %w glass fiber but 0.5 %w MFC.Especially, with 0.3 %w MFC, the tensile fatigue cycle to failure of composite processed byvacuum bag remarkably increased, 140.28 % at composite with 48 %w glass fiber and 265.63 %at hybrid composite reinforced by glass fiber/lung fiber, compared to samples without MFC