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Turning Dark Data Into Informed Content. Ai-Driven Scalable Document Classification For Today'S Enterprise Businesses
2018
Zenodo
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This is achieved by developing a modular system with a collection of subsystems that can be deployed and coordinated from a central source. ...
AIM: To design and implement a scalable and fault-tolerant production system that leverages existing and novel Machine Learning and Natural Language Processing techniques for document processing and classification ...
doi:10.5281/zenodo.1193230
fatcat:x4tus42anvahzluudzzzhz7jii
Cooperative and Fast-Learning Information Extraction from Business Documents for Document Archiving
[chapter]
2013
Lecture Notes in Computer Science
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Although current solutions for document classification and extraction work pretty well, they still require a high effort of on-site configuration done by domain experts or administrators. ...
such a system. ...
My special thanks to my colleagues for insightful discussions and careful prove reading and our project partners from DocuWare for providing us with the document corpus used for evaluation. ...
doi:10.1007/978-3-642-41033-8_4
fatcat:6lfzqf4xmjh6divigw3bamdu6m
Few-exemplar Information Extraction for Business Documents
english
2014
Proceedings of the 16th International Conference on Enterprise Information Systems
english
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to use a self-learning information extraction system. ...
Although current scientific and commercial self-learning solutions for document classification and extraction work pretty well, they still require a high effort of on-site configuration done by domain ...
We thank our project partners from DocuWare for insightful discussions and providing us with the document corpus used for evaluation. ...
doi:10.5220/0004946702930298
dblp:conf/iceis/EsserSMS14
fatcat:bqejw3cz2bdihk7k5ok5qis72a
Capsule Network on Font Style Classification
2020
Journal of Artificial Intelligence and Capsule Networks
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Capsule network is one among such algorithm and an emerging technique implemented for so many classification process with limited datasets. ...
that the proposed font style classification model based on CapsNet is classifying the images with better accuracy, F1 score and Gmean. ...
The CapsNet has the ability to learn the features with comparatively lesser samples required for convolution neural network and the ability to learn the features from an image is also excellent than the ...
doi:10.36548/jaicn.2020.2.001
fatcat:nobu654cpffb3jhx5ypcggrpme
Graph attention-driven document image classification through DualTune learning
2024
Indonesian Journal of Electrical Engineering and Computer Science
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Deep learning has become a pivotal tool for extracting and learning complex patterns. ...
This study presents a new approach to document image classification, named graph attention-driven with dual tune learning (GAD-DTL). GAD-DTL employs dual-tune learning and graph attention networks. ...
-We propose a novel approach, DualTune learning, for document image classification. ...
doi:10.11591/ijeecs.v33.i1.pp278-289
fatcat:erh7livuknf3nlcd4jgfxabufy
Challenges of Non-functional Requirements Extraction in Agile Software Development using Machine Learning
2021
International Journal of Computer Applications
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The automatic extraction and
and how we will elicit, document, and validate them. ...
The Naive software product, NFR needs to be extracted from
Bayes Classification method is a supervised learning method the requirements documents to be implemented.
that ...
doi:10.5120/ijca2021921835
fatcat:pqgv2sxlenejdj6o6imeosqfnu
Cognitive Approach in Document Indexing
2018
Eastern European Journal of Regional Studies
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The software can handle complex documents, in which the contents of different regions and fields can be highly heterogeneous with respect to layout, printing quality and the utilization of fonts and typing ...
Datum Solutions Cognitive Capture implements the automatic processing of administrative documents that need to be treated in a close to real time manner. ...
We employ a machine learning approach, whereby the system is first provided with a set of training documents in which the target fields are manually tagged, and automatically learns how to extract these ...
doaj:88af51e70b7740518ec328e031b516fe
fatcat:irimw43xvvgnfchiy3t66smbma
A System to Filter Unwanted Messages from Social Network User Walls
2017
IJIREEICE
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In order to make social network user wall a secured wall, introducing a rule based system wall as well as Machine Learning approach, neural text classification applied on user wall. ...
Users have ability to keep in touch with friends by exchanging different types of information or messages. Sometimes people post messages which may cause a serious problem to user's reputation. ...
