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Background and overview for KDD Cup 2002 task 1

Alexander Yeh, Lynette Hirschman, Alexander Morgan
2002 SIGKDD Explorations  
This paper presents a background and overview for task 1 (of 2 tasks) of the KDD Challenge Cup 2002, a competition held in conjunction with the ACM SIGKDD International Conference on Knowledge Discovery  ...  and Data Mining (KDD), July 23-26, 2002.  ...  In addition, many people at FlyBase worked to make this KDD Cup task possible, especially William Gelbart, Beverly Matthews, Leyla Bayraktaroglu, David Emmert and Don Gilbert.  ... 
doi:10.1145/772862.772873 fatcat:kwszbslaqregtf5y4njqvzmgru

Overview of BioCreAtIvE: critical assessment of information extraction for biology

Lynette Hirschman, Alexander Yeh, Christian Blaschke, Alfonso Valencia
2005 BMC Bioinformatics  
The goal of the first BioCreAtIvE challenge (Critical Assessment of Information Extraction in Biology) was to provide a set of common evaluation tasks to assess the state of the art for text mining applied  ...  The first dealt with extraction of gene or protein names from text, and their mapping into standardized gene identifiers for three model organism databases (fly, mouse, yeast).  ...  Acknowledgements The work of AV and CB was funded by the European Commission as part of the E-BioSci and ORIEL projects, contract numbers QLRI-CT  ... 
doi:10.1186/1471-2105-6-s1-s1 pmid:15960821 pmcid:PMC1869002 fatcat:kktugbhkrzgwvnnwuo7jxszkaq

TREC genomics special issue overview

William Hersh, Ellen Voorhees
2008 Information retrieval (Boston)  
The track also appreciated the help of Lori Buckland and others at NIST for help in its administration.  ...  We were also very grateful to the National Library of Medicine, Highwire Press, and the Mouse Genome Informatics Project for providing data for use in the track.  ...  More recently, challenge evaluations have been initiated for researchers interested in information extraction (IE) (Hirschman et al. 2002) , including the Knowledge Discovery from Databases (KDD) Cup  ... 
doi:10.1007/s10791-008-9076-6 fatcat:e36xnnbro5eqvkmmm7x4rxj2mu

Overview of the BioCreative III Workshop

Cecilia N Arighi, Zhiyong Lu, Martin Krallinger, Kevin B Cohen, W Wilbur, Alfonso Valencia, Lynette Hirschman, Cathy H Wu
2011 BMC Bioinformatics  
This special issue contains overview papers for the three tasks of BioCreative III.  ...  Ten teams participated in the PPI article classification task (ACT) requiring a system to classify and rank a PubMed ® record as belonging to an article either having or not having "PPI relevant" information  ...  Author details 1 Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, USA. 2 National Center for Biotechnology Information, National Library of Medicine, Bethesda,  ... 
doi:10.1186/1471-2105-12-s8-s1 pmid:22151647 pmcid:PMC3269932 fatcat:lp7c4vnknraqrkganmnqt4hfse

Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge

Martin Krallinger, Alexander Morgan, Larry Smith, Florian Leitner, Lorraine Tanabe, John Wilbur, Lynette Hirschman, Alfonso Valencia
2008 Genome Biology  
In case of the protein-protein interaction task, the importance and difficulties of experimentally confirmed annotation extraction from full-text articles were explored, yielding different results depending  ...  In response, a range of text-mining and information-extraction tools have recently been developed specifically for the biological domain.  ...  This article has been published as part of Genome Biology Volume 9 Supplement 2, 2008: The BioCreative II -Critical Assessment for Information Extraction in Biology Challenge.  ... 
doi:10.1186/gb-2008-9-s2-s1 pmid:18834487 pmcid:PMC2559980 fatcat:oebtobhdtbfexgyrmymmy7o6vi

Biomedical Language Processing: What's Beyond PubMed?

Lawrence Hunter, K. Bretonnel Cohen
2006 Molecular Cell  
Computational tools that classify documents, extract factual information, generate summaries, and generally process human language are providing powerful new tools for staying on top of the torrent of  ...  , and the number of new entries in MEDLINE each year has grown at a compounded annual growth rate of ~3.1% (see Figure 1 ).  ...  Acknowledgements The authors thank Hao Chen, Hans-Michael Müller, and Parantu Shah for usage data; Lynne Fox for information on PubMed; MITRE's Biomedical Information Processing group for data on Drosophila  ... 
doi:10.1016/j.molcel.2006.02.012 pmid:16507357 pmcid:PMC1702322 fatcat:yqvaab5kvjcl5norxcrh7fbvdm

Rutabaga by any other name: extracting biological names

Lynette Hirschman, Alexander A. Morgan, Alexander S. Yeh
2002 Journal of Biomedical Informatics  
Information extraction has been an active area of research in natural language processing and there are promising results for information extraction applied to news stories, e.g., balanced precision and  ...  This article examines emerging techniques to access biological resources through extraction of entity names and relations among them.  ...  We analyzed the results under a number of different experimental conditions on a small corpus of 86 articles drawn at random from the larger corpus of 862 full text articles for the KDD Challenge Cup.  ... 
doi:10.1016/s1532-0464(03)00014-5 pmid:12755519 fatcat:4w2eigmhuzecvnpe76dj7uu2u4

