New names for old concepts, or does history count?

Biomedical terminologies have been increasingly used in modern biomedical research and applications to facilitate data management and ensure semantic interoperability. As part of the evolution process, new concepts are regularly added to biomedical terminologies in response to the evolving domain knowledge and emerging applications. Most existing concept enrichment methods suggest new concepts via directly importing knowledge from external sources. In this paper, we introduced a lexical method based on formal concept analysis (FCA) to identify potentially missing concepts in a given terminology by leveraging its intrinsic knowledge - concept names. We first construct the FCA formal context based on the lexical features of concepts. Then we perform multistage intersection to formalize new concepts and detect potentially missing concepts. We applied our method to the Disease or Disorder sub-hierarchy in the National Cancer Institute (NCI) Thesaurus (19.08d version) and identified a total of 8,983 potentially missing concepts. As a preliminary evaluation of our method to validate the potentially missing concepts, we further checked whether they were included in any external source terminology in the Unified Medical Language System (UMLS). The result showed that 592 out of 8,937 potentially missing concepts were found in the UMLS.

We show how the problem of deciding the existence of uniform interpolants of TBoxes formulated in the Description Logic \EL can be divided into three subproblems based on a characterisation of the logical difference between \EL-TBoxes. We propose a proof-theoretic decision procedure for subsumer interpolants of general TBoxes formulated in the Description Logic \EL, solving one of these subproblems. A subsumer interpolant of a TBox depends on a signature and on a concept name. It is a TBox formulated using symbols from the signature only such that, both, it follows from the original TBox and it exactly entails the subsumers formulated in the signature that follow from the concept name \wrt~the original TBox. Our decision procedure first constructs a graph that exactly represents the part of original TBox that is describable using signature symbols only. Subsequently, it is checked whether a graph-representation of the original TBox can be simulated by the constructed graph, in which case a subsumer interpolant exists. We also evaluate our procedure by applying a prototype implementation on several biomedical ontologies.

According to the perceptual symbols theory (Barsalou, 1999), sensorimotor simulations underlie the representation of concepts. We investigated whether recognition memory for pictures of concepts was facilitated by earlier representation of visual properties of those concepts. During study, concept names (e.g., apple) were presented in a property verification task with a visual property (e.g., shiny) or with a nonvisual property (e.g., tart). Delayed picture recognition memory was better if the concept name had been presented with a visual property than if it had been presented with a nonvisual property. These results indicate that modality-specific simulations are used for concept representation.

Integration is a key issue in conceptual database design. However, the integration process is very complex and error prone and may often cause semantic loss. Semantic loss, in this chapter, is described as a problem that occurs if one or several concept names and/or dependencies describing the meaning of a concept are lost during the view integration process. Semantic loss often occurs because of the way resolution methods are used today since not only similarities, but also differences between the views have to be identified, resolved, and simplified. The high focus on technical and implementation issues that most of the modeling languages adopt today may also cause semantic loss. In this chapter we argue that a modeling language that instead puts focus on concept names and dependencies should be applied. We also argue and propose alternative resolution and simplification techniques for name conflicts and inter-schema properties that instead of getting rid of concept names and dependencies keep these as long as possible in the integration process. Applying the proposed resolution and simplification techniques might counter an impoverishment of the language used in the views and/or schema and prevent semantic loss. The proposed resolution techniques might even contribute to a semantically richer global conceptual database schema.

The main aim of the study is to quantitatively scrutinize the borrowability of IT-related Englishwords in Die Welt and Der Spiegel, as far as the proportion of nouns, verbs, and adjectives is con-cerned. The purpose of this study is to establish the most and the least frequently borrowed partsof speech and arrive at certain general tendencies governing the transfer of the most popular wordclass within the field of IT. The study covers an excerpt from authors’ research on IT-related angli-cisms carried out in 2016, and may serve as a basis for further investigation, since the developmentof ICT will always necessitate new names for concepts. Therefore, it is by all means prudent andinstructive to delve into the rationale behind the way anglicisms permeate into the German language.The study also constitutes a synchronic look at a given stage of the evolution of the German lan-guage.

