server responds to requests. See Figure 7-22 as an example of a Content  Classification Quick Start Tool interface for defining classification behavior. See Chapter 9, “Content analysis with IBM Content Classification and document  clustering” on page 305 for additional details about using Document clustering  and classification techniques with Content Analytics. Text mining and gaining insight into your content is an iterative process. The  following best-practice approach is based on years of field experiences: 7.4 Preferred practices Figure 7-22 Content Classification Quick Start Tool user interface GLYPH<SM590000> Assess your content and goals to determine which out-of-box analytics  (Named Entity Recognition, Sentiment, Terms of Interest, and so on) will be  valuable to configure. GLYPH<SM590000> Start your analysis with a small collection. This makes it quicker to index the  collection and allows more iterations of changes and tests. Gradually increase  collection size as you get closer to a configuration that meets your goals. GLYPH<SM590000> Follow the normal procedure several times:  – Crawl, parse, index, and inspect the content by using the content analytics  miner. 262  IBM Watson Content Analytics: Discovering Actionable Insight from Your Content