Feature extraction/selection Classification Feature extraction / selection helps identify important words in a text document. ...
doi:10.17148/ijireeice.2017.5110
fatcat:numej4olq5e6bka4gikfgm62zm
A Dataset for Multi-lingual Epidemiological Event Extraction
2020
Zenodo
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DANIEL is a multilingual news surveillance system that leverages unique attributes associated with news reporting repetition and saliency, to extract events. ...
The system has a wide geographical and language coverage, including low-resource languages. ...
This can be attributed to their ability to automatically learn discriminating and reliable features from the text corpus. ...
doi:10.5281/zenodo.3693646
fatcat:kzlaeqfuljg7zmyxpzet2aemcu
Page 217 of SRELS Journal of Information Management Vol. 23, Issue 4
[page]
1986
SRELS Journal of Information Management
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, (including heuristics) learning and expert systems. ...
The feature extraction pro- blem involves conversion of the input into discrete features with attributes and properties more readily interpreted by the system. ...
Document vector extension for document classification
2023
AIP Conference Proceedings
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huge narrative datum .We also advance a wellorganized proposition for document delineation, by using clustering algorithms to split up a repository container into various sub-containers and initiate the ...
Set side by side to simple even models, the outcomes manifest that our model give-rise to finest document depictions for document-eminent division correspondence tasks. ...
ACKNOWLEDGEMENTS The authors would like to thank the Management, K.RAMAKRISHNAN COLLEGE OF ENGINEERING(AUTONOMOUS), SAMAYAPURAM, TRICHY, INDIA, for their continuousencouragement and support. ...
doi:10.1063/5.0173197
fatcat:a6mlqqhjcrg4xglnww7svmhaga
novel deep neural network framework for biomedical named entity recognition
2022
International Journal of Health Sciences
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Biomedical Named Entity Recognition (BNER) gets more and more attention from the researchers since it is a fundamental task in biomedical information extraction. ...
With the dramatic improvements in the field of bio-informatics, extracting information from text and analyzing the association between the entities has received more attention in the past few years. ...
information along with word embedding and character embedding as the features along with Conditional Random field(CRF) to improve the performance of Bio-NER system. ...
doi:10.53730/ijhs.v6ns5.9557
fatcat:pzmgdcgg7fcploqwjz7otidi5q
A Study on Emotion Analysis for Online Learning Based on Students' Feedback via Social Networks
2023
Data Analytics and Artificial Intelligence
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Now a dayse-Learning system familiar for the virtual class room environment and learners free to learn at their own pace and to define personal learning path based on their individual needs and interests ...
Educational Data mining (EDM) in e-Learning systems is a rapidly growing phenomenon. It's used to improve education by monitoring student performance and trying to understand the students' learning. ...
CONCLUSION E-Learning is known as learning management system. E-Learning offers the ability to share material in all kinds of formats such as videos, slideshows, word documents and PDFs. ...
doi:10.46632/daai/3/2/2
fatcat:w3v4sbidzbhr5f56k5igb6caia
Multi-Label Classification of Product Reviews Using Structured SVM
2015
International Journal of Artificial Intelligence & Applications
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The feature extraction and classification of such text documents require an efficient machine learning algorithm which performs automatic text classification. ...
The real challenge in the multi-label classification is the labelling of large number of text documents with a subset of class categories. ...
The learning phase of the specified method involves the feature extraction of text documents and the training of the system with an appropriate machine learning technique. ...
doi:10.5121/ijaia.2015.6306
fatcat:xhb2gcchp5blrmq5xjgw6xkpdu
Arabic Document Classification by Deep Learning
2021
International Journal of Advanced Computer Science and Applications
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The main goal of using deep learning is its ability to automatically extract useful features from images, which eliminates the need for a manual feature extraction process. ...
For the document image classification, we used VGG16 convolutional layers, ran the dataset through them, and then trained a classifier on top of it. ...
The authors, therefore, acknowledge with thanks the University of Jeddah technical and financial support. ...
doi:10.14569/ijacsa.2021.0121034
fatcat:nu7rdhnqirai5cpsnra7jfgmvm
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