text mining research papers-3
Text mining: getting more value from literature resources
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R Hale ,Drug Discovery Today, 2005 ,journals2005.pasteur.ac.ir
1. Text mining: getting more value from literature resources Pages 377-379 Roger Hale 2. Predicting
ovarian tumor response Pages 380-381 Vida Foubister 3. Gefitinib does not increase survival
in lung cancer patients Page 381 Roy M. Golsteyn 4. Hematopoiesis: cMyb enters centre
Text-mining based journal splitting
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X Lin ,studies, 2003 ,cse.salford.ac.uk
Abstract This paper introduces a novel journal splitting algorithm. It takes full advantage of
various kinds of information such as text match, layout and page numbers. The core
procedure is a highly efficient text-mining algorithm, which detects the matched phrases
Text mining in the SOMLib digital library system: The representation of topics and genres
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A Rauber ,Applied Intelligence, 2003 ,Springer
With the increasing amount of textual information available in electronic form, more powerful
methods for exploring, searching, and organizing the available mass of information are
needed to cope with this situation. This paper presents the SOMLIb digital library system,
A suite of tools for marking up textual data for temporal text mining scenarios
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A Vasilakopoulos, M Bersani ,Proceedings of the 4th , 2004 ,sibilo.co.uk
Abstract Text Mining is a relatively new area of research, very interesting for both
computational linguists and data miners. It involves collecting and analyzing quantities of
textual data by domain experts, whose main task is the manual revision of markup. We
Improving knowledge discovery by combining text-mining and link analysis techniques
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M Ben-Dov, W Wu, on Data Mining, 2004 ,www-users.cs.york.ac.uk
11.. Abstract The availability of online text documents exposes the readers to a vast amount
of potentially valuable information buried in those texts. The huge number of documents
created the pressing need for automated methods of discovering relevant information
Enhanced semantic access to the protein engineering literature using ontologies populated by text mining
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T Kappler ,International Journal of Bioinformatics , 2007 ,Inderscience
The biomedical literature is growing at an ever-increasing rate, which pronounces the need
to support scientists with advanced, automated means of accessing knowledge. We
investigate a novel approach employing description logics (DL)-based queries made to
Practical text mining
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PKDD-98, p487, 1998 ,ns.isoc.org.il
Visit the Chicago Tribune on the Internet at http://www chicago tribune com/ The Finsbury
Park Mosque is the center of radical Muslim activism in England. Through <OFFLEN
OFFSET=”3576″ LENGTH=“33″ /> <Person>Abu Hamza al-Masri</Person>
A novel web text mining method using the discrete cosine transform
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L Park, M Palaniswami ,Principles of Data Mining , 2002 ,Springer
Fourier Domain Scoring (FDS) has been shown to give a 60% improvement in precision
over the existing vector space methods, but its index requires a large storage space. We
propose a new Web text mining method using the discrete cosine transform (DCT) to
Knowledge management, data mining, and text mining in medical informatics
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H Chen, SS Fuller, C Friedman ,Medical Informatics, 2005 ,Springer
In this chapter we provide a broad overview of selected knowledge management, data
mining, and text mining techniques and their use in various emerging biomedical
applications. It aims to set the context for subsequent chapters. We first introduce five
A framework for text mining services
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C Grover, H Halpin, Proceedings of the UK , 2004 ,ltg.ed.ac.uk
Abstract The growth of online scientific literature, coupled with the growing maturity of text
processing technology, has boosted the importance of text mining as a potentially crucial
tool. However, there are several challenges to be addressed before sophisticated text
Technology of text mining
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A Visa , Learning and Data Mining in Pattern Recognition, 2001 ,Springer
A large amount of information is stored in databases, in intranets or in Internet. This
information is organised in documents or in text documents. The difference depends on the
fact if pictures, tables, figures, and formulas are included or not. The common problem is to
Text mining
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Practical handbook of Internet computing. CRC Press, , 2004 ,cos.ufrj.br
“Bag of words” model, acronym extraction, authorship ascription, coordinate matching, data
mining, document clustering, document frequency, document retrieval, document similarity
metrics, entity extraction, hidden Markov models, hubs and authorities, information
Data mining and text mining for sciencetechnology research
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E Leopold, M May ,Handbook of quantitative science and , 2005 ,Springer
The goal of the paper is to give an overview on the state of the art of data mining and text
mining approaches which are useful for bibliometrics and patent databases. The paper
explains the basics of data mining in a non-technical manner. Basic approaches from
Text Mining applied to multilingual corpora
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F Neri ,Knowledge Mining, 2005 ,Springer
Up to 80% of electronic data is textual and most valuable information is often encoded in
pages which are neither structured, nor classified. Documents are—and will be—written in
various native languages, but these documents are relevant even to non-native speakers.
Knowledge-based selection of association rules for text mining
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D Janetzko, H Cherfi, R Kennke, A Napoli ,ECAI, 2004 ,frontiersinai.com
Abstract. A reoccuring problem in mining association rules is the selection of interesting
association rules within the overall, and possibly huge set of extracted rules. The majority of
previous work in this area relies on statistical methods for quality estimation and selection
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