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Knowledge graphs in the field of network security can integrate diverse, heterogeneous, and fragmented network security data, further explore the relationships between data, and provide support for deep analysis. Currently, there is sparse security information in the field of network security knowledge graphs. The limited information provided by traditional text encoding models leads to insufficient reasoning ability, greatly restricting the development of this field. Starting from text encoding, this paper first addresses the issue of the inadequate capabilities of traditional models using a deep learning model for assistance. It designs a vBiLSTM model based on a word2vec and BiLSTM combination to process network security texts. By utilizing word vector models to retain semantic information in entities and extract key features to input processed data into BiLSTM networks for extracting higher-level features that better capture and express their deeper meanings, this design significantly enhances understanding and expression capabilities toward complex semantics in long sentences before inputting final feature vectors into the KGC-N model. The KGC-N model uses feature vectors combined with graph structure information to fuse forward and reverse domain features and then utilizes a Transformer decoder to decode predictions and complete missing information within the network security knowledge map. Compared with other models using evaluation metrics such as MR, MRR demonstrates that employing our proposed method effectively improves performance on completion tasks and increases comprehension abilities toward complex relations, thereby enhancing accuracy and efficiency when completing knowledge graphs. [ABSTRACT FROM AUTHOR]

Automating sentiment analysis in texts has become an important task in recent years due to the exponential growth of user-generated content, including comments and opinions on products and services. This represents a valuable opportunity for businesses to glean insights into customer sentiment and, in turn, to refine their offerings. Motivated by this, the machine learning field has witnessed a surge of innovation, with an introduction of models and tools being introduced to streamline sentiment analysis. This paper offers a thorough review of the recent advancements in machine learning and deep learning approaches for text sentiment analysis. We propose a novel framework for studying these models, distinguishing them by their structural intricacies. Additionally, we delve into the challenges, prospects, and emerging directions in research, as illuminated by our framework. Consequently, this paper equips researchers with a detailed panorama of the cutting-edge machine learning methodologies for dissecting text sentiment, easing the way for future explorations in this vibrant field.

This paper presents the results of the modelling and analysis of the reading process within the Italian publishing house Einaudi after the Second World War, with a special focus on Natalia Ginzburg (1916-1991). More specifically, the corpus of sources consists of the reading reports concerning contemporary narrative works, which represent a fundamental step in the decision-making process that leads to the publication of a work and therefore to the construction of the catalogue of a publishing house. The examination of Natalia Ginzburg’s reading reports, mostly unpublished, provides the basis for a critical reflection on her editorial activity, a reflection which is rooted in the belief that editorial writing represents a complex critical genre that deserves to be investigated by specific methods. The tools (in the present case UML, PostgreSQL, XML TEI) and methods of the Digital Humanities have made a major contribution to the realisation of the scientific objectives of the research work. On the one hand, they have made it possible to model, represent and interrogate the corpus of documents in a relevant and efficient way; on the other hand, they were fundamental and indispensable from a methodological, heuristic and interpretative point of view.

This article evaluates the integration of digital editions, computational text analysis and digital scholarly editing in the context of an introductory undergraduate course on Italian literature and digital humanities taught at a US university. It offers specific examples of employing the apparatus of several digital platforms dedicated to the study of foundational authors in the Italian literary tradition (Dante, Petrarch, Boccaccio and Leopardi), and of gaining familiarity with a suite of digital tools for text analysis and editing, namely Voyant Tools, Recogito, Oxygen, Gephi, Transkribus Lite and OpenRefine. The discussion of digital project interfaces examines the student user experience of different design approaches, while the illustrations of tool exercises explore how these could support the close attention to a text and facilitate the navigation between its micro and macro frameworks of interpretation. The article furthermore suggests that digital text analysis could reinforce student appreciation of the signifying value of textual form and genre, and that the pedagogical method of digital text editing creates opportunities for situated learning. In conclusion, it argues that the academic work of students at the undergraduate level could be harnessed by the scaffolded methods of faculty-led digital research projects and contribute to the creation of public knowledge. [ABSTRACT FROM AUTHOR]

The paper presents the Digital Scholarly Edition of Umberto Eco's The Name of the Rose characterized since its conception by the dialogue between Digital Philology and Computational Literary Criticism in a interdisciplinary perspective called 'IDEA' paradigm (Interpretation, Didactics, Edition, Annotation). By bringing together Authorial Philology, Digital Annotation and Literature Didactics, the IDEA paradigm aims to overcome the objective limitations of publishing contemporary literature content on the Web in open format. The contribution then describes the portal «The Variants of the Rose», a virtual place where to present the critical apparatus of variants encoded in XML-TEI (and visualized through EVT2), some didactic content elaborated with TRAViz, Storymap JS and Timeline JS, the annotation in a Domain Specific Language developed on Euporia and further critical insights elaborated from Franco Moretti's Distant reading and Giuseppe Savoca's Literary Lexicography. Subsequently, a reflection on the modelling of edition, the concept of Extended Edition and the project workflow is presented. Finally, a road map of future content is proposed with a view to the increasing integration of scientific research and the Public Humanities.

