Use Cases for Taming Text, 2nd ed. by Grant Ingersoll.
From the post:
Drew Farris, Tom Morton and I are currently working on the 2nd Edition of Taming Text (http://www.manning.com/ingersoll for first ed.) and are soliciting interested parties who would be willing to contribute to a chapter on practical use cases (i.e. you have something in production and are willing to write about it) for search with Solr, NLP using OpenNLP or Stanford NLP and machine learning using Mahout, OpenNLP or MALLET — ideally you are using combinations of 2 or more of these to solve your problems. We are especially interested in large scale use cases in eCommerce, Advertising, social media analytics, fraud, etc.
The writing process is fairly straightforward. A section roughly equates to somewhere between 3 – 10 pages, including diagrams/pictures. After writing, there will be some feedback from editors and us, but otherwise the process is fairly simple.
In order to participate, you must have permission from your company to write on the topic. You would not need to divulge any proprietary information, but we would want enough information for our readers to gain a high-level understanding of your use case. In exchange for your participation, you will have your name and company published on that section of the book as well as in the acknowledgments section. If you have a copy of Lucene in Action or Mahout In Action, it would be similar to the use case sections in those books.
I am guessing the second edition isn’t going to take as long as the first. 😉
Couldn’t be in better company as far as co-authors.
See the post for the contact details.