Semantic Search, Navigation and Optimization Solutions

Digger Tags™: Semantic Content Tagger

Tags enable users to engage with a web site in ways that were not previously possible and are becoming commonplace. However, creating and maintaining tags is most often done manually, a process that is time-consuming and prone to inconsistencies. TextDigger's automatic tagging system enables highly-scalable, consistent content tagging to improve search engine optimization (SEO), site stickiness and ad targeting opportunities. Read more about Digger Tags

Digger Topics™: Semantic Topic Creator

Digger Topics is the cost-effective way to create thousands of new, engaging Web pages that leverage your editorial investment. Not only do readers benefit from topically organized content, you and your advertisers do as well. Since each topic is a high-quality landing page, it is prime real estate for search engine marketing (SEM) and highly targeted, relevant online advertising. Read more about Digger Topics

Digger Keywords™: Semantic SEO Tool

Effective use of keywords is one of the most important ways to rank well on search engines. TextDigger's keyword generation system analyzes the content of your page relative to the myriad pages on the web to recommend valuable, relevant keywords and phrases that will make a dramatic improvement to search engine ranking. Even pages that have already been manually optimized benefit from the depth and breadth of coverage of TextDigger's keyword generation solution. Read more about Digger Keywords

Digger.com is a different kind of web search tool. Rather than having to carefully craft the words used to search for content on the Web, Digger.com intelligently and automatically presents you with reasonable variations of your query. By analyzing the context and relationships of the words in your search query and content on the Web, Digger.com is able to present relevant sites that might otherwise be buried by other search engines. Sign up for a free beta account.

TextDigger's related search system suggests alternative, related or equivalent words and phrases for a site visitor's search query to improve the search experience, use of site search and monetization of search visits. Instead of being limited to hit-or-miss searching, search suggestions enable your visitors to find what they seek more quickly as well as discover related information. TextDigger's related search technology goes beyond purely statistical methods such as collaborative filtering in order to overcome cold start issues even in environments with sparse query data, where there is a large volume of search queries but few similarities among them. Read more about Digger Related Search

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