Expert System, a company that started out by making language software for Microsofts spell check software in the late 1980s, is one of several vendors poking their fingers in the eye of Googles keyword search by applying semantic search technology to disambiguate search queries and web text in order to increase the precision and relevancy of results.
Keywords running out of productivity gas
Currently keyword search remains the most popular search technique for users on the public Web and corporate intranets. But many believe its time is up because consumers and business users no longer want to see 30,000 hits on a search and then wade through a list of loosely related keyword results to find relevant documents.
This where a new breed of so-called semantic technologies comes into the frame. Unlike ranking algorithms such as Googles PageRank for predicting relevancy, semantic search dips into the meaning in language to produce highly relevant search results.
For example, Expert System provides its own semantic search platform branded as Cogito (Latin for I think), and is provided as a fully-hosted service worldwide to offer businesses better search.
The Cogito semantic engine is designed around the principles of human comprehension to allow content to be understood in the way in which the author intended it to be. This is something that keyword search ignores. For example, a Google search for the word jaguar would pull up content around the animal and the car. Semantic search would look not only at the keyword but also other words around it like jungle or saloon to separate the two meanings.
Semantic search is just one of several search techniques that are being forwarded as better and more precise alternatives to keyword search. Others include heuristics and ontology, linguistics and text mining, and statistical. However, Expert System claims that these approaches fall short, addressing only the morphological and grammatical aspects of analysis.
What semantic search does is look at sentence logic (how words in a sentence relate to one another) and semantic analysis (understanding the context of keywords referred to as word sense disambiguation in semantic parlance). When a term is ambiguous, meaning it can have several meanings (for example, bark), it needs some kind of semantic analysis of the other words that wrap around it to give it its true meaning and context.
Other search engines often hit a brick wall when it comes to deep analysis. For example, when a heuristically-driven search engine sees two adjectives in a sentence it usually washes them out and scores the sentence as neutral because it has no understanding of where the two separate adjectives are pointing.
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