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A Deep Learning-Based Text Classification of Adverse Nursing Events

Wenjing Lu, Wei Jiang, Na Zhang, Feng Xue, Rahim Khan
2021 Journal of Healthcare Engineering  
Additionally, we have proposed a text classification model for adverse nursing events in the health system.  ...  In the management of adverse nursing events, it is very important to categorize the text reports of adverse nursing events and divide these into different categories and levels.  ...  To make full use of the effective information in the unstructured text in the nursing adverse events, avoid dependence on characteristics, and improve the accuracy of the adverse event level prediction  ... 
doi:10.1155/2021/9800114 pmid:34840707 pmcid:PMC8616661 fatcat:37wxlt6pvfc6lmskd2lsx6rwfy

Evaluation Model of Power Operation and Maintenance Based on Text Emotion Analysis

Wei Wan, Yuanlong Liu, Xingwang Han, Huijian Wang, Gengxin Sun
2021 Mathematical Problems in Engineering  
The application of data mining technology in power field mainly focuses on the application of power defect text and dispatching text.  ...  The next sentence prediction analysis model of single round dialogue text based on transformer bidirectional encoder prediction and cosine similarity weighting is proposed, which can effectively divide  ...  If there is no conjunction in the sentence, β C � 1 for all basic units. (8) When there are both event words I ec and emotion words E cn in a sentence, event words, as words that objectively state facts  ... 
doi:10.1155/2021/2824689 fatcat:jumnyl6zifduzabzfszfmwzunm

Deep learning detects and visualizes bleeding events in electronic health records

Jannik S. Pedersen, Martin S. Laursen, Thiusius Rajeeth Savarimuthu, Rasmus Søgaard Hansen, Anne Bryde Alnor, Kristian Voss Bjerre, Ina Mathilde Kjær, Charlotte Gils, Anne‐Sofie Faarvang Thorsen, Eline Sandvig Andersen, Cathrine Brødsgaard Nielsen, Lou‐Ann Christensen Andersen (+2 others)
2021 Research and Practice in Thrombosis and Haemostasis  
Bleeding events are often described in the unstructured text of electronic health records, which makes them difficult to identify by manual inspection.  ...  A deep learning model can be used to detect and visualize bleeding events in the free text of electronic health records.  ...  | Visualization of bleeding events in EHR text In this study, we chose to use the sentence-level model on a note level because it makes the model capable of explaining its predictions.  ... 
doi:10.1002/rth2.12505 pmid:34013150 pmcid:PMC8114029 fatcat:x2evza34wng2vnx7gea4bdbwcy

Identification of End-User Economical Relationship Graph Using Lightweight Blockchain-Based BERT Model

Mukta Jagdish, Devangkumar Umakant Shah, Varsha Agarwal, Ganesh Babu Loganathan, Abdullah Alqahtani, Saima Ahmed Rahin, Vijay Kumar
2022 Computational Intelligence and Neuroscience  
In tests, the method can be used to get text information from unstructured economic user resumes and build a relationship map of people in the financial field.  ...  The experimental results show that the proposed approach is capable of efficiently retrieving information from unstructured financial personnel resume text and generating a character relationship graph  ...  For example, for sentence-level classification tasks, the output vector representation of the first label (CLS) is taken as the sentence representation; for character-level classification tasks, the output  ... 
doi:10.1155/2022/6546913 pmid:35571695 pmcid:PMC9106479 fatcat:3mjkijnbzvhwfdzg4qb4o4622i

Utilizing support vector machines in mining online customer reviews

Taysir Hassan A. Soliman, Mostafa A. Elmasry, Abdel Rahman Hedar, M. M. Doss
2012 2012 22nd International Conference on Computer Theory and Applications (ICCTA)  
Two levels of classification is applied: 1) Features classification and 2) Polarity classification for every feature class.  ...  In this paper, we apply an opinion mining approach to summarize the unstructured and ungrammatical users' reviews, based on Support Vector Machine (SVM).  ...  In addition, most of the sentences are written in an unstructured and ungrammatical format.  ... 
doi:10.1109/iccta.2012.6523568 fatcat:z7pplvjwnbad7pfce5rzzuzelq

A Survey of Opinion Mining and Sentiment Analysis

Vishakha Patel, Gayatri Prabhu, Kiran Bhowmick
2015 International Journal of Computer Applications  
The major challenge lies in analyzing the sentiments and identifying emotions expressed in texts.  ...  A huge amount of online information, rich web resources are highly unstructured and such natural language are not solvable by machine directly.  ...  Entity level Sentiment analysis Document level and sentence level classification may not be useful in all applications, as it fails to review opinion about a specific entity.  ... 
doi:10.5120/ijca2015907218 fatcat:afo3dkzukbhl7jdaw4zezisvli

Geotagging Location Information Extracted from Unstructured Data (Short Paper)

Kyunghyun Min, Jungseok Lee, Kiyun Yu, Jiyoung Kim, Michael Wagner
2018 International Conference Geographic Information Science  
If we can estimate the location of text by geotagging a large number of unstructured data, we can estimate the location of the event in real-time.  ...  We used the named entity recognizer and geotagged each sentence in combination of the fields in each category.  ...  In the English language, high-level recognition and classification performance were shown by using language characteristics such as capital letters [6] .  ... 
doi:10.4230/lipics.giscience.2018.49 dblp:conf/giscience/MinLYK18 fatcat:qha7f2nw2veevkiepmy7pqhm3m

