Bridging the gap between digital libraries and e-learning

Digital Libraries (DL) are offering access to a vast amount of digital content, relevant to practically all domains of human knowledge, which makes it suitable to enhance teaching and learning. Based on a systematic literature review, this article provides an overview and a gap analysis of educational use of DLs.The research work presented in this paper is partially supported by the FP7 Grant 316087 AComIn ”Advanced Computing for Innovation”, funded by the European Commission in the FP7 Capacity Programme in 2012-2016.peer-reviewe

Conceptual Information Compression and Efficient Pattern Search

This paper introduces an encoding of knowledge representation statements as regular languages and proposes a two-phase approach to processing of explicitly declared conceptual information. The idea is presented for the simple conceptual graphs where conceptual pattern search is implemented by the so called projection operation. Projection calculations are organised into off-line preprocessing and run-time computations. This enables fast run-time treatment of NP-complete problems, given that the intermediate results of the off-line phase are kept in suitable data structures. The experiments with randomly-generated, middle-size knowledge bases support the claim that the suggested approach radically improves the run-time conceptual pattern search

Extracting Patient-Related Description from Medical Records in Bulgarian

This paper deals with the extraction of medical information from hospital patient records. It proposes a cascade approach for the extraction of multi-layer knowledge statements because the subject is too complex. We sketch the Information Extraction view to text analysis, where patient-related facts are recognised using predefined regular expressions and templates. A laboratory prototype for patient status ex- traction is presented together with the first evaluation results

bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark

We present bgGLUE (Bulgarian General Language Understanding Evaluation), a benchmark for evaluating language models on Natural Language Understanding (NLU) tasks in Bulgarian. Our benchmark includes NLU tasks targeting a variety of NLP problems (e.g., natural language inference, fact-checking, named entity recognition, sentiment analysis, question answering, etc.) and machine learning tasks (sequence labeling, document-level classification, and regression). We run the first systematic evaluation of pre-trained language models for Bulgarian, comparing and contrasting results across the nine tasks in the benchmark. The evaluation results show strong performance on sequence labeling tasks, but there is a lot of room for improvement for tasks that require more complex reasoning. We make bgGLUE publicly available together with the fine-tuning and the evaluation code, as well as a public leaderboard at https://bgglue.github.io/, and we hope that it will enable further advancements in developing NLU models for Bulgarian.Comment: Accepted to ACL 2023 (Main Conference

Incretins and SGLT-2i Therapy of Type 2 Diabetes – Real Life Study of Their Therapeutic and Economic Effects

AimIncretins [dipeptidyl peptidase-4 inhibitors (DPP-4i) and glucagon-like peptide 1 RA (GLP-1 RA)] and sodium-glucose cotransporter-2 inhibitors (SGLT-2i) groups are now routinely used for type 2 diabetes therapy and comprise a large number of medicinal products. The long term therapeutic and economic effect of the incretins’ and SGLT-2i in real life setting is not well documented. The goal of the current study is to analyze the cost and results of incretins and SGLT-2i based therapy for type 2 diabetes in Bulgaria.MethodsThe study uses information about the changes in glycated hemoglobin (HbA1c) level from the National diabetes register for 6122 patients and cost paid by the National Health Insurance Fund (NHIF) for diabetes complications, and medicine prices.ResultsThe results show that after the therapy patients achieved excellent diabetes control. There were no HbA1c values less than 6% before treatment. After the therapy, 3356 people showed values less than 7% HbA1c. It is considered very good diabetic control. The number of people with HbA1c above 8% is decreasing significantly. The number of people with values above 9% is decreasing by almost four times. HbA1c level decreases with the highest percentage for the patients treated with GLP-1 RA, followed by those treated with DPP-4i and SGLT-2i. For a year NHIF reimbursed 5.25 million BGN for incretins and SGLT-2i therapy. NHIF can save between 306 and 510 thousand BGN from incidents that have not occurred as a result of 5 years of therapy.ConclusionIncretins [dipeptidyl peptidase-4 inhibitors (DPP-4i) and glucagon-like peptide 1 receptor agonists (GLP-1 RA)] and sodium-glucose linked transporter-2 inhibitors (SGLT-2i) therapy steadily decreases the HbA1c level, and risk of developing diabetic incidents is reduced to between 333 and 465 cases among 6122 treated patients. Avoided cost for therapy of diabetes incidents account for between 305 and 510 thousand BGN

NL domain explanations in knowledge based MAT

This paper discusses an innovative approach to knowledge based Machine Aided Translation (MAT) where the translator is supported by an user-friendly environment providing linguistic and domain knowledge explanations. Our project aims at integration of a Knowledge Base (KB) in a MAT system and studies the integration principles as well as the internal interface between language and knowledge. The paper presents some related work, rel~)rts the solutions applied in our project and tries to generaiize our evaluation of the selected MAT approach. 1

DB-MAT: Knowledge Acquisition, Processing and NL Generation Using Conceptual Graphs

. This paper presents some research results and a demo implementation of a knowledge-based Machine Aided Translation (MAT) system supporting the translation process with the necessary linguistic and conceptual knowledge. Conceptual Graphs (cgs) were chosen as a knowledge representation formalism since they provide formal structures and operations suitable for representing and processing of terminological knowledge. We employ the cg operations to extract relevant knowledge with a flexible granularity. The paper describes all system components from a cg perspective and their interaction hidden under the user-friendly interface. 1 Introduction The attractive idea of building knowledge-based Natural Language (NL) systems has inspired a lot of research and prototype implementations. However, the problems of differentiation and interrelation of the two layers -- language and knowledge, as well as the problem of designing flexible user interfaces to the knowledge, are far from bein..

DB-MAT: A NL Based Interface to Domain Knowledge

Successful user-friendly interfaces will enable the application of knowledge based techniques in systems oriented towards end users who are not specialised in computer science. This paper discusses an approach to knowledge based Machine Aided Translation (MAT) which provides an user-friendly interface to Knowledge Bases (KB) of conceptual graphs. It is shown that each knowledge item is accessible in a simple and transparent way. The system explanation -- synthesised by a Natural Language (NL) generation -- allows for further clarifications within the context of previous answers. An evaluation of our approach in comparison to the strategy of follow-up questions is discussed as well. 1 Introduction and rationale KB methods from Artificial Intelligence are seldom combined with computational linguistics. There are two major difficulties for the adaptation of knowledge based approaches to Natural Language Processing (NLP) systems: (i) a task-adequate and useful distinction between languag..