Evaluation of BioCreAtIvE assessment of task 2

Christian Blaschke, Eduardo Leon, Martin Krallinger, Alfonso Valencia
2005 BMC Bioinformatics  
Information relating to functional descriptions is generally extracted manually from textual data and stored in biological databases to build up annotations for large collections of gene products.  ...  We report on task two which addressed the automatic extraction and assignment of Gene Ontology (GO) annotations of human proteins, using full text articles.  ...  In the domain of biomedical literature, the knowledge discovery and data mining (KDD) challenge cup [7] evaluated how text mining tools could aid in the process of database curation, in this case of  ... 
doi:10.1186/1471-2105-6-s1-s16 pmid:15960828 pmcid:PMC1869008 fatcat:2pbvytvsqjcdbivxu7yia6oyue

Creation of a new longitudinal corpus of clinical narratives

Vishesh Kumar, Amber Stubbs, Stanley Shaw, Özlem Uzuner
2015 Journal of Biomedical Informatics  
This paper details the process used to select records for this corpus and provides an overview of novel research uses for this corpus.  ...  The 2014 i2b2/UTHealth Natural Language Processing (NLP) shared task featured a new longitudinal corpus of 1,304 records representing 296 diabetic patients.  ...  OHSUMED: an interactive retrieval evaluation and new large test collection for research.. In: Bruce Croft, W.; van Rijsbergen, CJ., editors.  ... 
doi:10.1016/j.jbi.2015.09.018 pmid:26433122 pmcid:PMC4978168 fatcat:awxawdb3ujbqjoap6uaioxxwlm

Multi-dimensional classification of biomedical text: Toward automated, practical provision of high-utility text to diverse users

H. Shatkay, F. Pan, A. Rzhetsky, W. J. Wilbur
2008 Bioinformatics  
specific biomedical retrieval and extraction tasks.  ...  Motivation: Much current research in biomedical text mining is concerned with serving biologists by extracting certain information from scientific text.  ...  ACKNOWLEDGEMENTS We are grateful to the group of eight dedicated annotators for their efforts in producing the corpus. Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btn381 pmid:18718948 pmcid:PMC2530883 fatcat:fckcbutwsfb7zore25m4jel5jy

Enhancing navigation in biomedical databases by community voting and database-driven text classification

Timo Duchrow, Timur Shtatland, Daniel Guettler, Misha Pivovarov, Stefan Kramer, Ralph Weissleder
2009 BMC Bioinformatics  
well with concurrent change events, and can be adapted to add text classification capability to other biomedical databases.  ...  The breadth of biological databases and their information content continues to increase exponentially. Unfortunately, our ability to query such sources is still often suboptimal.  ...  We also thank Vladimir Morozov and Gabriel Berriz for helpful discussions. We thank the anonymous reviewers for their comments, and the PepBank user community for support and valuable feedback.  ... 
doi:10.1186/1471-2105-10-317 pmid:19799796 pmcid:PMC2768718 fatcat:kgmpbf7j7naw3hion45q2b372a

Challenges for automatically extracting molecular interactions from full-text articles

Tara McIntosh, James R Curran
2009 BMC Bioinformatics  
It is an invaluable case study providing guidance to developers of biomedical IR and IE systems, and can be used as a gold-standard evaluation set for full-text IR tasks.  ...  However, most Information Retrieval (IR) and Extraction (IE) tools currently process only abstracts.  ...  Acknowledgements This work was supported by the CSIRO ICT Centre and Australian Research Council Discovery grants DP0453131 and DP0665973.  ... 
doi:10.1186/1471-2105-10-311 pmid:19778419 pmcid:PMC2761905 fatcat:s6wm264gxjcw7ltw64lny5on2a

A Survey of Utility-Oriented Pattern Mining

Wensheng Gan, Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Vincent Tseng, Philip Yu
2019 IEEE Transactions on Knowledge and Data Engineering  
UPM is a vital task, with numerous high-impact applications, including cross-marketing, e-commerce, finance, medical, and biomedical applications.  ...  This survey aims to provide a general, comprehensive, and structured overview of the state-ofthe-art methods of UPM.  ...  INTRODUCTION D ATA mining [1] , [2] focuses on extraction of information from a large set of data and transforms it into an easily interpretable structure for further use.  ... 
doi:10.1109/tkde.2019.2942594 fatcat:nipxkmyfb5cyxh2662xbz6feo4

A Wide Scale Classification of Class Imbalance Problem and its Solutions: A Systematic Literature Review

Gillala Rekha, Amit Kumar Tyagi, V. Krishna Reddy
2019 Journal of Computer Science  
This article presents a systematic literature review and analyze the results of more than 400 research  ...  If prediction is performed by these learning algorithms on imbalanced data, the accuracy will be high for majority classes, i.e., resulting in poor performance.  ...  The authors would like to thank Koneru Lakshmaiah Education Foundation and AARIN, India, an education foundation body and a research network for supporting the project through its financial assistance.  ... 
doi:10.3844/jcssp.2019.886.929 fatcat:cg3x36g4rzhybi7xzca6rfyaqi

Summarization from medical documents: a survey

Stergos Afantenos, Vangelis Karkaletsis, Panagiotis Stamatopoulos
2005 Artificial Intelligence in Medicine  
Discussion and conclusions: The paper discusses thoroughly the promising paths for future research in medical documents summarization.  ...  It mainly focuses on the issue of scaling to large collections of documents in various languages and from different media, on personalization issues, on portability to new sub-domains, and on the integration  ...  Spyropoulos and Dr. George Paliouras, for their helpful and constructive comments. Many thanks also to Ms. Eleni Kapelou and Ms. Irene Doura for checking the use of English.  ... 
doi:10.1016/j.artmed.2004.07.017 pmid:15811783 fatcat:n7u6ji5t2rgkvjktacjf4rdire
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