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Open Information Extraction on Scientific Text: An Evaluation [article]

Paul Groth and Michael Lauruhn and Antony Scerri and Ron Daniel Jr
2018 arXiv   pre-print
Open Information Extraction (OIE) is the task of the unsupervised creation of structured information from text.  ...  In this article, we evaluate the performance of OIE on scientific texts originating from 10 different disciplines.  ...  The work presented here provides an independent evaluation of these tools in their use on scientific text.  ... 
arXiv:1802.05574v2 fatcat:g354xnerxrch7geekdkmuml3rm

Evaluating an intelligent diagnosis system of historical text comprehension

Grammatiki Tsaganou, Maria Grigoriadou, Theodora Cavoura, Dimitra Koutra
2003 Expert systems with applications  
The evaluation results are encouraging for the system's educational impact on learners and for future work concerning an intelligent educational system for individualized learning.  ...  The system was also evaluated for its behavior when using two different historical texts.  ...  In section 5, we focus on the evaluation by human experts of system's diagnosis accuracy and of its performance when using a new historical text.  ... 
doi:10.1016/s0957-4174(03)00090-3 fatcat:56rd5jxbevcijgvbu5newahgbe

An open-source framework for large-scale, flexible evaluation of biomedical text mining systems

William A Baumgartner, K Bretonnel Cohen, Lawrence Hunter
2008 Journal of Biomedical Discovery and Collaboration  
Results: Our evaluation framework was assembled using the Unstructured Information Management Architecture.  ...  of such an evaluation framework for promoting collaboration between developers of biomedical language processing technologies.  ...  See the accompanying README file for instructions on installation and use.  ... 
doi:10.1186/1747-5333-3-1 pmid:18230184 pmcid:PMC2276192 fatcat:xest7iswrzh43mfsdltfasm77a

Layout-aware text extraction from full-text PDF of scientific articles

Cartic Ramakrishnan, Abhishek Patnia, Eduard Hovy, Gully APC Burns
2012 Source Code for Biology and Medicine  
Conclusions: LA-PDFText is an open-source tool for accurately extracting text from full-text scientific articles. The release of the system is available at  ...  that use published literature as an information source.  ...  It should be noted that the evaluation of text extraction was done on full text of papers explicitly to contrast LA-PDFText with PDF2Text.  ... 
doi:10.1186/1751-0473-7-7 pmid:22640904 pmcid:PMC3441580 fatcat:jmgj5wso5jbjjhsohxtd4dwram

ADE Eval: An Evaluation of Text Processing Systems for Adverse Event Extraction from Drug Labels for Pharmacovigilance

Samuel Bayer, Cheryl Clark, Oanh Dang, John Aberdeen, Sonja Brajovic, Kimberley Swank, Lynette Hirschman, Robert Ball
2020 Drug Safety  
Two metrics modeled the experiences of FDA safety evaluators: one measured the ability of an algorithm to identify correct Medical Dictionary for Regulatory Activities (MedDRA®) terms for the text from  ...  the annotated corpora, and the other assessed the quality of evidence extracted from the corpora to support the selected MedDRA® term by measuring the portion of annotated text an algorithm correctly  ...  to extract information from a variety of textual sources, including scientific literature, EHRs, patents, news feeds, clinical trials data, and proprietary content; and • MetaMap [7] , an NLP-based system  ... 
doi:10.1007/s40264-020-00996-3 pmid:33006728 pmcid:PMC7813736 fatcat:ov6rytfn5naoragwaaesk7urbi

Text stream processing

Dunja Mladenić, Marko Grobelnik, Blaž Fortuna, Delia Rusu
2012 Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics - WIMS '12  
Open Information Extraction using Wikipedia. ACL 2010.  ...  Identifying Relations for Open Information Extraction. EMNLP 2011. A. Fader, S. Soderland O. Etzioni. Identifying Relations for Open Information Extraction. EMNLP 2011.  ... 
doi:10.1145/2254129.2254138 dblp:conf/wims/MladenicGFR12 fatcat:tjkukeyxg5cthcgyaulvxw3agm

The Feasibility of Automated Topic Analysis: An Empirical Evaluation of Deep Learning Techniques Applied to Skew-Distributed Chinese Text Classification

Yuen-Hsien Tseng
2020 Journal of Educational Media & Library Sciences  
Text classification (TC) is the task of assigning predefined categories (or labels) to texts for information organization, knowledge management, and many other applications.  ...  ML techniques on five skew-distributed datasets (four in Chinese, and one in English for comparison).  ...  Empirical Evaluation of DeepLearning Techniques Applied to Skew-Distributed Text Classification," Proceedings of the International Conference on Library and Information Science (ICLIS), pp. ψ deep  ... 
doi:10.6120/joemls.202003_57(1) doaj:888d8b6c9630437888b4b2c36ffcf663 fatcat:fydfewsk5jhjlkadsokrh4x2za

