Introduction to ANTOM v4.0

ANTOM is the name for Automated Ontology Manager. It functions as a fully automated search and categorization engine for all kinds of text documents. It uses the Semantic Web technology to power the inside logic of the system. One of the contributions of this system is it supports semantic search. Semantic search is probably a new name for most ordinary searchers who use generic search tools to look for things they are interested, either from their computers or the Web. Before we begin to explain how to use ANTOM to support your daily work, let us explore the meaning of semantic search.

[Quote from Wikipedia]
Semantic search is a process used to improve online searching by using data from semantic networks to disambiguate queries and web text in order to generate more relevant results. Hildebrand et al. provide an overview that lists semantic search systems and identifies other uses of semantics in the search process.
Guha et al. distinguish two major forms of search: Navigational and Research. In navigational search, the user is using the search engine as a navigation tool to navigate to a particular intended document. Semantic Search is not applicable to navigational searches. In Research Search, the user provides the search engine with a phrase which is intended to denote an object about which the user is trying to gather/research information. There is no particular document which the user knows about that s/he is trying to get to. Rather, the user is trying to locate a number of documents which together will give him/her the information s/he is trying to find. Semantic Search lends itself well here.
Rather than using ranking algorithms such as Google's PageRank to predict relevancy, Semantic Search uses semantics, or the science of meaning in language, to produce highly relevant search results. In most cases, the goal is to deliver the information queried by a user rather than have a user sort through a list of loosely related keyword results.
Other authors primarily regard semantic search as a set of techniques for retrieving knowledge from richly structured data sources like ontologies as found on the Semantic Web. Such technologies enable the formal articulation of domain knowledge at a high level of expressiveness and could enable the user to specify his intent in more detail at query time.