Our first step is to create a Web search engine that goes beyond just keyword searching, enabling our users to dig deeper, locate faster and retrieve results that are more relevant.

Infocious achieves this through performing our proprietary and fully automated linguistic analysis algorithms on web pages downloaded by our advanced crawler. The latent information recovered from this analysis, mainly through resolving ambiguities in natural languages, is used throughout Infocious to improve search quality, simplify information gathering, and reduce information overload.

Presently, keyword-based search engines return query results in one single unorganized list. For example, a search for Jaguar will return results that may be about Jaguar cars, Jaguar the animal, or, Jaguar the football team, all in one non-categorized list. A user interested in only one of the above topics may have to read through pages of search results and manually sort out irrelevant entries. This task takes time and can frustrate the user due to the immense amount of information that he/she would have to wade through. The problem is only getting worse as the amount of information on the Web grows rapidly over time.

Infocious tackles this difficulty by first automatically recognizing whether a user's query, such as Jaguar, may fall into multiple categories. If so, Infocious provides our users the option to narrow their search to one of the categories with a single mouse click. For example, the "Computers" categories will show only pages about the Macintosh operating system, whereas "Autos" would be about Jaguar cars.

Infocious takes this categorization idea a step further to offer our "topic specific search" capability, or some might call it vertical market searches. A topic is a collection of categories that our users might be interested in, such as travel or health. By pre-organizing the Web into more manageable domains, Infocious helps our users stay focused on the topic of interest and not be frustrated by off-topic noise. An example of this is searching for "drivers" in the context of travel (bus or taxi drivers) versus the Web, where the computer software usage dominates.

In addition to categorization, our underlying technology enables additional tools users can utilize to find relevant results quickly. These tools include automated identification of the most important phrases within the results (called Key Phrases), suggestions for concepts related to the current search (called Related Topics), as well as personalization capabilities. Broadly speaking, while Key Phrases further enables users to pinpoint their searches, Relevant Concepts enables them, if they would like to, to expand their searches into contextually related topics.

Other highlights of our technology includes our advanced web crawler that allows users to not only search the surface web (i.e., the pages that are accessible simply by following links), but content retrieved via HTML forms (a.k.a., the "hidden" web) and thus are not accessible via traditional web crawlers. If you are interested in finding more about our technology, please see our technology section.