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You're reading from  Java for Data Science

Product typeBook
Published inJan 2017
Reading LevelIntermediate
PublisherPackt
ISBN-139781785280115
Edition1st Edition
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Authors (2):
Richard M. Reese
Richard M. Reese
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Richard M. Reese

Richard Reese has worked in the industry and academics for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville Texas. Richard is the author of various books and video courses some of which are as follows: Natural Language Processing with Java. Java for Data Science Getting Started with Natural Language Processing in Java
Read more about Richard M. Reese

Jennifer L. Reese
Jennifer L. Reese
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Jennifer L. Reese

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to high-school students. Her interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education. She has co-authored two books: Java for Data Science and Java 7 New Features Cookbook. She previously worked as a software engineer. In her free time she enjoys reading, cooking, and traveling—especially to any destination with a beach. She is a musician and appreciates a variety of musical genres.
Read more about Jennifer L. Reese

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Other optional enhancements


There are numerous improvements that can be made to the application. Many of these are user preferences and others relate to improving the results of the application. A GUI interface would be useful in many situations. Among the user options, we may want add support for:

  • Displaying individual tweets

  • Allowing null sub-topics

  • Processing other tweet fields

  • Providing list of topics or sub-topics the user can choose from

  • Generating additional statistics and supporting charts

With regard to process result improvements, the following should be considered:

  • Correct user entries for misspelling

  • Remove spacing around punctuation

  • Use alternate stop word removal techniques

  • Use alternate sentiment analysis techniques

The details of many of these enhancements are dependent on the GUI interface used and the purpose and scope of the application.

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Java for Data Science
Published in: Jan 2017Publisher: PacktISBN-13: 9781785280115

Authors (2)

author image
Richard M. Reese

Richard Reese has worked in the industry and academics for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville Texas. Richard is the author of various books and video courses some of which are as follows: Natural Language Processing with Java. Java for Data Science Getting Started with Natural Language Processing in Java
Read more about Richard M. Reese

author image
Jennifer L. Reese

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to high-school students. Her interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education. She has co-authored two books: Java for Data Science and Java 7 New Features Cookbook. She previously worked as a software engineer. In her free time she enjoys reading, cooking, and traveling—especially to any destination with a beach. She is a musician and appreciates a variety of musical genres.
Read more about Jennifer L. Reese