Results 31 to 40 of about 803,882 (321)
Open Knowledge Extraction Challenge
, 2015 The Open Knowledge Extraction (OKE) challenge is aimed at promoting research in the automatic extraction of structured content from textual data and its representation and publication as Linked Data. We designed two extraction tasks: (1) Entity Recognition, Linking and Typing and (2) Class Induction and entity typing.
Nuzzolese, Andrea Giovanni +5 more
openaire +8 more sources
Machine Learning and Knowledge Extraction, 2023 Machine learning (ML) has been used in different ways in the fight against COVID-19 disease. ML models have been developed, e.g., for diagnostic or prognostic purposes and using various modalities of data (e.g., textual, visual, or structured).
Oliver Lohaj +4 more
doaj +1 more source
Identifying Knowledge Problems of Call Center Process Based on Process Mining (Case Study: Water and Wastewater Organization Call Center of Tehran Province) [PDF]
علوم و فنون مدیریت اطلاعات, 2022 Aim: This study was conducted to compare the designed process with the process extracted from the process discovery phase at the call center and to identify the knowledge problems associated with process deviations.
Mohammad Aghdasi +2 more
doaj +1 more source
Ontology-enhanced Prompt-tuning for Few-shot Learning [PDF]
, 2022 Few-shot Learning (FSL) is aimed to make predictions based on a limited number of samples. Structured data such as knowledge graphs and ontology libraries has been leveraged to benefit the few-shot setting in various tasks. However, the priors adopted by the existing methods suffer from challenging knowledge missing, knowledge noise, and knowledge ...
arxiv +1 more source
Trusted Data Storage Architecture for National Infrastructure
Sensors, 2022 National infrastructure is a material engineering facility that provides public services for social production and residents’ lives, and a large-scale complex device or system is used to ensure normal social and economic activities.
Yichuan Wang +4 more
doaj +1 more source
BERT-based knowledge extraction method of unstructured domain text [PDF]
arXiv, 2021 With the development and business adoption of knowledge graph, there is an increasing demand for extracting entities and relations of knowledge graphs from unstructured domain documents. This makes the automatic knowledge extraction for domain text quite meaningful.
arxiv
Text to Insight: Accelerating Organic Materials Knowledge Extraction via Deep Learning [PDF]
arXiv, 2021 Scientific literature is one of the most significant resources for sharing knowledge. Researchers turn to scientific literature as a first step in designing an experiment. Given the extensive and growing volume of literature, the common approach of reading and manually extracting knowledge is too time consuming, creating a bottleneck in the research ...
arxiv
Open Domain Knowledge Extraction for Knowledge Graphs
, 2023 7 pages, 7 figures, 5 tables, preprint technical report, no code or data is ...
Qian, Kun +17 more
openaire +2 more sources
Ontology-Based Knowledge Acquisition Method for Natural Language Texts
Цифровая трансформация, 2023 The main task of knowledge acquisition (also named knowledge extraction) from natural language texts is to extract knowledge from natural language texts into fragment of knowledge base of intelligent system.
Longwei Qian
doaj +1 more source
Extracting Cultural Commonsense Knowledge at Scale
Proceedings of the ACM Web Conference 2023, 2023 Structured knowledge is important for many AI applications. Commonsense knowledge, which is crucial for robust human-centric AI, is covered by a small number of structured knowledge projects. However, they lack knowledge about human traits and behaviors conditioned on socio-cultural contexts, which is crucial for situative AI.
Tuan-Phong Nguyen +3 more
openaire +3 more sources