text mining research papers


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Text mining: The state of the art and the challenges
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Proceedings of the PAKDD 1999 Workshop on , 1999 ,ntu.edu.sg
Abstract Text mining, also known as text data mining or knowledge discovery from textual
databases, refers to the process of extracting interesting and non-trivial patterns or
knowledge from text documents. Regarded by many as the next wave of knowledge 

an Internet text-mining tool for biomedical information, with application to gene expression profiling
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L Tanabe, U Scherf, LH Smith, JK Lee ,, 1999 ,137.187.213.210
ABSTRACT The trend toward high-throughput techniques in molecular biology and the
explosion of online scientific data threaten to overwhelm the ability of researchers to take full
advantage of available information. This problem is particularly severe in the rapidly 

Text mining at the term level
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  of Data Mining and , 1998 ,Springer
Knowledge Discovery in Databases (KDD) focuses on the computerized exploration of large
amounts of data and on the discovery of interesting patterns within them. While most work on
KDD has been concerned with structured databases, there has been little work on 

What is text mining
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Text Mining is the discovery by computer of new, previously unknown information, by
automatically extracting information from different written resources. A key element is the
linking together of the extracted information together to form new facts or new hypotheses 

A brief survey of text mining
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Abstract The enormous amount of information stored in unstructured texts cannot simply be
used for further processing by computers, which typically handle text as simple sequences of
character strings. Therefore, specific (pre-) processing methods and algorithms are 

Hybrid text mining for finding abbreviations and their definitions
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Y Park ,Proceedings of the 2001 , 2001
Abstract We present a hybrid text mining method for finding abbreviations and their
definitions in free format texts. To deal with the problem, this method employs pattern-based
abbreviation rules in addition to text markers and cue words. The pattern-based rules 

GTP (General Text Parser) software for text mining
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JT Giles, L Wo , data mining and knowledge discovery, 2003 ,eecs.utk.edu
Because of the seemingly transparent nature of search engine design and use, there is a
tendency to forget the decisions and tradeoffs constantly made throughout the design
process, which ultimately affect the performance of any information retrieval (IR) system. 

Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge
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 biomedcentral.com
Abstract Background: Genome sciences have experienced an increasing demand for
efficient text-processing tools that can extract biologically relevant information from the
growing amount of published literature. In response, a range of text-mining and 

Linking genes to literature: text mining, information extraction, and retrieval applications for biology
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 biomedcentral.com
Abstract Efficient access to information contained in online scientific literature collections is
essential for life science research, playing a crucial role from the initial stage of experiment
planning to the final interpretation and communication of the results. The biological 

Text mining infrastructure in R
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I Feinerer, K Hornik, D Meyer ,Journal of , 2008  text-analysis.googlecode.com
Abstract During the last decade text mining has become a widely used discipline utilizing
statistical and machine learning methods. We present the tm package which provides a
framework for text mining applications within R. We give a survey on text mining facilities 

Text mining for causal relations
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R Girju ,Proceedings of the FLAIRS Conference, 2002 ,aaai.org
Abstract Given a semantic relation, the automatic extraction of linguistic patterns that express
that relation is a rather difficult problem. This paper presents a semi-automatic method of
discovering generally applicable lexico-syntactic patterns that refer to the causal relation. 

Knowledge management: A text mining approach
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 abhatoo.net.ma
Abstract Knowledge Discovery in Databases (KDD), also known as data mining, focuses on
the computerized exploration of large amounts of data and on the discovery of interesting
patterns within them. While most work on KDD has been concerned with structured 

Lexical, terminological and ontological resources for biological text mining
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O Bodenreider  Text mining for biology and biomedicine, 2006 ,130.14.53.23
Biomedical terminologies and ontologies are frequently described as enabling resources in
text mining systems [eg, 1, 2, 3]. These resources are used to supports tasks such as entity
recognition (ie, the identification of biomedical entities in text) and relation extraction (ie, 

Structured digital abstract makes text mining easy
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SIR—Your Editorial “The database revolution”(Nature 445, 229–230; 2007) highlighted the
difficulty in maintaining a stable information architecture for biology—in terms of both funding
it consistently and evolving a common format. In addition to the suggestions you made, we 

Text mining for biology-the way forward: opinions from leading scientists
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 biomedcentral.com
Abstract This article collects opinions from leading scientists about how text mining can
provide better access to the biological literature, how the scientific community can help with
this process, what the next steps are, and what role future BioCreative evaluations can 

Text mining in a digital library
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 2004 ,Springer
Digital librarians strive to add value to the collections they create and maintain. One way is
through selectivity: a carefully chosen set of authoritative documents in a particular topic
area is far more useful to those working in the area than a huge, unfocused collection (like 

Thesaurus or logical ontology, which one do we need for text mining?
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J Tsujii ,Language resources and evaluation, 2005 ,Springer
Abstract Ontologies are recognised as important tools, not only for effective and efficient
information sharing, but also for information extraction and text mining. In the biomedical
domain, the need for a common ontology for information sharing has long been 

An ontology-based framework for text mining
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 kde.cs.uni-kassel.de
Abstract Structuring of text document knowledge frequently appears either by ontologies and
metadata or by automatic (un-) unsupervised text categorization. This paper describes our
integrated framework OTTO (OnTology-based Text mining framewOrk). OTTO uses text 

A text mining approach for definition question answering
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 2006 ,Springer
This paper describes a method for definition question answering based on the use of
surface text patterns. The method is specially suited to answer questions about person’s
positions and acronym’s descriptions. It considers two main steps. First, it applies a 


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