| By Sydney Fairman |
Gale is excited to announce several enhancements to theDigital Scholar Lab. We have made notable improvements to the overall workflow, text cleaning capabilities, and topic modeling tool. For instance, the topic modeling tool offers a new topic overview and “topic proportion by document” results.
Along with tabular data, these enhancements better align with what users expect from the Machine Learning for Language Toolkit (MALLET). Typically,MALLETrequires an advanced understanding of programming. This can be difficult to interpret and assign meaning to the results if you’re a Digital Humanities scholar that lacks a background in computer science and statistics. The topic modeling tool improvements allow users to form clear connections between MALLET data and their content set.
Read below to see whatAmerican Reference Books Annual (ARBA)has to say about the overall value ofDigital Scholar Lab:
“毕业学生和学者的吸引力是显而易见的，但数字学者实验室还必须作出深入的研究访问，以本科生的潜力。强烈推荐给学术图书馆“。金宝搏彩票
-ARBA人员审阅
Explore the possibilities and request a free trial of Digital Scholar Lab today >>