text mining research paper 2013
RESEARCH PAPERS

text mining research paper 2013




EventCube: Multi-Dimensional Search and Mining of Structured and Text Data
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ABSTRACT A large portion of real world data is either text or structured (eg, relational) data. Moreover, such data objects are often linked together (eg, structured specification of products linking with the corresponding product descriptions and customer comments). 

Introduction to the tm Package Text Mining in R
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This vignette gives a short introduction to text mining in R utilizing the text mining framework provided by the tm package. We present methods for data import, corpus handling, preprocessing, meta data management, and creation of term-document matrices. Our 

A Decoupled Architecture for Scalability in Text Mining Applications.
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ABSTRACT Sophisticated Text Mining features such as visualization, summarization, and clustering are becoming increasingly common in software applications. In Text Mining, documents are processed using techniques from different areas which can be very 

Survey of Text Mining
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Recently text mining has become an important research area. Text can be placed in newspaper articles, SMS, mails, on-line chats, journals, product reviews, and organization files. Text mining also known as text data mining, intelligent text analysis or knowledge 

CLUO: Web-Scale Text Mining System for Open Source Intelligence Purposes
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ABSTRACT The amount of textual information published on the Internet is considered to be in billions of web pages, blog posts, comments, social media updates and others. Analyzing such quantities of data requires high level of distribution–both data and computing. This is 

D-VITA: A Visual Interactive Text Analysis System Using Dynamic Topic Mining.
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ABSTRACT Recent developments in web technologies like Web 2.0 have led to the generation of massive amounts of data. The rapid growth of data makes knowledge extraction and trend prediction a challenging task. A recent approach for the unsupervised analysis of text 

Integrating content analysis and text mining in studying psychology of religion
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Purpose? Another sample is needed in order to further examine Bering's notion. In contrast to the US, in the United Kingdom churchgoers are 10% of the entire population, and a survey indicates that only 44% of UK citizens believe in God.

Practice of Instant Text-mining in English Courses
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This paper describes our attempts to construct Instant Text-mining (ITS) incorporated into Moodle and illustrates our practice in English presentation course. The importance of receiving real-time feedback from the audience is often stated in relation to the discussion 

A Tool for Text Mining in Molecular Biology Domains
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ABSTRACT Researchers need to be constantly aware of the work that has been done in their research area. Nowadays, most of the publications are available on the Internet. However there is, usually, an overwhelming amount of information making it impossible for a 

and Classification Aug Clustering and Classification Augmented with Semantic mented with Semantic Similarity for Text Mining Similarity for Text Mining
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ABSTRACT Semantic similarity is a way of analyzing the perfect synonym that exists between word-pairs. This measure is necessary to detect the degree of relationship that persists within word-pairs. To compute the semantic similarity that lies between a word-pair, 

TEXT MINING FOR PATTERN IDENTIFICATION
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ABSTRACT The searching process in web or application software was performed by comparing the search content with the text. The search complexity varies as the most of the words can be represented by their approximate meaningful content. This proposed 

APPLICATIONS OF GRAPH THEORY IN TEXT MINING
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A Sharma , JOURNAL OF TECHNICAL AND NON-TECHNICAL ,vsrdjournals.com ABSTRACT That is an era of technology and their applications, behind this advanced technology a domain of conventional computing domain always works and provides supports to make changes and improvement over the existing domain. In The same way 

Morphological Text Mining Implementation
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M Markandeyulu, B Nagarjuna, T VijayKumar ,irj.iars.info ABSTRACT Text mining is extracting useful or relevant information from a Textual file. The extraction of information works on search engine or through a tool. Text mining is used for text retrievalextraction and also categorization. We have developed a tool which will 

Social Media Text Mining and Network Analysis for Decision Support in Natural Crisis Management
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ABSTRACT A core issue in crisis management is to extract from the mass of incoming information what is important for situational awareness during mass emergencies. Based on a case study we develop a prototypical application, TweetComp1, which is integrated into 

Content Extraction with text mining using natural language processing for anatomy based topic summarization
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ABSTRACT Inorder to get exact content for the web browsers when searching for some information we have combined two methods together. The first method is text mining using natural language processing and parse tree query language, the second method is 

Basic Techniques in Text Mining using Open-source Tools
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J Iio ,opensym.org ABSTRACT There are many text mining tools provided commercially and non-commercially. However, the elementary text-based analysis can be done with basic Unix commands, shell- scripts, and small program of scripting languages, instead of using such extensive 

Graphical Interface that Supports Users' Trial-and-Error Process of Text Mining
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N Otsuka, M Matsushita Large amounts of text data can be found via the World Wide Web and stored on computers. Such a text is used for browsing and as information resources for finding useful knowledge based on its analysis. Text mining is a technique for finding useful knowledge from 

