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Evolutionary algorithm based on different semantic similarity functions for synonym recognition in the biomedical domain

Lectures Hagenberg
2018 Figshare  
One of the most challenging problems in the semantic web field consists of computing the semantic similarity between different terms.  ...  In this article we propose a new approach which uses different existing semantic similarity methods to obtain precise results in the biomedical domain.  ...  As future work, we propose to explore further possibilities for synonym recognition in other domains.  ... 
doi:10.6084/m9.figshare.6839297.v1 fatcat:tmrwo2zmgvg2jotfmongcyrzje

Evolutionary algorithm based on different semantic similarity functions for synonym recognition in the biomedical domain

José M. Chaves-González, Jorge Martínez-Gil
2013 Knowledge-Based Systems  
Specifically, we have developed an evolutionary algorithm which uses information provided by different semantic similarity metrics.  ...  In this article we propose a new approach which uses different existing semantic similarity methods to obtain precise results which are very close to human judgments in the biomedical domain.  ...  As future work, we propose to explore further possibilities for synonym recognition in other domains.  ... 
doi:10.1016/j.knosys.2012.07.005 fatcat:6r5fsqe4s5gzrcu2ct4wmijlva

A Study on Some Tasks, Corpus and Resources of Medical Information Retrieval

P. Gayathri, N. Jaisankar
2016 Indian Journal of Science and Technology  
Applications/Improvements: Improvements in retrieval results is achieved by using context-aware keywords as indexing keywords and highly robust hybrid evolutionary algorithm based ranking function for  ...  Conventional ranking functions fail to capture the inherent features of natural language text. Evolutionary algorithm based ranking can enhance the retrieval performance.  ...  Some researchers have designed evolutionary algorithm based ranking functions for enhancing the performance of the retrieval system.  ... 
doi:10.17485/ijst/2016/v9i25/86655 fatcat:ghsig6x4zvgrnbf7xa662hbsoe

OMIT: Dynamic, Semi-Automated Ontology Development for the microRNA Domain

Jingshan Huang, Jiangbo Dang, Glen M. Borchert, Karen Eilbeck, He Zhang, Min Xiong, Weijian Jiang, Hao Wu, Judith A. Blake, Darren A. Natale, Ming Tan, Franca Fraternali
2014 PLoS ONE  
Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem.  ...  Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes.  ...  Acknowledgments The authors would like to thank Dr. Jeffrey Todd McDonald and Ms. Leyue Wang for their help in the project.  ... 
doi:10.1371/journal.pone.0100855 pmid:25025130 pmcid:PMC4099014 fatcat:hsy3rgtu7bb7vkrtu3nv6k3fee

Concept-based annotation of enzyme classes

O. Hofmann, D. Schomburg
2005 Bioinformatics  
False positives could be removed by a variety of filters including minimum number of co-occurrences, removal of sentences containing a negation and the classification of sentences based on their semantic  ...  Phrases in the abstracts were assigned to concepts from the Unified Medical Language System (UMLS) utilizing the MetaMap program, allowing for the identification of disease-related concepts by their semantic  ...  Finally, we would like to thank the Semantic Knowledge Representation Group for making the MetaMap software available and for their help with any questions.  ... 
doi:10.1093/bioinformatics/bti284 pmid:15661799 fatcat:zx5bunzib5d2nnjdoselc7poce

Boosting drug named entity recognition using an aggregate classifier

Ioannis Korkontzelos, Dimitrios Piliouras, Andrew W. Dowsey, Sophia Ananiadou
2015 Artificial Intelligence in Medicine  
Objective: Drug named entity recognition (NER) is a critical step for complex biomedical NLP tasks such as the extraction of pharmacogenomic, pharmacodynamic and pharmacokinetic parameters.  ...  In this study, we improve the performance of drug NER without relying exclusively on manual annotations.  ...  It was also facilitated by the Manchester Biomedical Research Centre and the NIHR Greater Manchester Comprehensive Local Research Network. We would like to thank Prof.  ... 
doi:10.1016/j.artmed.2015.05.007 pmid:26116947 fatcat:j7ntzew4trepdbkmoanpdtihdq

Empirical distributional semantics: Methods and biomedical applications

Trevor Cohen, Dominic Widdows
2009 Journal of Biomedical Informatics  
In this paper, we review the available methodologies for derivation of semantic relatedness from free text, as well as their evaluation in a variety of biomedical and other applications.  ...  Over the past 15 years, a range of methods have been developed that are able to learn human-like estimates of the semantic relatedness between terms from the way in which these terms are distributed in  ...  The authors would like to acknowledge Google, Inc. for their support of author DW's ongoing research on the subject.  ... 
doi:10.1016/j.jbi.2009.02.002 pmid:19232399 pmcid:PMC2750802 fatcat:ehih5ybxqffbbpw4xjkihel3fm

What Is Computational Intelligence and Where Is It Going? [chapter]

