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Semantic classifier approach to document classification [article]

Piotr Borkowski and Krzysztof Ciesielski and Mieczysław A. Kłopotek
2017 arXiv   pre-print
We demonstrate its superiority over classical text classification approaches, including traditional classifier ensembles.  ...  The method consists in combining a document categorization technique with a single classifier or a classifier ensemble (SEMCOM algorithm - Committee with Semantic Categorizer).  ...  Semantic approach (in its base, unsupervised setting) could be tested also for clustering tasks under semantic gap scenario as well as to mixtures of classification and clustering.  ... 
arXiv:1701.04292v1 fatcat:lzwwf3l3rzhr3ovuqzfwrwgx2u

Use of semantic features to classify patient smoking status

Patrick J McCormick, Noémie Elhadad, Peter D Stetson
2008 AMIA Annual Symposium Proceedings  
The recent i2b2 NLP Challenge smoking classification task offers a rare chance to compare different natural language processing techniques on actual clinical data.  ...  We compare the performance of a classifier which relies on semantic features generated by an unmodified version of MedLEE, a clinical NLP engine, to one using lexical features.  ...  Thank you to Carol Friedman for the use of the MedLEE system (R01 LM007659 and R01 LM008635). Thank you to Özlem Uzuner of i2b2 for granting access to the smoking data used in this study.  ... 
pmid:18998969 pmcid:PMC2655942 fatcat:grv7cykmzzdudi6f3tjx3jkdbm

Semantic Similarity Strategies for Job Title Classification [article]

Yun Zhu, Faizan Javed, Ozgur Ozturk
2016 arXiv   pre-print
To improve classification accuracy and effectiveness, we experiment with various semantic representation strategies such as average W2V vectors and document similarity measures such as Word Movers Distance  ...  In the online recruitment domain, we refer to classifying job ads to pre-defined or custom occupation categories as job title classification.  ...  A semantic enrichment approach to job title classification is discussed in [8] .  ... 
arXiv:1609.06268v1 fatcat:weyapdfp2raejl374nfjdjmgpi

Reduction of Search Space in Restful Service Discovery

G. Venugopal, P. Radhika Raju, A. Ananda Rao
2019 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
TASSIC approach will search the semantic characteristics of search and match interface terms in the service document.  ...  This approach is meant for increasing search precision in the retrieval and quick search for classifying their RESTful services or Api according to user-defined criteria.  ...  Its prepared inputs to new service classification approach to Service document and query document before the experiment.  ... 
doi:10.32628/cseit195430 fatcat:3rb2fxtygzbt5ngcrx5uv7fi3u

Enriching Ontologies with Encyclopedic Background Knowledge for Document Indexing [chapter]

Lisa Posch
2014 Lecture Notes in Computer Science  
The proposed approach aims to exploit this information for improving both ontology-based methods for classifying and indexing documents and methods based on supervised machine learning.  ...  Due to the time consuming and tedious nature of manual classification and indexing, there is a need for better methods to automate this process.  ...  proposed approach for classifying and indexing documents using encyclopedic background knowledge.  ... 
doi:10.1007/978-3-319-11915-1_36 fatcat:tlxxzhwivzgzrhseieect3zqf4

Enhancing Sensitivity Classification with Semantic Features Using Word Embeddings [chapter]

Graham McDonald, Craig Macdonald, Iadh Ounis
2017 Lecture Notes in Computer Science  
in classification effectiveness, correctly classifying 9.99% more sensitive documents compared to the text classification baseline.  ...  Government documents must be reviewed to identify any sensitive information they may contain, before they can be released to the public.  ...  Acknowledgements The authors are thankful to the Foreign & Commonwealth Office and The National Archives of the UK for their support of this work.  ... 
doi:10.1007/978-3-319-56608-5_35 fatcat:w7t4zeamkbadbgyni7pmefps4u

Novel Unsupervised Features for Czech Multi-label Document Classification [chapter]

Tomáš Brychcín, Pavel Král
2014 Lecture Notes in Computer Science  
Another interesting contribution is that these two semantic spaces have never been used in the context of document classification before.  ...  The proposed approaches are evaluated on a Czech newspaper corpus. We experimentally show that almost all proposed features significantly improve the document classification score.  ...  We also would like to thank Czech New Agency (ČTK) for support and for providing the data.  ... 
doi:10.1007/978-3-319-13647-9_8 fatcat:heooyb77lnch7bkfherzecelea

Towards Robust Text Classification with Semantics-Aware Recurrent Neural Architecture

Blaž Škrlj, Jan Kralj, Nada Lavrač, Senja Pollak
2019 Machine Learning and Knowledge Extraction  
The experiments show that the proposed approach outperforms the approach without semantic knowledge, with highest accuracy gain (up to 10%) achieved on short document fragments.  ...  This paper presents an efficient semantic text mining approach, which converts semantic information related to a given set of documents into a set of novel features that are used for learning.  ...  In text mining, document classification refers to the task of classifying a given text document into one or more categories based on its content [2] .  ... 
doi:10.3390/make1020034 fatcat:o6bjp46cljdj3kng2kxsfvvzei

