Results 1 to 10 of about 88,310 (211)
Semi-Automatic Terminology Ontology Learning Based on Topic Modeling [PDF]
Ontologies provide features like a common vocabulary, reusability, machine-readable content, and also allows for semantic search, facilitate agent interaction and ordering & structuring of knowledge for the Semantic Web (Web 3.0) application. However, the challenge in ontology engineering is automatic learning, i.e., the there is still a lack of ...
Monika Rani, Amit Kumar Dhar, O. P. Vyas
semanticscholar +9 more sources
Nebiz, ülkemizdeki karşılığı ile “şıra” diye bilinen özellikle yaş veya kuru haldeki hurma veya üzümden, parçalanıp sulandırılarak üretilmiş şekerli ve alkol içermeyen sıvı içecek grubudur. Günümüze kadar ulaşan fıkhi tartışmalarda, üretim benzerliği ve alkol oluşum riski dikkate alınarak, buğday, arpa, mısır, pirinç ve darı gibi nişastalı bitkisel ...
Adem Elgün
semanticscholar +6 more sources
Prior studies have shown that terminology support can improve health information retrieval but have not taken into account the characteristics of the user performing the search.
Carla Teixeira Lopes, Cristina Ribeiro
semanticscholar +4 more sources
Improving topic modeling performance on social media through semantic relationships within biomedical terminology. [PDF]
Topic modeling utilizes unsupervised machine learning to detect underlying themes within texts and has been deployed routinely to analyze social media for insights into healthcare issues. However, the inherent messiness of social media hinders the full realization of this technique’s potential. As such, we hypothesized that restricting medical concepts
Xin Y+8 more
europepmc +5 more sources
Query Behavior: The Impact of Health Literacy, Topic Familiarity and Terminology
We conducted a user study to analyze how health literacy, topic familiarity and the terminology used in past queries affect query behavior in health searches. We found that users with inadequate health literacy have less success in web searches and show more difficulties in query formulation.
Carla Teixeira Lopes, Cristina Ribeiro
semanticscholar +5 more sources
About the "Mistress" and confessional terminology (to the topic "Dostoevsky and the Old Believers")
S.S. Bytko
semanticscholar +3 more sources
Terminological variation, a means of identifying research topics from texts [PDF]
After extracting terms from a corpus of titles and abstracts in English, syntactic variation relations are identified amongst them in order to detect research topics. Three types of syntactic variations were studied: permutation, expansion and substitution. These syntactic variations yield other relations of formal and conceptual nature.
Fidelia Ibekwe-Sanjuan
+7 more sources
Unsupervised Terminological Ontology Learning Based on Hierarchical Topic Modeling [PDF]
In this paper, we present hierarchical relationbased latent Dirichlet allocation (hrLDA), a data-driven hierarchical topic model for extracting terminological ontologies from a large number of heterogeneous documents. In contrast to traditional topic models, hrLDA relies on noun phrases instead of unigrams, considers syntax and document structures, and
Xiaofeng Zhu+2 more
openalex +5 more sources
Improving Terminology to Describe Coronary Artery Procedures
Coronary artery disease (CAD) is treated with medical therapy with or without percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG). The latter 2 options are commonly referred to as "myocardial revascularization" procedures.
Torsten Doenst+4 more
openaire +4 more sources
Why Terminology Matters for Successful Rollout of Carbon Dioxide Utilization Technologies
To realize their full sustainability potential, carbon dioxide utilization technologies (carbon capture and utilization/CCU) presently require policy support.
Barbara Olfe-Kräutlein+5 more
doaj +2 more sources