The present paper deals with choosing the input alphabet for the end-to-end synthesizer of the Lithuanian language. Tacotron 2 is a state-of-the-art end-to-end speech synthesis model. Characters, phonemes or their combinations can be used as an input of the model. The model was trained on Lithuanian speech recordings using the following five input alphabets: letters, lowercase letters, accented letters, reduced set of accented letters, letters with separate accent marks. Acceptability of the synthesized speech was evaluated on the basis of human listeners' subjective judgment. Experimental testing showed that accent marks significantly improved the quality of the synthesized speech. Reducing the size of the input alphabet also has a slight positive impact. Putting accent marks into the text produced the best results as compared to using the accented letters. [ABSTRACT FROM AUTHOR]

Text-to-Face generation is an interesting and challenging task with great potential for diverse computer vision ap- plications in public safety domain. There has been very selective work in Text-to-Face synthesis than Text-to-Image due to diverse facial visual attributes and their corresponding descriptions. In this paper, we have proposed a Text-to-Face generative model that can produce high quality and high resolution images from a given textual description. The model is also able to produce a range of diverse images for a given description. In the proposed approach, the encoded text input is mapped to the generator to produce high quality output which is further manipulated to better reflect the described attributes. Apart from diversity (or in addition to diversity), the model is also able to significantly emphasize the facial attributes provided in the description. The applications of the proposed model include criminal investigation, character generation (video games, movies etc.), manipulating facial attributes according to brief textual description, text based style transfer, text based Image retrieval etc. [ABSTRACT FROM AUTHOR]

Computers work with text data by assigning a code for each character, called encoding. Character-encoding techniques emerged in the late 1960s, and a similar type of technique is still used to encode text data. Computers can only understand alphabets, not words. In this article, we develop an approach that enables computers to understand words. We introduce a word-based encoding of text data named WordCode. WordCode encodes the most frequent set of characters (i.e., words) found in Internet directories with a dynamic code combination. Although some dictionary-encoding techniques have been proposed, we still tend to use character encoding, such as Unicode, to encode text data. Dictionary-encoding techniques have not been adopted due to the massive size of the code page and the complexity in accessing the code page. In this article, we introduce a customised trie named WordTrie to store words for faster encoding and decoding. We generate the code combination in such a way that the size of the WordCode for a word is always smaller than the total size of the character coding. Our experimental results from encoding text files from the Gutenberg corpus, Canterbury corpus, large corpus, Calgary corpus and Silesia corpus using WordCode show an up to 19.9% reduction in file size with respect to character-based encoding. This smaller file size means that less storage space is needed and results in faster processing and communication of text data.

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper presents the potential means of utilizing digital edition tools by retracing the process of the Codice Pelavicino digital edition. We will also explore the related issues of coding, output, easiness of use, relationship with users. The paper presents the reworking of a lecture presented at the webinar “Medieval archival sources in digital environment. The challenge of processing and visualizing semi-structured data ", organized on 22-23 June 2020 by the Digital Culture Laboratory (University of Pisa) and by the head of the Engineering Historical Memory project. The aim is to promote future collaboration and experimentation initiatives in the field of processing and extraction of information from semi-structured editions of archival documents.

The webinar “Medieval archival sources in the digital world. The challenge of treating and visualizing semi-structured data”, organized by the Digital Culture Laboratory (UNIPI) and by the Engineering Historical Memory project. This thematic dossier aims to offer a brief account of the results of the workshop, with particular attention to future collaborations and experimentations in the field of processing and extracting information from semi-structured editions of archival documents. These advanced features are essential to broaden the use of digital editions of archival sources and other written documents, making them more flexible and open to research tools. The central problem concerns the relationship between text coding and the creation of good interfaces, to which the user can accessintuitively.

