READIT - 2009 - Indira Gandhi Centre for Atomic Research

Proceedings of READIT-2009, Kalpakkam - 603 102, 29-30 Dec 2009
traditional web search, but it will not replace it. 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.
The Semantic Search Engine or Third-Generation Search Engine is a search engine in which
Semantic technologies and / or Natural Language Processing (NLP) techniques are applied. The
semantic search engine informs its user using a rich framework for conceptual interpretation married
with the best of modern indexing and search techniques. Differently from traditional search engines,
a semantic search engine stores semantic information about Web resources and is able to solve
complex queries, considering as well the context where the Web resource is targeted. The major
semantic search engines are the following:
2.1. HAKIA –WWW.HAKIA.COM
Hakia is a semantic search engine that brings relevant results based on concept match rather than
keyword match or popularity ranking. I.e. Hakia is an ontological semantic and natural language
processing (NLP) based search engine. Hakia was founded by Riza Berkan, a nuclear scientist by
training with a specialization in artificial intelligence and fuzzy logic, and Pentti Kouri, a New Yorkbased
economist and venture capitalist. Hakia is a general purpose "semantic" search engine,
dedicated to quality search experience. Hakia’s quality search results satisfy three criteria
simultaneously: They (1) come from credible Web sites recommended by librarians, (2) represent
the most recent information available, and (3) remain absolutely relevant to the query. Hakia
semantic search is essentially built around three evolving technologies:
1. OntoSem (sense repository)
2. QDEX (Query indexing technique)
3. Semantic Rank algorithm
99