This introduction presents the main motivations for the development of Description Logics (DLs) as a formalism for representing knowledge, as well as some important basic notions underlying all systems that have been created in the DL tradition. In addition, we provide the reader with an overview of the entire book and some guidelines for reading it. We first address the relationship between Description Logics and earlier semantic network and frame systems, which represent the original heritage of the field. We delve into some of the key problems encountered with the older efforts. Subsequently, we introduce the basic features of DL languages and related reasoning techniques. DL languages are then viewed as the core of knowledge representation systems, considering both the structure of a DL knowledge base and its associated reasoning services. The development of some implemented knowledge representation systems based on Description Logics and the first applications built with such systems are then reviewed. Finally, we address the relationship of Description Logics to other fields of Computer Science.We also discuss some extensions of the basic representation language machinery; these include features proposed for incorporation in the formalism that originally arose in implemented systems, and features proposed to cope with the needs of certain application domains.

https://assets.cambridge.org/97805218/76254/frontmatter/9780521876254_frontmatter.pdf

The Description Logic Handbook

This article presents a number of ways in which ontologies-schematic descriptions of the contents of domain knowledge-can be constructed and can be used to improve the knowledge engineering process. The main message is that early in the knowledge engineering process an application-specific ontology should be constructed. To facilitate this, the article presents some principles for organizing a library of reusable ontological theories which can be configured into an application ontology. This application ontology is then exploited to organize the knowledge acquisition process and to support computational design. The process is illustrated with a knowledge engineering scenario in the domain of treating acute radiation syndrome.

Using explicit ontologies in KBS development

KADS: a modelling approach to knowledge engineering

In this paper, we review 300 references on video retrieval, indicating when text-only solutions are unsatisfactory and showing the promising alternatives which are in majority concept-based. Therefore, central to our discussion is the notion of a semantic concept: an objective linguistic description of an observable entity. Specifically, we present our view on how its automated detection, selection under uncertainty, and interactive usage might solve the major scientific problem for video retrieval: the semantic gap. To bridge the gap, we lay down the anatomy of a concept-based video search engine. We present a component-wise decomposition of such an interdisciplinary multimedia system, covering influences from information retrieval, computer vision, machine learning, and human–computer interaction. For each of the components we review state-of-the-art solutions in the literature, each having different characteristics and merits. Because of these differences, we cannot understand the progress in video retrieval without serious evaluation efforts such as carried out in the NIST TRECVID benchmark. We discuss its data, tasks, results, and the many derived community initiatives in creating annotations and baselines for repeatable experiments. We conclude with our perspective on future challenges and opportunities.

/pdf/concept-based-video-retrieval-1iy430iazc.pdf

Concept-Based Video Retrieval

The composition and structure of the pregnancy vaginal microbiome may influence susceptibility to adverse pregnancy outcomes. Studies on the pregnant vaginal microbiome have largely been limited to Northern American populations. Using MiSeq sequencing of 16S rRNA gene amplicons, we characterised the vaginal microbiota of a mixed British cohort of women (n = 42) who experienced uncomplicated term delivery and who were sampled longitudinally throughout pregnancy (8–12, 20–22, 28–30 and 34–36 weeks gestation) and 6 weeks postpartum. We show that vaginal microbiome composition dramatically changes postpartum to become less Lactobacillus spp. dominant with increased alpha-diversity irrespective of the community structure during pregnancy and independent of ethnicity. While the pregnancy vaginal microbiome was characteristically dominated by Lactobacillus spp. and low alpha-diversity, unlike Northern American populations, a significant number of pregnant women this British population had a L. jensenii-dominated microbiome characterised by low alpha-diversity. L. jensenii was predominantly observed in women of Asian and Caucasian ethnicity whereas L. gasseri was absent in samples from Black women. This study reveals new insights into biogeographical and ethnic effects upon the pregnancy and postpartum vaginal microbiome and has important implications for future studies exploring relationships between the vaginal microbiome, host health and pregnancy outcomes.

/pdf/the-vaginal-microbiome-during-pregnancy-and-the-postpartum-zevaqkc8z2.pdf

The vaginal microbiome during pregnancy and the postpartum period in a European population

While technology enables the storage and distribution of photographic images on an unprecedented scale, finding what you want can be like finding the proverbial needle in a haystack. The authors describe their approach and the tool they developed to make annotating photos and searching for specific images more intelligent.

/pdf/ontology-based-photo-annotation-46whqbcv4b.pdf

Ontology-based photo annotation

SWI-Prolog is neither a commercial Prolog system nor a purely academic enterprise, but increasingly a community project. The core system has been shaped to its current form while being used as a tool for building research prototypes, primarily for knowledge-intensive and interactive systems. Community contributions have added several interfaces and the constraint (CLP) libraries. Commercial involvement has created the initial garbage collector, added several interfaces and two development tools: PlDoc (a literate programming documentation system) and PlUnit (a unit testing environment).

In this article, we present SWI-Prolog as an integrating tool, supporting a wide range of ideas developed in the Prolog community and acting as glue between foreign resources. This article itself is the glue between technical articles on SWI-Prolog, providing context and experience in applying them over a longer period.

Swi-prolog

In this paper we discuss a tool for semantic annotation and search in a collection of art images. Multiple existing ontologies are used to support this process, including the Art and Architecture Thesaurus, WordNet, ULAN and Iconclass. We discuss knowledge-engineering aspect such as the annotation structure and links between the ontologies. The annotation and search process is illustrated with an application scenario.

https://homepages.cwi.nl/~hollink/pubs/Hollink03_saic.pdf

Semantic Annotation of Image Collections

The Prolog programmer’s needs have always been the focus for guiding the development of the SWI-Prolog system This article accompanies an invited talk about how the SWI-Prolog environment helps the Prolog programmer solve common problems It describes the central parts of the graphical development environment as well as the command line tools which we see as vital to the success of the system We hope this comprehensive overview of particularly useful features will both inspire other Prolog developers, and help SWI-Prolog users to make more productive use of the system

/pdf/an-overview-of-the-swi-prolog-programming-environment-17x145mr6w.pdf

An Overview of the SWI-Prolog Programming Environment.

Thesauri such as the Art and Architecture Thesaurus (AAT) provide structured vocabularies for describing art objects. However, if we want to create a knowledge-rich description of an (image of an) art object, such as required by the "semantic web", thesauri turn out to provide only part of the knowledge needed. In this paper we look at problems related to capturing background knowledge for art resources. We describe a case study in which we attempt to construct an ontology for a subset of art-object descriptions, namely antique furniture, using AAT as well as metadata standards as input. We discuss the representation requirements for such an ontology as well as representational problems for our sample ontology with respect to the emerging web standards for knowledge representation (RDF, RDFS, OIL).

/pdf/from-thesaurus-to-ontology-4e3dour6t4.pdf

Jan Wielemaker

Papers

Ontology-based photo annotation

Swi-prolog

Semantic Annotation of Image Collections

An Overview of the SWI-Prolog Programming Environment.

From thesaurus to ontology