Knowledge graphs (KGs) are crucial in documenting bridge maintenance expertise. However, existing KG schemas lack integration of bridge design and practical inspection insights. Meanwhile, traditional methods for node feature initialization, relying on meticulous manual encoding or word embeddings, are inadequate for real-world maintenance textual data. To address these challenges, this paper introduces a bridge maintenance-oriented KG (BMKG) schema and approaches for graph data mining, including node-layer classification and link prediction. These methods leverage large language model (LLM)-based text encoding combined with GraphSAGE, demonstrating excellent performance in semantic enrichment and KG completion on deficient BMKGs. Additionally, ablation studies reveal the superiority of the pre-trained BERT text encoder and the L2 distance pairwise scoring calculator. Furthermore, a practical implementation framework integrating these approaches is developed for routine bridge maintenance, which can facilitate various practical applications, such as maintenance planning, and has the potential to enhance the efficiency of engineers' documentation work. • This paper introduces a hierarchical knowledge graph schema based on real-world bridge maintenance reports. • A node-layer classification approach is proposed for semantic enrichment by employing GraphSAGE and LLM-based text encoding. • A link prediction approach is proposed for graph completion by leveraging GraphSAGE and contrastive learning. • An implementation framework integrating the above schema and approaches is designed for practical bridge maintenance. [ABSTRACT FROM AUTHOR]

In common with many technical aspects of digital humanities, the TEI has a reputation for being difficult to teach and difficult to learn, with potential practitioners put off by the large and (at first sight) intimidating set of guidelines, the seemingly complex hierarchical structure and the profusion of angle brackets. One-to-one or small group teaching in the context of a specific project is often the preferred method, where the short but steep learning curve required to engage with the TEI can be addressed in a way which is relevant to the aims and experience of the learner. This, however, is not a particularly efficient way of teaching. In this article, the authors discuss their experience of teaching (and learning) the TEI, and how lessons learned in contexts relating to specific projects might feed into the teaching of TEI in a more general setting – the Digital Humanities at Oxford Summer School being the prime example.

Literary and textual scholars have long speculated about Wilde’s intentions for revising the homoerotic content of his famous novel, The Picture of Dorian Gray (1891). More recently, electronic editing tools enable scholars to explore textual composition histories within a digital space. This project uses the Text Encoding Initiative (TEI) standard, an electronic editing tool that allows researchers to ‘mark up’, or tag, textual elements. Using the TEI, I mark up the first chapter of Wilde’s manuscript of Dorian Gray, which introduces the story’s three main characters, Basil Hallward, Lord Henry Wotten, and Dorian Gray. Drawing from debates in Textual Scholarship and Queer Historiography, I question how electronic editing with the TEI might register the ways that Wilde suppressed the homoeroticism between these three characters during his revision process. My work here pushes against what I identify as TEI’s main constraint, which is its limitation for handling data that is discrete, rather than smooth or ambiguous data, like the homoeroticism of this text. I conclude by proposing a TEI customization that marks Wilde’s revisions according to the four homoerotic themes of ‘intimacy’, ‘beauty’, ‘passion’ and ‘fatality’. As an experiment in ‘queer encoding’, this customization shows how strict data structures like the TEI might engage the fluidity and complexity of queerness in text.

The paper discusses the phenomenon of text reuse in the manuscript tradition of Ethiopia and Eritrea and, by examining examples of different forms of text reuse, presents the possibilities of its encoding in TEI XML within the frame of the project Beta maṣāḥǝft. Text reuse, which consists in the implicit or explicit repetition of text, is attested in a variety of forms, including quotations, allusions, paraphrases, and cross-linguistic text reuse. The documentation of this practice contributes to the study of different aspects of the manuscript tradition, for example, to the impact and relative dating of texts, and history of their transmission. The variety of text reuse forms allows for different approaches to their encoding which are presented in this paper to illustrate the possibilities of text reuse markup within the project’s schema. Additionally, the paper discusses the concept of narrative units and its difference to the concept of text reuse, as well as the markup of a type of text reuse which involves the reference to external entities.