Background. Affectonyms are linguistic resources with inherent positive-evaluative coloring, expressed through various emotional lexemes across different language levels. These units in contemporary Ukrainian song lyrics have not been studied linguistically, making this article relevant. The study of affectonyms in contemporary Ukrainian song lyrics helps to understand their role in the linguistic worldview Ukrainians of the XXI century. Methods. To fulfill the tasks, set out in the article, descriptive method, functional method, systematic analysis, contextual analysis, and component analysis were used. Results. The lexical and semantic diversity of affectonyms is vast and dynamic, constantly enriched by communicators’ creativity. A key feature of affectonyms is their aim to elicit a reaction from the addressee. Contemporary Ukrainian bands and performers use affectonyms in the following groups: 1) zoomorphisms; 2) florisms; 3) lexemes to refer to people by their external features and the speaker’s attitude; 4) names with astronomical and meteorological meanings; 5) names of mythological creatures, heroes of famous works 6) names of titles; 7) names with the meaning of preciousness; 8) lexemes with negative semantics; 9) names of abstract concepts; 10) polite and formal forms; 11) names of household items; 12) names with the meaning of “beloved”. The lyrics of contemporary Ukrainian bands and performers are dominated by noun affectonyms due to their ability to express deep emotions. Adjectives are less common, as their emotional intensity is lower, but uninflated feminine adjective forms show a continuation of folklore traditions. Musicians use affectonym phrases to create complex expressions of emotional connection and sound images in music. Conclusion. Affectonyms have always occupied an important place in the linguistic worldview of Ukrainians, reflecting the specifics of their emotional comprehension of the world and being an organic component of communication and creativity of both previous generations and modern Ukrainians.

This paper explores the verbal representations of the WEAPON concept in Old English and Old Icelandic texts, examining how irrational knowledge structures, or "nano-myths," are embedded within the inner form of the concept's names through etymological analysis and interdisciplinary comparisons. These "nano-myths" serve as interpretational and categorizational filters, providing insight into the conceptual underpinnings of these language units. The study emphasizes the role of cognitive models as the basis for these conceptual verbalizations. The analytical approach used in this research is rooted in the theory of myth-oriented semiosis, which forms a key component of the interdisciplinary methodology known as "M-logic." This approach involves reconstructing the cognitive premises underlying these language units and mapping them against a universal model of an open system to identify patterns and variations. The identified models are then compared to ascertain the differences and similarities in conceptual representation between Old English and Old Icelandic. The paper's synthetic interpretations suggest that the set of conceptualized semantic features, organized within the hierarchical plane of the universal model, helps define the allomorphic contours of the respective semantic spaces in the two worldviews. The instrumental component of the isomorphic frame-type structure, which reflects the synergetic dynamics of these semantic spaces, is extended in distinct ways in the Old English and Old Icelandic contexts. This differentiation contributes to the allomorphic structure observed in these worldviews, indicating a unique approach to the concept of weapons in each linguistic tradition.

The semantic similarity measure between biomedical terms or concepts is a crucial task in biomedical information extraction and knowledge discovery. Most of the existing similarity approaches measure the similarity degree based on the path length between concept nodes as well as the depth of the ontology tree or hierarchy. These measures do not work well in case of the “primitive concepts” which are partially defined and have only few relations in the ontology structure. Namely, they cannot give the desired similarity results against human expert judge on the similarity among primitive concepts. In this paper, the existing two ontology-based measures are introduced and analyzed in order to determine their limitations with respect to the considered knowledge base. After that, a new similarity measure based on concept name analysis is proposed to solve the weakness of the existing similarity measures for primitive concepts. Using SNOMED CT as the input ontology, the accuracy of our proposal is evaluated and compared against other approaches with the human expert results based on different types of ontology concepts. Based on the correlation between the results of the evaluated measures and the human expert ratings, this paper analyzes the strength and weakness of each similarity measure for all ontology concepts.