Włodzisław Duch
2007 Studies in Computational Intelligence  
In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions  ...  A brief survey of the scope of CI journals and books with "computational intelligence" in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary  ...  Broad foundations for CI that go beyond pattern recognition need to be constructed, including solving problems related to the higher cognitive functions (see [27] , this volume).  ... 
doi:10.1007/978-3-540-71984-7_1 fatcat:nunojdsotzd3jfljtffejg6kz4

A Hybrid Document Features Extraction with Clustering based Classification Framework on Large Document Sets

S Anjali Devi, S Siva
2020 International Journal of Advanced Computer Science and Applications  
In this work, a hybrid document clustering similarity index is optimized to find the essential key document clusters based on the contextual keywords.  ...  Experimental results are conducted on different datasets, it is noted that the proposed document clustering-based classification model has high true positive rate, accuracy and low error rate than the  ...  Different evolutionary approaches such as genetic algorithms, Rough-set, SVM, etc. are used to classify the document sets from large corpus.  ... 
doi:10.14569/ijacsa.2020.0110748 fatcat:n4syo3e2mfdjtakvg6jmz2qswe

A system for knowledge management in bioinformatics

Sudeshna Adak, Vishal S. Batra, Deo N. Bhardwaj, P. V. Kamesam, Pankaj Kankar, Manish P. Kurhekar, Biplav Srivastava
2002 Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02  
We address this problem in a comprehensive system for knowledge management in bioinformatics called e2e.  ...  To the biologist or biological applications, e2e exposes a common semantic view of inter-relationship among biological concepts in the form of an XML representation called eXpressML, while internally,  ...  For example, hierarchical clustering [6] has been used to determine the functions of gene clusters in regulating cell-cycle in yeast. e2e provides a platform for integrating algorithms made available  ... 
doi:10.1145/584792.584905 dblp:conf/cikm/AdakBBKKKS02 fatcat:ueh36lhoeng6zpsvzqbayn56sq

Recent advances in methods of lexical semantic relatedness – a survey

ZIQI ZHANG, ANNA LISA GENTILE, FABIO CIRAVEGNA
2012 Natural Language Engineering  
It is recognised that a fundamental task in Information Extraction is Named Entity Recognition, the goals of which are identifying references of named entities in unstructured documents, and classifying  ...  them into pre-defined semantic categories.  ...  Research in the biomedical domain generally prefers biomedical knowledge bases.  ... 
doi:10.1017/s1351324912000125 fatcat:b62qbqwrqfaf3gytw22yktc5ae

Neurocognitive Informatics Manifesto [article]

Włodzisław Duch
2021 arXiv   pre-print
Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still  ...  beyond the reach of machines.  ...  All these biologically inspired algorithms are used for similar applications, although the time-scales of evolutionary, behavioral and immunological processes are very different, and the type of intelligence  ... 
arXiv:2101.03609v1 fatcat:newlygw52vfytmfxtvtlzrohju

A literature review on the state-of-the-art in patent analysis

Assad Abbas, Limin Zhang, Samee U. Khan
2014 World Patent Information  
The literature review will be helpful for the researchers in finding the latest research efforts pertaining to the patent analysis in a unified form.  ...  The rapid growth of patent documents has called for the development of sophisticated patent analysis tools.  ...  Acknowledgments The authors are thankful to Saif-ur-Rehman Malik, Ahmad Fayyaz, and Saeeda Usman for the valuable reviews, suggestions, and comments.  ... 
doi:10.1016/j.wpi.2013.12.006 fatcat:prs6spbuhfd6lheiocbw5jz3di

An Unsupervised Text Mining Method for Relation Extraction from Biomedical Literature

Changqin Quan, Meng Wang, Fuji Ren, Gajendra P. S. Raghava
2014 PLoS ONE  
The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations.  ...  Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs  ...  Conceived and designed the experiments: CQ FR. Performed the experiments: CQ MW. Analyzed the data: CQ MW. Contributed reagents/materials/analysis tools: CQ. Wrote the paper: CQ MW.  ... 
doi:10.1371/journal.pone.0102039 pmid:25036529 pmcid:PMC4103846 fatcat:nql5b24dbjho7emus6hcdavpdy

New Challenges for Biological Text-Mining in the Next Decade

Hong-Jie Dai, Yen-Ching Chang, Richard Tzong-Han Tsai, Wen-Lian Hsu
2010 Journal of Computer Science and Technology  
These challenges must be overcome in order for text-mining to be more effective.  ...  As a result, recent biology contests, notably JNLPBA and BioCreAtIvE, have focused on evaluating various methods in which the literature may be navigated.  ...  The named entity recognition (NER) task in the biomedical domain has different characteristics from that in the newswire domain, such as the MUC-7 NER task [22] .  ... 
doi:10.1007/s11390-010-9313-5 fatcat:tuhnhtzeabdjzdaa4rjpsnkwsy
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