Computers work with text data by assigning a code for each character, called encoding. Character-encoding techniques emerged in the late 1960s, and a similar type of technique is still used to encode text data. Computers can only understand alphabets, not words. In this article, we develop an approach that enables computers to understand words. We introduce a word-based encoding of text data named WordCode. WordCode encodes the most frequent set of characters (i.e., words) found in Internet directories with a dynamic code combination. Although some dictionary-encoding techniques have been proposed, we still tend to use character encoding, such as Unicode, to encode text data. Dictionary-encoding techniques have not been adopted due to the massive size of the code page and the complexity in accessing the code page. In this article, we introduce a customised trie named WordTrie to store words for faster encoding and decoding. We generate the code combination in such a way that the size of the WordCode for a word is always smaller than the total size of the character coding. Our experimental results from encoding text files from the Gutenberg corpus, Canterbury corpus, large corpus, Calgary corpus and Silesia corpus using WordCode show an up to 19.9% reduction in file size with respect to character-based encoding. This smaller file size means that less storage space is needed and results in faster processing and communication of text data. [ABSTRACT FROM AUTHOR]

In common with many technical aspects of digital humanities, the TEI has a reputation for being difficult to teach and difficult to learn, with potential practitioners put off by the large and (at first sight) intimidating set of guidelines, the seemingly complex hierarchical structure and the profusion of angle brackets. One-to-one or small group teaching in the context of a specific project is often the preferred method, where the short but steep learning curve required to engage with the TEI can be addressed in a way which is relevant to the aims and experience of the learner. This, however, is not a particularly efficient way of teaching. In this article, the authors discuss their experience of teaching (and learning) the TEI, and how lessons learned in contexts relating to specific projects might feed into the teaching of TEI in a more general setting – the Digital Humanities at Oxford Summer School being the prime example. [ABSTRACT FROM AUTHOR]

The idea of textual variation was notably rejected in the early days of critique génétique, but versions have been playing a prominent role in most editorial schools of genetic orientation. This article presents a systematic review of the literature to distinguish the main working definitions and editorial approaches to the notion of version, both in genetic analogue editions and digital archives based on text encoding and computer-assisted collation. [ABSTRACT FROM AUTHOR]

As a student of intellectual, religious, and cultural developments in areas of the Chinese cultural sphere, my initial motivation for engaging with digital texts thirty years ago was to open up the new possibilities that the digital medium offered to researchers, without losing any of the affordances of a traditional printed edition. This requirement includes use of texts for reading, translating, annotating, quoting, and publishing, thus integrating with the whole of the scholarly workflow. At that time theories of electronic texts started to appear and the Text Encoding Initiative had already begun to create a common text model and interchange specification, based mainly on European languages. For East Asian texts, things were much more complicated because of different and quickly evolving character encoding standards, different textual traditions and approaches to text editing, as well as different institutional embedding. In this paper, I will look back at these developments, first to recount some of the history, albeit from a strictly personal perspective, but also to take stock of the situation and consider where we are now, how we got there, and what remains to be done to realize the dream of the universal digital text, easily shared and annotated, but still tractable, verifiable, and authoritative.

This article first outlines the challenges involved in the editing of Old English anonymous and Wulfstanian homilies before introducing the Electronic Corpus of Anonymous Homilies in Old English (ECHOE) project. This new initiative at the University of Göttingen reverses the traditional collation of texts and instead celebrates the book-historical significance of every individual manuscript version, its textual and palaeographical idiosyncrasies, and its revisional layers up through c. 1200 AD. The project provides new forms of display to expose the complex interversional network of textual representations, and develops a range of digital tools to facilitate the identification and swift comparison of related passages. It includes digital facsimiles, palaeographical and rhetorical version profiles, and the Latin sources for each homily, creating opportunities for unprecedented research on the transmission, composition, variation, and performance of the fluid preaching text. [ABSTRACT FROM AUTHOR]

Croatian philology has a long tradition of publishing reference books in the field of historical linguistics; it is very important to continue and foster this tradition in the future, as well as to adapt it to the modern digital era. Recent large-scale digitization initiatives have focused heavily on historical texts. Many reasons have led to the increasing digitization of archival documents, library and museum material, and collections of old books and manuscripts stored in monasteries. One of the main reasons for the digitization of old texts is to protect the original document from possible damage resulting from inappropriate handling. The use of digital copies instead of original documents is necessary to protect and preserve old written texts, as they are the most reliable way to back up original documents. Another very important reason for digitizing old texts is to make them more accessible to scholars, experts, and the public. In this way, young people who prefer using digital media will become more easily acquainted with cultural heritage that would otherwise be inaccessible to them. The digitization model of old Croatian grammar books will be discussed, as the existing resources do not include grammar books from the pre-standard period of the Croatian language. [ABSTRACT FROM AUTHOR]

The project of editing the early Biographie W. A. Mozart’s (1828) by Georg Nikolaus Nissen (Nissen Online) began as part of the Digital Mozart-Edition (DME) at the Mozarteum Foundation Salzburg. The aim of the edition is to reveal the structure of the text by identifying the diverse sources Nissen relied on when writing the biography. These include primary sources such as original letters and documents from the Mozart family, secondary sources such as contemporary literature about Wolfgang Amadeus Mozart, and original text written by the author and later editors. Considering the challenges that arise when creating an edition that tries to define the different strands of a text, this paper describes how XML/TEI markup was applied to encode text passages which often do not correlate with common text structures (paragraphs, chapters); document different types of sources and their authors or editors; and integrate a detailed bibliography of the sources as well as critical annotations for each single text passage.

