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Showing 1 to 20 of 31 for “"Named entity recognition (NER)"”.
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Character language models for generalization of multilingual named entity recognition
"State-of-the-art Named Entity Recognition (NER) models usually achieve high performance on entities that they have seen in training data, but a significantly lower performance on unseen entities. This is one of the key reasons in performance degradation observed when NER models are evaluated on …
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Clinical Text De-identification Using Large Language Models: Insights from Organ Procurement Data
… baseline techniques, including traditional Named Entity Recognition (NER) and rules-based systems. Through a slew of experiments, we assesses the strengths and limitations of each method regarding precision and recall. This work will contribute to a uniquely extensive dataset, comprising …
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Fine-grained entity typing system - design and analysis
Named entity recognition (NER) is a natural language processing (NLP) task that involves identifying mentions (spans of text) denoting entities in a given text document and assigning them a semantic category/type from a given taxonomy. It is considered to be one of the fundamental tasks in NLP and …
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Natural Language Processing Methods to Automatically Parse Eligibility Criteria in Dietary Supplements Clinical Trials
… significant obstacle is identifying an efficient Named Entity Recognition (NER) system to parse the clinical trial eligibility criteria. The study comprises of two parts. In the first part of the study, the objective was to (1) understand data elements associated with DS trials’ eligibility …
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A schema conversion approach for constructing heterogeneous information networks from documents
… information networks. First, we utilize named entity recognition (NER) tools to explore networks over entities, topics, and words to demonstrate how a probabilistic model can convert the data schema of the NER tools. Second, we address a pat- tern mining method to construct a network with …
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Specialized Named Entity Recognition for Breast Cancer Subtyping
… information from text on various topics. Named Entity Recognition (NER), is one way to automate knowledge extraction of raw text. NER is defined as the task of identifying named entities from text using labels such as people, dates, locations, diseases, and proteins. There are several NLP …
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Domain-agnostic named entity recognition on unstructured text
Named Entity Recognition (NER) is the task of extracting informing entities belonging to predefined semantic classes from raw text. These semantic classes could be general-purpose like a person, location or domain-specific like genes, protein names in biomedical texts. NER has widespread …
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Minimally-supervised Methods for Arabic Named Entity Recognition
Named Entity Recognition (NER) has attracted much attention over the past twenty years, as a main task of Information Extraction. The current dominant techniques for addressing NER are supervised methods that can achieve high performance, but require new manually annotated data for every new domain …
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Artificial Intelligence-Aided Synthesis and Characterization of 2D Materials
… have emerged as promising candidates for next-generation transistors, to maintain the pace of Moore's Law—doubling the number of transistors every 18 months. The integration of AI and automation in material science has recently drawn significant attention, offering the potential to expedite and …
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Construction and Annotation of a Greek Corpus of Archaeological Texts
… κείμενα είναι η Αναγνώριση Ονοματικών Οντοτήτων (Named Entity Recognition – NER). Η παρούσα εργασία παρουσιάζει την ανάπτυξη ενός συνόλου δεδομένων εκπαίδευσης και αξιολόγησης που βασίζεται σε κείμενα με αρχαιολογικό περιεχόμενο. Ένα σώμα κειμένων, αποτελούμενο από 324 προτάσεις, επισημειώθηκε …
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Performance analysis of text classification algorithms for PubMed articles
… to each MeSH label. The second approach used Named Entity Recognition (NER) to extract entities from the unstructured text and another approach relied on word embeddings able to capture latent knowledge from literature. At the start of the study text was tokenised using the Term Frequency …
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Enhancing E-commerce Dataset recommendations using BERT and Named Entity Recognition
… Data Processing, and Query Processing. It uses Named Entity Recognition (NER) to enrich incomplete metadata by extracting contextual information and applies Term Frequency-Inverse Document Frequency (TF-IDF) alongside BERT embeddings to capture both keyword relevance and semantic context. This …
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Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery
… from explicit statements in literature to generate new or unstated knowledge. Automated LBD can thus facilitate hypothesis testing and generation from large collections of publications to support and accelerate scientific research, which is adversely affected by publication explosion and …
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Arabic News Text Classification and Summarization: A Case of the Electronic Library Institute SeerQ (ELISQ)
… news. Due to the lack of high quality tools for Named Entity Recognition (NER) and topic identification for Arabic, two new tools were constructed: RenA for Arabic NER, and ALDA for Arabic topic extraction tool (using the Latent Dirichlet Algorithm). Controlled experiments with each of RenA and …
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Information extraction with weak supervision
… fundamental information extraction (IE) tasks: Named Entity Recognition (NER), Relation Extraction (RE), and Entity Linking (EL). Traditional supervised learning methods in these domains often require extensive human annotations, which are costly and time-consuming, limiting their scalability …
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Active Expert Sourcing; Knowledge Extraction from Domain Specific Information
The development of Named Entity Recognition (NER) in recent years is partially attributed to the availability of annotated ata-sets. Data-sets play a crucial part indeveloping, training, and testing NER algorithms. The need for data-sets becomes more important when adapting the algorithms to new …
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Quantitative Geographic Analysis: A Cultural History of Australian Bushfire Narratives
… and exclusionary constructions of Australian identity, highlighting the need for a critical reassessment of cultural representations of bushfires and their associated national values. This task, however, is complicated by the limited historical research on 19th-century bushfires. While major …
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Quantitative Geographic Analysis: A Cultural History of Australian Bushfire Narratives
… and exclusionary constructions of Australian identity, highlighting the need for a critical reassessment of cultural representations of bushfires and their associated national values. This task, however, is complicated by the limited historical research on 19th-century bushfires. While major …
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Extracting Information on Dietary Supplements from Clinical Notes in Electronic Health Record Systems Through Natural Language Processing Techniques
… terms. Second, to detect and extract the named entities of DS as well as their relations with events (i.e., indications or AEs), named entity recognition (NER) and relation extraction (RE) tasks have been performed. Both machine learning and deep learning methods were evaluated and …
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Biographical information extraction: A language-agnostic methodology for datasets and models
… to a specific genre or topic, and are generally monolingual. It therefore stands to reason, that certain genres and topics have better models, as they are treated with a higher priority due to financial interests for instance. This in turn leads to RE models not being available to every …
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