To develop a system for checking indication and contraindication of medicines in prescription order entry system, a master table consisting of the disease names corresponding to the medicines adopted in a hospital is needed. The creation of this table requires a considerable manpower. We developed a Web-based system for constructing a medicine/disease thesaurus and a knowledge base. By authority management of users, this system enables many specialists to create the thesaurus collaboratively without confusion. It supports the creation of a knowledge base using concept names by referring to the thesaurus, which is automatically converted to the check master table. When a disease name or medicine name was added to the thesaurus, the check table was automatically updated. We constructed a thesaurus and a knowledge base in the field of circulatory system disease. The knowledge base linked with the thesaurus proved to be efficient for making the check master table for indication/contraindication of medicines.

Ontologies are a useful model to express semantics in a machine-readable way. A matching of heterogeneous ontologies is often required for many different applications like query answering or ontology integration. Many systems coping with the matching problem have been developed in the past, most of them using meta information like concept names as a basis for their calculations. This approach works well as long as the pieces of meta information are similar. In case of very differently structured ontologies or if a lot of possible synonyms, homonyms or meaningless meta information are used, the recognition of mappings gets difficult. In these cases instance-based matching methods are a useful extension to find additional correct mappings resulting in an improved matching quality, because instances provide a lot of information about a concept. This paper presents a novel instance-based matching algorithm which calculates different features using instances. These features characterize the concepts and are compared using different similarity functions. Finally, the similarity values are used to determine 1:1 mapping proposals.

We study \(\mathcal{ALCK}_m\) and \(\mathcal{ALCS}4_m\), which extend the description logic \(\mathcal{ALC}\) by adding modal operators of the basic multi-modal logics Km and S4m. We develop a sound and complete tableau algorithm \(\Lambda_\mathcal{K}\) for answering \(\mathcal{ALCK}_m\) queries w.r.t. an \(\mathcal{ALCK}_m\) knowledge base with an acyclic TBox. Defining tableau expansion rules in the presence of acyclic definitions by considering only the concept names on the left-hand side of TBox definitions or their negations, allows us to give a PSPACE implementation for \(\Lambda_\mathcal{K}\). We then consider answering \(\mathcal{ALCS}4_m\) queries w.r.t. an \(\mathcal{ALCS}4_m\) knowledge base (with an acyclic TBox) in which the epistemic operators correspond to those of classical multi-modal logic S4m. The expansion rules in the tableau algorithm ΛS4 are designed to syntactically incorporate the epistemic properties. Blocking is corporated into the tableau expansion rules to ensure termination. We also provide a PSPACE implementation for ΛS4. In light of the fact that the satisfiability problem for \(\mathcal{ALCK}_m\) with general TBox and no epistemic properties (i.e., \(\mathbf{K}_{\mathcal{ALC}}\)) is NEXPTIME-complete, we conclude that both \(\mathcal{ALCK}_m\) and \(\mathcal{ALCS}4_m\) offer computationally manageable and practically useful fragments of \(\mathbf{K}_{\mathcal{ALC}}\).

An analysis of FMA using structural self-bisimilarity

The Craig interpolation property (CIP) states that an interpolant for an implication exists iff it is valid. The projective Beth definability property (PBDP) states that an explicit definition exists iff a formula stating implicit definability is valid. Thus, the CIP and PBDP reduce potentially hard existence problems to entailment in the underlying logic. Description (and modal) logics with nominals and/or role inclusions do not enjoy the CIP nor the PBDP, but interpolants and explicit definitions have many applications, in particular in concept learning, ontology engineering, and ontology-based data management. In this article, we show that, even without Beth and Craig, the existence of interpolants and explicit definitions is decidable in description logics with nominals and/or role inclusions such as 𝒜ℒ𝒞𝒪, 𝒜ℒ𝒞ℋ, and 𝒜ℒ𝒞ℋ𝒪ℐ and corresponding hybrid modal logics. However, living without Beth and Craig makes these problems harder than entailment: the existence problems become 2ExpTime -complete in the presence of an ontology or the universal modality, and coNExpTime -complete otherwise. We also analyze explicit definition existence if all symbols (except the one that is defined) are admitted in the definition. In this case, the complexity depends on whether one considers individual or concept names. Finally, we consider the problem of computing interpolants and explicit definitions if they exist and turn the complexity upper bound proof into an algorithm computing them, at least for description logics with role inclusions.