This paper presents the first phase in the development of a new, TEI-based protocol for the encoding of promptbooks. Because the principal function of a promptbook is to record spatiotemporal events whose communicative importance supersedes that of the book in which they are recorded, current standards for digital encoding do not always apply. With the stage managerial artifacts of The. John Gray and the Canadian Stratford Festival Archives as case studies, we provide a rationale for exploring additions to the existing TEI guidelines to account for the unique characteristics of promptbooks. Cet article présente la phase initiale du développement d’un nouveau protocole de codage TEI adopté pour des livres rapides. Puisque la fonction principale d’un livre rapide est l’enregistrement des évènements spatio-temporels dont l’importance communicative l’emporte sur celle du livre dans lequel on les écrit, les normes de codage numérique ne s’applique pas toujours. Avec les artefacts du régisseur The. John Gray et des archives du festival de Stratford du Canada, nous fournissons une justification pour la recherche sur l’adjonction aux consignes de TEI qui rend compte des caractéristiques uniques des livres rapides. Mots-clés: codage de texte; TEI; livres rapides; textes littéraires

Copyright of Digital Studies / Champ Numérique is the property of Open Library of Humanities and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tourism is becoming a viable and important economic development strategy in the regeneration of historic districts. Nonetheless, tourism may bring negative impacts to the local communities. As a result, local residents′ perceptions and attitudes toward tourism development are critical to the sustainable development of tourism. This study follows a qualitative research approach, attempting to examine the relationship between local residents′ social-demographic features and their perceptions of tourism development. The framework is applied to the case of Nanluoguxiang in Beijing, China, which is a typical tourism destination benefitting from its traditional urban forms. Data from 24 in-depth interviewees are analyzed using word-frequency analysis through text encoding. The results reveal that the cultural perception of the residents promoted place attachment, which was associated with impact perception, and together, they determined behavioral demand. The stronger the cultural perception of the residents is and the stronger their place attachment is, the more the negative impact of tourism is perceived and the stronger their demand for cultural protection is. Long-term residents, those with occupations unrelated to tourism, and those who live adjacent to the tourism attractions perceived more negative impacts.

This paper proposes a minor but significant modification to the TEI ODD language and explores some of its implications. Can we improve on the present compromise whereby TEI content models are expressed in RELAX NG? A very small set of additional elements would permit the ODD language to cut its ties with any existing schema language, and thus permit it to support exactly and only the subset or intersection of their facilities which makes sense in the TEI context. It would make the ODD language an integrated and independent whole rather than an uneasy hybrid, and pave the way for future developments in the management of structured text beyond the XML paradigm.

The role of the reference librarian has changed considerably over the past thirty years. Today reference librarians spend as much time on public relations as on answering reference questions and more time solving log-in issues than on helping with research. Despite this, there is still a role for reference librarians to play using their research and curation skills. That role involves the digital humanities, particularly text encoding projects following the guidelines of the Text Encoding Initiative Consortium (TEI). One such TEI project is the Rosarium Project, which curates online popular materials about roses. [ABSTRACT FROM PUBLISHER]

By combining traditional historical enquiry with TEI XML encoding and decoding in a corpus analysis phase, the project aims at addressing research questions mainly related to the French and British positions on the topics of armament design and production and of armament control within the Western European Union (WEU) from 1954 to 1982. The paper focuses on the annotation of speakers (different countries and institutional representatives) and their discourse in a selection of institutional documents (minutes, notes, studies, memoranda) (encoding phase) and the identification of linguistic patterns on armament issues in their discourse, as well as the interpretation of results (decoding phase). From a larger perspective, the study considers the TEI encoding as adding to the original text a “material” layer that further supports both machine and human interpretation (decoding). In this sense, this study may move closer to the concept of “material hermeneutics,” by understanding code, and digital technology in general, as an instrument we can use in hermeneutic ways to produce knowledge.