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Delete hyphens after reading pdf-files

Hi there,

I'm very new to RapidMiner. I'm reading german pdf-files and tokenizing them, which is working fine... However, the pdf-files contain hyphens that seperate a fair amount of words in to two parts, like the following example:

"die Bedeutung der finan-

ziellen Interessen der Union"

I'm trying to dehyphenate the broken text to:

"die Bedeutung der finanziellen Interessen der Union"

I'm using the replace tokens operator to joines the lines and remove the '-'. It works when I try it with examples within the operator, but when I play the process the words are all still broken and nothing seems to have been replaced. Maybe someone from the community can help? Thanks in advance! Here is my process:

<?xml version="1.0" encoding="UTF-8"?><process version="9.10.001">

<context>

<input/>

<output/>

<macros/>

</context>

<operator activated="true" class="process" compatibility="9.4.000" expanded="true" name="Process" origin="GENERATED_TUTORIAL">

<parameter key="logverbosity" value="init"/>

<parameter key="random_seed" value="2001"/>

<parameter key="send_mail" value="never"/>

<parameter key="notification_email" value=""/>

<parameter key="process_duration_for_mail" value="30"/>

<parameter key="encoding" value="SYSTEM"/>

<process expanded="true">

<operator activated="true" class="retrieve" compatibility="9.10.001" expanded="true" height="68" name="Retrieve BPW_Dictionary_zusammengefasst" width="90" x="179" y="187">

<parameter key="repository_entry" value="BPW_Dictionary_zusammengefasst"/>

</operator>

<operator activated="true" class="operator_toolbox:dictionary_sentiment_learner" compatibility="2.12.000" expanded="true" height="103" name="Dictionary-Based Sentiment (Documents)" width="90" x="380" y="187">

<parameter key="value_attribute" value="C"/>

<parameter key="key_attribute" value="A"/>

<parameter key="negation_attribute" value=""/>

<parameter key="negation_window_size" value="1"/>

<parameter key="negation_strength" value=""/>

<parameter key="use_symmetric_negation_window" value="false"/>

<parameter key="use_intensifier" value="false"/>

<parameter key="intensifier_word" value=""/>

<parameter key="intensifier_value" value=""/>

<parameter key="use_symmetric_intensifier_window" value="false"/>

</operator>

<operator activated="true" class="concurrency:loop_files" compatibility="9.10.001" expanded="true" height="82" name="Loop Files" width="90" x="179" y="34">

<parameter key="directory" value="D:/Masterarbeit/Daten_RapidMiner/Lageberichte_txt/2010"/>

<parameter key="filter_type" value="glob"/>

<parameter key="recursive" value="true"/>

<parameter key="enable_macros" value="false"/>

<parameter key="macro_for_file_name" value="file_name"/>

<parameter key="macro_for_file_type" value="file_type"/>

<parameter key="macro_for_folder_name" value="folder_name"/>

<parameter key="reuse_results" value="false"/>

<parameter key="enable_parallel_execution" value="true"/>

<process expanded="true">

<operator activated="true" class="text:read_document" compatibility="9.4.000" expanded="true" height="68" name="Read Document" width="90" x="45" y="34">

<parameter key="extract_text_only" value="true"/>

<parameter key="use_file_extension_as_type" value="true"/>

<parameter key="content_type" value="pdf"/>

<parameter key="encoding" value="SYSTEM"/>

</operator>

<operator activated="true" class="retrieve" compatibility="9.10.001" expanded="true" height="68" name="Retrieve Stopwords_zusammengefasst" width="90" x="715" y="187">

<parameter key="repository_entry" value="Stopwords_zusammengefasst"/>

</operator>

<operator activated="true" class="text:replace_tokens" compatibility="9.4.000" expanded="true" height="68" name="Replace Tokens" width="90" x="179" y="34">

<list key="replace_dictionary">

<parameter key="\n" value=" "/>

</list>

</operator>

<operator activated="true" class="text:replace_tokens" compatibility="9.4.000" expanded="true" height="68" name="Replace Tokens (2)" width="90" x="313" y="34">

<list key="replace_dictionary">

<parameter key="()" value="$1"/>

</list>

</operator>

<operator activated="true" class="text:tokenize" compatibility="9.4.000" expanded="true" height="68" name="Tokenize (2)" width="90" x="447" y="34">

<parameter key="mode" value="non letters"/>

<parameter key="characters" value=".:"/>

<parameter key="language" value="German"/>

<parameter key="max_token_length" value="3"/>

</operator>

<operator activated="true" class="text:filter_by_length" compatibility="9.4.000" expanded="true" height="68" name="Filter Tokens (by Length) (2)" width="90" x="581" y="34">

<parameter key="min_chars" value="3"/>

<parameter key="max_chars" value="999"/>

</operator>

<operator activated="true" class="text:transform_cases" compatibility="9.4.000" expanded="true" height="68" name="Transform Cases (2)" width="90" x="715" y="34">