In 3 experiments, participants decided whether sensory and functional features were true of living and nonliving concepts. In Experiments 1 and 2, concepts were presented twice: test phase followed study phase after either 3 min (Experiment 1) or 3 s (Experiment 2). At test, concepts were paired with the same feature as that at study, or a different feature from either the same modality (within-modality priming) or another modality (cross-modality priming). In both experiments functional decisions were faster than sensory decisions for living and nonliving concepts. Whilst no semantic priming occurred between study and test in Experiment 1, the shorter study-test interval of Experiment 2 did lead to test phase semantic priming. Here there was greater within- than cross-modality priming for sensory decisions, but equivalent within- and cross-modality priming for functional decisions owing to significantly greater facilitation of functional decisions from prior sensory decisions than vice versa. Experiment 3 involved a single verification phase: For half the participants the feature name preceded the concept name, and for half the concept name preceded the feature name. The functional processing advantage persisted irrespective of presentation order. Results suggest that functional information is central to the representation of all concepts: Function is processed faster than sensory information and is activated obligatorily.

BackgroundRadiology reporting is a clinically oriented form of documentation that reflects critical information for patients about their health care processes. Realizing its importance, many medical institutions have started providing radiology reports in patient portals. The gain, however, can be limited because of medical language barriers, which require a way for customizing these reports for patients. The open-access, collaborative consumer health vocabulary (CHV) is a terminology system created for such purposes and can be the basis of lexical simplification processes for clinical notes.ObjectiveThe aim of this study was to examine the comprehensibility and suitability of CHV in simplifying radiology reports for consumers. This was done by characterizing the content coverage and the lexical similarity between the terms in the reports and the CHV-preferred terms.MethodsThe overall procedure was divided into the following two main stages: (1) translation and (2) evaluation. The translation process involved using MetaMap to link terms in the reports to CHV concepts. This is followed by replacing the terms with CHV-preferred terms using the concept names and sources table (MRCONSO) in the Unified Medical Language System (UMLS) Metathesaurus. In the second stage, medical terms in the reports and general terms that are used to describe medical phenomena were selected and evaluated by comparing the words in the original reports with the translated ones. The evaluation includes measuring the content coverage, investigating lexical similarity, and finding trends in missing concepts.ResultsOf the 792 terms selected from the radiology reports, 695 of them could be mapped directly to CHV concepts, indicating a content coverage of 88.5%. A total of 51 of the concepts (53%, 51/97) that could not be mapped are names of human anatomical structures and regions, followed by 28 anatomical descriptions and pathological variations (29%, 28/97). In addition, 12 radiology techniques and projections represented 12% of the unmapped concepts, whereas the remaining six concepts (6%, 12/97) were physiological descriptions. The rate of lexical similarity between the CHV-preferred terms and the terms in the radiology reports was approximately 72.6%.ConclusionsThe CHV covered a high percentage of concepts found in the radiology reports, but unmapped concepts are associated with areas that are commonly found in radiology reporting. CHV terms also showed a high percentage of lexical similarity with terms in the reports, which contain a myriad of medical jargon. This suggests that many CHV terms might not be suitable for lay consumers who would not be facile with radiology-specific vocabulary. Therefore, further patient-centered content changes are needed of the CHV to increase its usefulness and facilitate its integration into consumer-oriented applications.