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https://issues.apache.org/jira/browse/BEAM-1439?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15944466#comment-15944466
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Kenneth Knowles commented on BEAM-1439:
---------------------------------------

And also, please engage with the Beam community early - before applications are 
reviewed!

Here are some ideas for getting engaged:

# Work through Beam's "getting started" materials such as 
https://beam.apache.org/get-started/quickstart-java/
#* Especially get as familiar as you can with the runner that you are 
interested in
# Subscribe to d...@beam.apache.org and/or u...@beam.apache.org
# You are welcome to share your applications for early commentary on 
d...@beam.apache.org to get early feedback and mentorship (this is quite normal 
for GSoC+Apache; even if you don't get selected by GSoC you will learn and make 
new acquaintances)
# Pick up starter bugs to get familiar with the codebase beyond our getting 
started material

> Beam Example(s) exploring public document datasets
> --------------------------------------------------
>
>                 Key: BEAM-1439
>                 URL: https://issues.apache.org/jira/browse/BEAM-1439
>             Project: Beam
>          Issue Type: Wish
>          Components: examples-java
>            Reporter: Kenneth Knowles
>            Assignee: Kenneth Knowles
>            Priority: Minor
>              Labels: gsoc2017, java, mentor, python
>
> In Beam, we have examples illustrating counting the occurrences of words and 
> performing a basic TF-IDF analysis on the works of Shakespeare (or whatever 
> you point it at). It would be even cooler to do these analyses, and more, on 
> a much larger data set that is really the subject of current investigations.
> In chatting with professors at the University of Washington, I've learned 
> that scholars of many fields would really like to explore new and highly 
> customized ways of processing the growing body of publicly-available 
> scholarly documents, such as PubMed Central. Queries like "show me documents 
> where chemical compounds X and Y were both used in the 'method' section"
> So I propose a Google Summer of Code project wherein a student writes some 
> large-scale Beam pipelines to perform analyses such as term frequency, bigram 
> frequency, etc.
> Skills required:
>  - Java or Python
>  - (nice to have) Working through the Beam getting started materials



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