Natural Language Processing
For decades, one of the highest goals for computer scientists is the program that can process natural language. The trail to this Holy Grail, however, is littered with failed attempts, the most notable of which is Artificial Intelligence (AI).

With the advent of the Web, the bar has been raised considerably. Instead of trying to make sense of large databases of structured data, as AI researchers attempted, programmers now must find a way to make sense of massive databases of unstructured data on the Web.

Search Engine Application
Search engines are the highest profile examples of failure in writing programs that can make sense of Web text. For more than a decade, the best and the brightest minds in computer science have attempted to provide users with relevant search results for their queries. Most advances have nipped at the edges of the problem by enabling closer approximations of the meaning of users’ inputs, including Boolean search strings, exact phrase matches, and natural language search strings. In every case, they have enabled users to more accurately type what they want in the search field. But they have failed to appreciably improve the way their programs match search outputs to user’s meanings.

Recent advancements in XML metadata, such as Web ontologies, have attempted to add semantic structure to sites. In theory, the Web Ontology Language (OWL) and other advances of the Semantic Web allow browsers, search engines, or other agents to understand the meaning of Web content and give users desired outputs—executive summaries, abstracts, or whatever form of encapsulated meaning the user defines.

In practice, the Semantic Web is a long way from the Holy Grail. Because the onus is on individual sites to define their terms in ways that can be understood by browsers and other agents, adoption will be incomplete, and will suffer from a lack of consistent standards. Just as it took years for HTML, XML, and related technologies to become sufficiently robust to allow easy-to-use user interface designs, so it will take years for OWL and related technologies to become sufficiently robust to allow browsers to decode the meaning of Web content . And some doubt that it will ever reach the Holy Grail.

But there is a program—Syntactica—that can do today what OWL might only do after much rapid refinement and adoption. And unlike the Semantic Web, Syntactica requires no work by the webmasters of existing Web sites. It does all the work to gather the data, analyze it, and produce the output. It currently works on any document, but could be easily adapted to plug into Web browsers, word processing programs, or PDF readers.

Syntactica is not a program per se, but a Web Service that can be embedded in any number of applications to return relevant outputs given a wide variety of natural language inputs. In addition to plugging into Web browsers or search engines, it could plug into word processing programs to automatically provide abstracts, executive summaries, back-of-the book indexes, and writing or translation support.

It also could be plugged into tools used by editors and indexers of search sites to better track and evaluate content on the Web. It could also be used by corporate webmasters to give users more personalized information based on their stated desires. Indeed the range of applications that could take advantage of Syntactica Web Services is quite broad.

In fact all of the products presented on the Syntactica web site are relatively simple applications that take advantage of the Syntactica Web Services available at http://ws.syntactica.com/syntactica.asmx

Developers, please feel free to experiment with these services in your own non-commercial applications.  Syntactica Web Service calls are comprised of sending unstructured text files and receiving the processed results.

Have Fun!