Concept/keyword extraction, and named entity recognition (ner). Natural - an awesome natural language processing toolkit for node. This ignores what's available on python, but was surprisingly useful for our purposes. Text statistics - useful Germany Phone Number List for getting data on sentence length, reading level, etc. Majestic - I started by exploring their api through a custom script, but they delivered the data Germany Phone Number List in one sip which was very nice. Thanks, dixon! Cheerio - an easy-to-use library for parsing dom elements using jquery-style markup. Ipinfo - not really a library, but a great api for getting server information.
The crawl process was very slow, mainly due to overflow limits from api providers and our proxy service. We would have created a cluster, but the expense limited us to hitting a few apis about once per second. Slowly we got a full crawl of the full 500,000 urls. Here are some notes on my experience with url crawling for data Germany Phone Number List collection: use apis whenever possible. Aylien was invaluable Germany Phone Number List for performing tasks where node libraries would be inconsistent. Find a good proxy service that will switch between consecutive calls. Create logic for websites and content types that may cause errors. Craigslist, pdf, and word documents caused issues when crawling. Check the collected data diligently, especially during the first few thousand
Results, to ensure that errors in mining do not create problems with the structure of the collected data. The results we reported our results from the Germany Phone Number List ranking predictions in a separate article, but I wanted to review some of the interesting insights in the data collected. Most competitive niches for this data, we reduced the dataset to include only top 20 rankings and also removed the top four percent of observations based on reference domains. The purpose of removing the Germany Phone Number List top four percent of referring domains was to prevent urls such as google, yelp, and other large websites from unduly influencing the averages. Since we were focusing on service industry results, we wanted to make sure that local business websites would likely be