TEXT CLUSTERING IN CONCEPT BASED MINING
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PS RANDIVE, NN PISE ABSTRACT In text mining most techniques depends on statistical analysis of terms. Statistical analysis trances important terms within document only. However this concept based mining model analyses terms in sentence, document and corpus level. This mining model consist 

Text Mining Interpreting Knowledge Discovery from Biomed Articles
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K Prabavathy, P Sumathi ,thesij.com ABSTRACT The biggest challenge for text and data mining in biomedical informatics is to impact the discovery process, enabling scientists to generate novel hypothesis to address the most crucial questions for understanding the knowledge basis from biomed articles or 

A Detailed Study on Text Mining Techniques
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R Agrawal, M Batra ,International Journal of Soft Computing ABSTRACT Text Mining is an important step of Knowledge Discovery process. It is used to extract hidden information from not-structured or semi-structured data. This aspect is fundamental because most of the Web information is semistructured due to the nested 

An Efficient Concept-Based Mining Model for Enhancing Text Clustering
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N Menaga, B Hemapriya ,International Journal ABSTRACT The common techniques in text mining are based on the statistical analysis of a term, either word or phrase. Text is represented by the words it mentions, and thematic similarity is based on the proportion of words that texts have in common. The complex is 

Text Mining and Its Applications
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ABSTRACT As computer networks become the backbones of science and economy, enormous quantities of machine readable documents become available. Computerization and automated data gathering has resulted in extremely large data repositories eg Walmart: 

Effective Concept-Based Mining Model For Text Clustering
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A Nirmala, KA Vanitha ABSTRACT The common techniques in text mining are based on the statistical analysis of a term, either word or phrase. Statistical analysis of a term frequency captures the importance of the term within a document only. Two terms can have the same frequency in their 

Review of Text Mining Method: Investigation and Analysis
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MDS Charjan ABSTRACT Basically we can define the process of text mining is nothing but the extraction of non trivial and interesting data from the unstructured text. As per our study, text mining is consisting of many computer science oriented rules majorly intended towards the artificial 

Stability of Text Mining Techniques for Identifying Cancer Staging
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ABSTRACT We address the task of extracting information from free-text histopathology reports: such information includes cancer staging and tumour characteristics. In particular, we investigate the stability of a text mining model constructed from records from one health 

Improving Laboratories Efficiency through Website Using Text Mining
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A Tariq ABSTRACT Text mining is an emerging technology that can be used to augment existing data in corporate databases by making unstructured text data available for analysis. This research aim to present a proposed text mining system customized to improve 

General introduction Text mining in MedlineAbstracts versus in full-text articles
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R Frijters, J van Dieten, W Fleuren, J de Vlieg ,PDF hosted at the ,repository.ubn.ru.nl ABSTRACT MedlineAbstracts represent a rich source for extracting information on biomedical concepts (eg genes, pathways, diseases, drugs) and their relationships. In recent years the number of full articles that become publicly available has grown 

Concept Based Mining in Text Clustering
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P Randive, N Pise ,irdindia.in ABSTRACT In text mining most techniques depends on statistical analysis of terms. Statistical analysis trances important terms within document only. However this concept based mining model analyses terms in sentence, document and corpus level. This mining model consist 

On the Comparison of Semi-Supervised Hierarchical Clustering Algorithms in Text MiningTasks
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ABSTRACT Semi-supervised clustering approaches have emerged as an option for enhancing clustering results. These algorithms use external information to guide the clustering process. In particular, semi-supervised hierarchical clustering approaches have been explored in 

Text mining approach for WSI in QA systems through relation construction
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ABSTRACT The paper attempts to identify the exact sense of the word through a process of establishing relations between similar words in the sample ontology. The philosophy relates to analysing the variance in sense among similar words with the help of a data mining tool 

Parallel Text Mining for Large Text Processing
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ABSTRACT There is an urgent need to develop new text mining solutions using High Performance Computing (HPC) and grid environments to tackle the exponential growth in textual data. Problem sizes are increasing by the day by addition of new text documents. 

Predicting Citation Counts Using Text and Graph Mining
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ABSTRACT As the volume of scientific literature grows faster it becomes more difficult for researchers to identify promising papers that are likely to become influential in their field. We study the problem of predicting future citation counts of papers given information available 

Text Mining Detection in Effective Model
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D Sailaja, KJ Paul ,ietrj.com ABSTRACT Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text 

Large-Scale Text Mining of Biomedical Literature
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Natural Language Processing in the Biomedical Domain (BioNLP) deals with text mining of scientific biomedical literature, most typically represented by the PubMed1Abstracts, and less frequently also the Open Access subset of PubMed Central2 full article texts. The 

Discovering Patterns to Produce Effective Output through Text Mining Using Naïve Bayesian Algorithm
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ABSTRACT Text mining has been an unavoidable data mining technique. There are different methods for text mining, One of the most successful will be mining using the effective patterns. Here a Naïve Bayesian algorithm is being used for discovering of patterns, since 


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