Semantic based web search engines- Changing the world of Search by Prachi Nagpal.
From the post:
An important quality that the majority of search engines functional today lack is the ability to take into account the intention of the user behind the overall query. Basing the matching of web pages on keyword frequency and a ranking metric such as Pagerank return various results that may be of high ranking but still irrelevant to the users intended context. Therefore I explored and realized that there is a need to add semantics to the web search.
There are some semantic search engines that have already come up in the markets eg. Hakia, Swoogle, Kosmix, etc. that takes a semantic based approach which is different from the traditional search engines. I really liked their idea of implementing and adding semantics to the web search. This provoked me to do more research in this field and tried to think of different ways to add semantics.
Following is an Algorithm that can be used in Semantic Based Web Search Engines :-
So, to find web pages on the internet that match a user’s query based not only on the important keywords in a user query, but also based on the intention of the user, behind that query, first the user’s entered query is expanded using WordNet ontology.
This Algorithm focuses on work that uses the Hypernym/Hyponymy and Synset relations in WordNet for query expansion algorithm. A set of words that are highly related to the words in the user query, determined by the frequency of their occurrence in the Synset and Hyponym tree for each of the user query terms is created. This set is now refined using the same relations to get a more precise and accurate expanded query.
Interesting approach but as the comments indicate, a lack of use of RDF makes it problematic.
I would rephrase the problem statement from:
…the majority of search engines functional today lack is the ability to take into account the intention of the user behind the overall query.
to: …the majority of search engines lack the ability to accurately interpret the semantics to web accessible content.
I think we would all agree that web accessible content has semantics.
The problem is how to bring those semantics to the attention of search engines?
Or perhaps better, how do we take advantage of those semantics with current search engines, which are semantically deaf and dumb?