An evaluation of Bradfordizing Effects

Philipp Mayr
2008 Collnet Journal of Scientometrics and Information Management  
An evaluation of the method and its effects is carried out in two laboratorybased information retrieval experiments (CLEF and KoMoHe) using a controlled document corpus and human relevance assessments.  ...  The purpose of this paper is to apply and evaluate the bibliometric method Bradfordizing for information retrieval (IR) experiments.  ...  CLEF evaluation 2003-2007 and our assisting student Dirk Hohmeister who helped with the assessments and analysis.  ... 
doi:10.1080/09737766.2008.10700850 fatcat:s2mnwdvgbnd4ro5v7ujflictri

An evaluation of two approaches for teaching reading comprehension strategies in the primary years using science information texts

D. Ray Reutzel, John A. Smith, Parker C. Fawson
2005 Early Childhood Research Quarterly  
in four second-grade classrooms using science information texts.  ...  as measured by a standardized test of reading comprehension, recall of main ideas from reading two 200 word passages from information texts, a reading motivation survey and a strategy use survey.  ...  information book and from one novel or not-previously read (unfamiliar) information book was an informal measure of student comprehension.  ... 
doi:10.1016/j.ecresq.2005.07.002 fatcat:btzc7zeti5fpplw26t5jd3iymm

Text Extraction from Image using Python

T.Gnana Prakash, K. Anusha
2017 International Journal of Trend in Scientific Research and Development  
With so much of our lives computerized, it is vitally important that machines and humans can understand one another and pass information back and forth.  ...  However, when it comes to processing more human kinds of information, like an old-fashioned printed book or a letter scribbled with a fountain pen, computers have to work much harder.  ...  The problem of Text Information Extraction TIE system receives an input in the form of a still image or a sequence of images.  ... 
doi:10.31142/ijtsrd2501 fatcat:itujgokbnnhbzok2dl6obcs64e

Text mining for systems biology

Juliane Fluck, Martin Hofmann-Apitius
2014 Drug Discovery Today  
Initially focusing on finding and extracting information from PubMed abstracts, text-mining technology has advanced with impressive speed and is focusing increasingly on the extraction of complex biological  ...  Text mining technologies for the automated extraction of useful biomedical information from unstructured text that can be directly used for systems biology modelling have been substantially improved over  ...  In this article, we briefly review the current state of automated named entity and relation extraction from scientific text, and shed light on the types of information needed for the above-mentioned modelling  ... 
doi:10.1016/j.drudis.2013.09.012 pmid:24070668 fatcat:ajnerehdqndv5nk3l6jak42n5e

Word-level Text Highlighting of Medical Texts forTelehealth Services [article]

Ozan Ozyegen, Devika Kabe, Mucahit Cevik
2021 arXiv   pre-print
Three different word-level text highlighting methodologies are implemented and evaluated. The first method uses TF-IDF scores directly to highlight important parts of the text.  ...  The medical domain is often subject to information overload.  ...  Medical professionals and researchers rely on information from many resources such as clinical notes and scientific literature to accomplish their work.  ... 
arXiv:2105.10400v1 fatcat:d2ohoug33nb4zashp77azwejki

Evaluating Automatic Speaker Recognition systems: An overview of the NIST Speaker Recognition Evaluations (1996-2014)

Joaquin Gonzalez-Rodriguez
2014 Loquens  
In the last 20 years, the US National Institute of Standards and Technology (NIST) has organized, providing the proper speech data and evaluation protocols, a series of text-independent Speaker Recognition  ...  In this paper, we outline how the evaluations progressively challenged the technology including new speaking conditions and sources of variability, and how the scientific community gave answers to those  ...  FLAVOURS IN AUTOMATIC SPEAKER RECOGNITION This section gives an introductory outlook of the different architectures and speaker information extraction components that can be used to build an automatic  ... 
doi:10.3989/loquens.2014.007 fatcat:km6fn6sx5jbmbnbvhn3ilkbsse

Networks and Shared Tasks in Clinical Text Mining [chapter]

Hercules Dalianis
2018 Clinical Text Mining  
In Fig. 11 .1 there is an overview of all ShARe/CLEF eHealth evaluation tasks from 2013 to 2016.  ...  Workshops as International Workshop on Health Text Mining and Information Analysis (Louhi) and the Biomedical Natural Language Processing (BioNLP) at both the Association for Computational Linguistics  ... 
doi:10.1007/978-3-319-78503-5_11 fatcat:bob7cb2zxvgffg6rqqj7gvbjee

Information Extraction from Text [chapter]

Jing Jiang
2012 Mining Text Data  
Information extraction is the task of finding structured information from unstructured or semi-structured text.  ...  It is an important task in text mining and has been extensively studied in various research communities including natural language processing, information retrieval and Web mining.  ...  Introduction Information extraction from text is an important task in text mining.  ... 
doi:10.1007/978-1-4614-3223-4_2 fatcat:4sdthex63rhi3kj2xerrh7v2p4
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