<parameter key="transform_to" value="lower case"/>

</operator>

<operator activated="true" class="operator_toolbox:filter_tokens_using_exampleset" compatibility="2.12.000" expanded="true" height="82" name="Filter Tokens Using ExampleSet" width="90" x="916" y="34">

<parameter key="attribute" value="A"/>

<parameter key="case_sensitive" value="true"/>

<parameter key="invert_filter" value="false"/>

</operator>

<connect from_port="file object" to_op="Read Document" to_port="file"/>

<connect from_op="Read Document" from_port="output" to_op="Replace Tokens" to_port="document"/>

<connect from_op="Retrieve Stopwords_zusammengefasst" from_port="output" to_op="Filter Tokens Using ExampleSet" to_port="example set"/>

<connect from_op="Replace Tokens" from_port="document" to_op="Replace Tokens (2)" to_port="document"/>

<connect from_op="Replace Tokens (2)" from_port="document" to_op="Tokenize (2)" to_port="document"/>

<connect from_op="Tokenize (2)" from_port="document" to_op="Filter Tokens (by Length) (2)" to_port="document"/>

<connect from_op="Filter Tokens (by Length) (2)" from_port="document" to_op="Transform Cases (2)" to_port="document"/>

<connect from_op="Transform Cases (2)" from_port="document" to_op="Filter Tokens Using ExampleSet" to_port="document"/>

<connect from_op="Filter Tokens Using ExampleSet" from_port="document" to_port="output 1"/>

<portSpacing port="source_file object" spacing="0"/>

<portSpacing port="source_input 1" spacing="0"/>

<portSpacing port="source_input 2" spacing="0"/>

<portSpacing port="sink_output 1" spacing="0"/>

<portSpacing port="sink_output 2" spacing="0"/>

</process>

</operator>

<operator activated="true" class="operator_toolbox:apply_model_documents" compatibility="2.12.000" expanded="true" height="103" name="Apply Model (Documents)" width="90" x="581" y="34">

<list key="application_parameters"/>

</operator>

<connect from_port="input 1" to_op="Loop Files" to_port="input 1"/>

<connect from_op="Retrieve BPW_Dictionary_zusammengefasst" from_port="output" to_op="Dictionary-Based Sentiment (Documents)" to_port="exa"/>

<connect from_op="Dictionary-Based Sentiment (Documents)" from_port="mod" to_op="Apply Model (Documents)" to_port="mod"/>

<connect from_op="Loop Files" from_port="output 1" to_op="Apply Model (Documents)" to_port="doc"/>

<connect from_op="Apply Model (Documents)" from_port="exa" to_port="result 1"/>

<connect from_op="Apply Model (Documents)" from_port="doc" to_port="result 2"/>

<connect from_op="Apply Model (Documents)" from_port="mod" to_port="result 3"/>

<portSpacing port="source_input 1" spacing="0"/>

<portSpacing port="source_input 2" spacing="0"/>

<portSpacing port="sink_result 1" spacing="0"/>

<portSpacing port="sink_result 2" spacing="0"/>

<portSpacing port="sink_result 3" spacing="0"/>

<portSpacing port="sink_result 4" spacing="0"/>

<background height="232" location="//Samples/Tutorials/Basics/02/tutorial2" width="1502" x="26" y="47"/>

Find more posts tagged with

AI Studio

PDFs

Tokens

Replace

Text Mining + NLP

Sentiment Analysis

Accepted answers

Hi!

Try some combination of or \n\r instead of just \n.
\n is the "Unix line ending", just a newline character.
is Carriage Return + Newline, the Windows tradition.

It depends on your documents and how they are processed.

Regards,
Balázs

All comments

Hi,

I'd suggest a different regular expression in Replace Tokens (2).

Image: https://us.v-cdn.net/6030995/uploads/editor/p2/uneukkogk4at.png

RE: ([^ ])- +(\w)
Replacement: $1$2

This should be a bit more robust. It searches for a non-space before the hyphen, one or more spaces and then a word character.

However, the problem is that only the first match is replaced as you can see in the example.

So you might need to repeat the operator in a loop with "reuse results" checked.

Regards,
Balázs

Hi Balázs,

Thank you for helping me with this, the regular expression you recommended works great! The only problem I'm still fighting, is that it only works when I use the "Create Document" Operator, so I would manually have to transfer the text from the pdf file. When I try the "Read Document" Operator on the pdf or txt file, it seems as if the \n command doesn't work and the line breaks don't get deleted. Do you or anyone following this post know a workaround for this? Or is there a way to read the pdfs and automatically create a document in RapidMiner?

Thanks

Hi!

Try some combination of or \n\r instead of just \n.
\n is the "Unix line ending", just a newline character.
is Carriage Return + Newline, the Windows tradition.

It depends on your documents and how they are processed.

Regards,
Balázs

Hi Balázs,

Thanks for your help again! The expression r\n|\r|\n did the trick for me.

All the best

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