Ontology-Concepts Weighting for Enhanced Semantic Classification of Documents

Salam Fraihat
2016 International Journal of Innovative Computing, Information and Control  
This paper proposes a new semantic approach for documents classification.  ...  Automatic document classification has become increasingly important and difficult due to the large scale of the electronic documents used in the last years.  ...  document classification approach.  ... 
doi:10.24507/ijicic.12.02.519 fatcat:y22opoeqgbhbhgocf2afkzsnim

Sentence-Level and Document-Level Sentiment Mining for Arabic Texts

Noura Farra, Elie Challita, Rawad Abou Assi, Hazem Hajj
2010 2010 IEEE International Conference on Data Mining Workshops  
For document-level classification, we use sentences of known classes to classify whole documents, using a novel approach whereby documents are divided dynamically into chunks and classification is based  ...  Finally, we propose a hierarchical classification scheme that uses the results of the sentence-level classifier as input to the documentlevel classifier, an approach which has not been investigated previously  ...  We used the known (correct) sentence classes as input to a document classifier and considered the semantic contribution of different chunks in the document.  ... 
doi:10.1109/icdmw.2010.95 dblp:conf/icdm/FarraCAH10 fatcat:3fbfahbo4zg75bkwe5uk36vv34

Optimizing Support Vector Machine Classification Based on Semantic-Text Knowledge Enrichment

Mr. Shadi Diab, Mr. Nasim Hamaydeh
2019 Zenodo  
We propose using semantic-knowledge enrichment scheme to inject new concepts into the original contents of the text documents.  ...  In this research, we enhanced the performance of Support Vector Machine (SVM) in text classification by applying semantic-knowledge enrichment.  ...  IV.Injecting Semantic-Knowledge Background Our approach to enrich the text document is by injecting powerful related concepts into the document prior to performing training on the classifier.  ... 
doi:10.5281/zenodo.2576351 fatcat:cvvpr7aeeve6lhkah6uebh5aka

Semantic Ontology-Based Approach to Enhance Arabic Text Classification

Ahmad Hawalah
2019 Big Data and Cognitive Computing  
We rely in this study on the vector space model (term frequency-inverse document frequency (TF-IDF)) as well as the cosine similarity approach to classify new Arabic textual documents.  ...  Text classification is a process of classifying textual contents to a set of predefined classes and categories.  ...  to improve the classification approach by taking advantage of the semantic information in ontologies.  ... 
doi:10.3390/bdcc3040053 fatcat:y573mco2yvhypbvfncahatfwym

Optimizing support vector machine based classification and retrieval of semantic video events with genetic algorithms

Bashar Tahayna, Mohammed Belkhatir, Saadat M. Alhashmi, Thomas O'Daniel
2010 2010 IEEE International Conference on Image Processing  
IV.Injecting Semantic-Knowledge Background Our approach to enrich the text document is by injecting powerful related concepts into the document prior to performing training on the classifier.  ...  The text classification task requires a given set of classes and a learning model to classify new unseen documents based on the learned process [1] .  ...  time of the original dataset before applying our proposed approach.  ... 
doi:10.1109/icip.2010.5653724 dblp:conf/icip/TahaynaBAO10 fatcat:lg7rblx775ejhc64d3eodlqbee

Optimizing Support Vector Machine Classification Based on Semantic-Text Knowledge Enrichment

Mr. Shadi Diab, Mr. Nasim Hamaydeh
2019 Zenodo  
We propose using semantic-knowledge enrichment scheme to inject new concepts into the original contents of the text documents.  ...  In this research, we enhanced the performance of Support Vector Machine (SVM) in text classification by applying semantic-knowledge enrichment.  ...  Semantic-Text Knowledge Enrichment Mr. Shadi Diab Mr. Nasim Hamaydeh time of the original dataset before applying our proposed approach.  ... 
doi:10.5281/zenodo.2582947 fatcat:nwaj57vkffcb3ehp7uaolbqkte

Dynamic Classification for Web Documents Using Semantic Knowledge (DBpedia)

Passent Elkafrawy, Dina Eldemerdash
2018 The Egyptian Journal of Language Engineering  
Currently, most approaches to text classification represent document as (bag of words) and training the large set of documents to train the classifier.  ...  we present a dynamic Web document Classification using semantic knowledge (DBpedia). We present a method for a dynamic Web document Classification and automatic classification.  ...  SEMANTIC CLASSIFICATION FOR WEB DOCUMENTS This paper aims to present a semantic classification system that classifies web documents by a semantic approach based on the DBpedia Ontology.  ... 
doi:10.21608/ejle.2018.59345 fatcat:sjnl7hvegfhqbefam2v5eegxg4
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