Content from the e-LICO group

Image Mining with RapidMiner (1)

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This is an image mining process using the image mining Web service provided by NHRF within e-Lico. It first uploads a set of images found in a directory, then preprocesses the images and visualizes the result. Furthermore, references to the uploaded images are stored in the local RapidMiner repository so they can later be used for further processing without uploading images a second time.

Created: 2010-04-28 | Last updated: 2012-01-16

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Core text mining workflows

Created: 2010-02-19 10:12:33 | Last updated: 2011-12-13 16:03:17

7 items in this pack

Comments: 0 | Viewed: 727 times | Downloaded: 136 times

Termine with c-value threshold (1)

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This workflow accepts a list of sentences from a single document and returns the terms found by the TerMine web service. It also allows you to set a threshold c-value score so that only terms with a user-controlled probability (of being a real term) are returned as an output.   To get sentences to supply to this workflow you can use the sentence splitting workflow.  The TerMine service (used in this workflow) only accepts text in ASCII encoding, so you should also use the Clean p...

Created: 2010-02-19 | Last updated: 2011-12-13

Credits: James Eales

PDF to plain text (1)

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This workflow will extract the plain text content of PDF files supplied to the input port.  You can connect the Load PDF from directory workflow to this workflows input. We recommend you send the output from this workflow to the Clean plain text workflow, because the PDF to text process can add characters into the text that are XML-invalid and therefore can not be sent to most services as plain text.  Another way round this problem is to encode the text as Base64 using the handy loc...

Created: 2010-02-19 | Last updated: 2011-12-13

Credits: James Eales

Sentence splitting (1)

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This workflow will attempt to split up text into sentences, returning a list of sentences to the output port.  The sentence splitting service makes use of the OpenNLP sentence detector and has been trained to work on english text. This workflow can be used to provide input to the Termine with c-value threshold workflow. This is a workflow component, designed to be used as a nested workflow inside a larger text mining or text processing workflow.

Created: 2010-02-19 | Last updated: 2011-12-13

Credits: James Eales

Terms from collection of PDF files (2)

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This workflow will give you a set of candidate terms for each PDF document in a user-specified directory. You can also specify a c-value threshold that will restrict the terms to those with higher scores. This workflow was created using only nested workflows.  These workflow components work on their own and can be linked together to form more complex workflows such as this. You can view the text mining workflow components in this pack. If you receive errors when running this workflow t...

Created: 2010-02-19 | Last updated: 2011-12-13

Credits: James Eales

Terms from collection of text files (1)

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This workflow will give you a set of candidate terms for each text file in a user-specified directory. You can also specify a c-value threshold that will restrict the terms to those with higher scores. This workflow was created using only nested workflows.  These workflow components work on their own and can be linked together to form more complex workflows such as this. You can view the text mining workflow components in this pack. If you receive errors when running this workflow then...

Created: 2010-02-22 | Last updated: 2011-12-13

Credits: James Eales

Load PDF from directory (1)

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This workflow will automate the reading of a set of PDF files stored in a single directory (the path to which should be supplied as a single input value). This is a workflow component, designed to be used as a nested workflow inside a larger text mining or text processing workflow.  

Created: 2010-02-19 | Last updated: 2011-12-13

Credits: James Eales

Load plain text from directory (1)

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This workflow will automate the reading of a set of text files stored in a single directory (the path to which should be supplied as a single input value).  It will assume that the text files are saved using the default character encoding for the system that Taverna is running on.  This is a workflow component, designed to be used as a nested workflow inside a larger text mining or text processing workflow.  

Created: 2010-02-18 | Last updated: 2011-12-13

Credits: James Eales

Clean plain text (ASCII) (1)

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This workflow will remove any XML-invalid and non-ASCII characters (e.g. for sending to the ASCII-only Termine service) from any text supplied to the input port. This is a workflow component, designed to be used as a nested workflow inside a larger text mining or text processing workflow.

Created: 2010-02-18 | Last updated: 2011-12-13

Credits: James Eales

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e-LICO recommender workflows

Created: 2011-03-15 15:33:48 | Last updated: 2012-01-28 19:39:06

6 items in this pack

Comments: 0 | Viewed: 305 times | Downloaded: 162 times

Clean plain text (1)

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This workflow will remove any XML-invalid characters (these characters often appear in the output of PDF to text software) from any text supplied to the input port. This is a workflow component, designed to be used as a nested workflow inside a larger text mining or text processing workflow.  

Created: 2010-02-18 | Last updated: 2011-12-13

Credits: James Eales

miRNA GFF to entrez gene (1)

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This workflow reads a GFF file of miRNA cooridinates and uses BioMart to search human ensemble genes for the gene that codes for the miRNA. The workflow returns a list of miRNAid, chromosome, start, stop, strand, entrez gene id, gene name, gene strand. Example input file here: ftp://mirbase.org/pub/mirbase/CURRENT/genomes/hsa.gff

Created: 2011-01-26 | Last updated: 2012-01-11

Using Remember / Recall for "tunneling" re... (1)

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This process shows how Remeber and Recall operators can be used for passing results from one position to another position in the process, when it's impossible to make a direct connection. This process introduces another advanced RapidMiner technique: The macro handling. We have used the predefined macro a, accessed by %{a}, that gives the apply count of the operator. So we are remembering each application of the models that are generated in the learning subprocess of the Split validation. Af...

Created: 2010-04-29 | Last updated: 2012-01-16