Architecture of Text Mining Application in Analyzing Public Sentiments of West Java Governor Election using Naive Bayes Classification [article]

Suryanto Nugroho, Prihandoko
2018 arXiv   pre-print
The result of this research is that Twitter opinion mining is part of text mining where opinions in Twitter if they want to be classified, must go through the preprocessing text stage first.  ...  The selection of West Java governor is one event that seizes the attention of the public is no exception to social media users.  ...  Meanwhile, according to [3] analysis of sentiment in a sentence describes the consideration of the assessment of specific entities or events.  ... 
arXiv:1810.07767v1 fatcat:2hjovdovljbfpje5xl7slf4fa4

Opinion Mining Framework In The Education Domain

A. M. H. Elyasir, K. S. M. Anbananthen
2014 Zenodo  
The extraction stage includes web crawling, HTML parsing, Sentence segmentation for punctuation classification, Part of Speech (POS) tagging, the second stage processes the unstructured text with stemming  ...  Hence, we divide our framework to three main stages; opinion collection (extraction), unstructured text processing and polarity classification.  ...  The sentence classification applies when the polarity of sentence level is crucial while classification on document level matters for overall and general polarity.  ... 
doi:10.5281/zenodo.1336261 fatcat:uomgf335pvcf7hjy4ambiiclsy


А. Mukasheva
2021 Scientific Journal of Astana IT University  
There are three levels of classifications: classification at the text level, at the level of a sentence, and at the aspect level of the object.  ...  After classifying the text at the desired level, the next task is to extract structured data from unstructured information. The problem can be solved using the five-tuple method.  ...  Converting unstructured text to structured data The next task is to structure the information. That is, in computational linguistics, texts written in human language are considered unstructured.  ... 
doi:10.37943/aitu.2021.57.68.005 fatcat:goolqgtddjefvfdpv6efjlgexa

Event Extraction from Unstructured Amharic Text

Ephrem Tadesse, Rosa Tsegaye, Kuulaa Qaqqabaa
2020 International Conference on Language Resources and Evaluation  
Event extraction has been done on different languages text but not on one of the Semitic language, Amharic. In this study, we present a system that extracts an event from unstructured Amharic text.  ...  In information extraction, event extraction is one of the types that extract the specific knowledge of certain incidents from texts.  ...  Because of this prominent significance of extracting events from unstructured Amharic text for high level Natural Lan-guage Processing (NLP) tasks we are interested to tackle this problem.  ... 
dblp:conf/lrec/TadesseTQ20 fatcat:orbqiykikzcbvcgh66cbd4qtfi

Event Detection and Classification in Hungarian Natural Texts

Zoltan Subecz
2019 European Scientific Journal  
The detection and analysis of events in natural language texts plays an important role in several NLP applications such as summarization and question answering.  ...  This paper focuses on introducing a machine learningbased approach that can detect and classify verbal and infinitival events in Hungarian texts.  ...  In order to exploit this unstructured data, machine learning and text mining techniques can be used to recognize events.  ... 
doi:10.19044/esj.2019.v15n21p411 fatcat:hc5sbcr2hjbnvois53bx2vsw3y

idrbt-team-a@IECSIL-FIRE-2018 : Relation Categorization for Social Media News Text

N. Satya Krishna, S. Nagesh Bhattu, Durvasula V. L. N. Somayajulu
2018 Forum for Information Retrieval Evaluation  
This working note presents a statistical based classifier for text classification using entity relationship information present in the input text.  ...  These features (POS tags, NE) along with the words, in input text sentence, are used as input features to classify the given input into any one of the predefined relationship class.  ...  In second stage we train a sentence level classifier and build the model by feeding training sentences along with features extracted in the previous stage.  ... 
dblp:conf/fire/KrishnaBS18 fatcat:b7aall44cfhajaays7fw2u5yua

Experiencer Detection and Automated Extraction of a Family Disease Tree from Medical Texts in Russian Language [chapter]

Ksenia Balabaeva, Sergey Kovalchuk
2020 Lecture Notes in Computer Science  
In order to find the facts about the right person (experiencer) and convert the unstructured medical text into structured information, we developed a module of experiencer detection.  ...  Text descriptions in natural language are an essential part of electronic health records (EHRs).  ...  In order to segment text parts describing family members, we have developed a module of binary sentence classification.  ... 
doi:10.1007/978-3-030-50423-6_45 fatcat:zwbiwdjpcvgkna5igjk3gkjjhm

Intelligent Opinion Mining and Sentiment Analysis Using Artificial Neural Networks [chapter]

Keith Douglas Stuart, Maciej Majewski
2015 Lecture Notes in Computer Science  
The paper proposes a method for classification of the text being examined based on the amount of positive, neutral or negative opinion it contains.  ...  This conceptual method for processing natural-language text enables a variety of analyses of the subjective content of texts.  ...  These in turn form phrases/clauses that form sentences that form texts.  ... 
doi:10.1007/978-3-319-26561-2_13 fatcat:kfomlex6hfcabdrjk2lyqxwyve
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