Search Engine Semantics

A Semantic Search Engine could be described as an agent that allows users to search at the topic level. Once a topic of interest is identified, then drill down to the specific document. Semantics is been applied these days by search engines in a few closely related fields. A possible way, is by using statistical analysis to retrieve semantic matches to a query. With this approach, they are capable of providing relational results based on the topics and keywords given by the user, and help them in the proccess of narrowing the search to be more specific.

To outline the process, there are basically 3 steps to consider: (1) User enters a search query, with a given number of words describing wath the topic of their search is, (2) The engine returns results matching the words user entered, plus adding suggested alternatives (3) The second step repeats itself untill the results returned are sasticfactory to the user.

Automated semantic tagging is also possible, when the topic of a given page is well known. In this application, dynamic categorization of topical information about a query is implemented without any human intervention. These categorizations could take place in real time or be maintained incrementally over a time period. This is possible because there are available cognitive objects and conceptual models to identify sense information. Then these could be precisely weighted and measured, to determine the relevance among variable words forms and grammars in multiple corpus of content.

Google's application of semantics goes beyond Adsense. Relational Search is now evident when returning results from their index. This takes place if you get search results alternatives based upon an initial query you performed or after pulling pre categorised phrases on a database. Not so generalized yet due to multiple current limitations like speed, scalability and others. Performance is getting better and better, but it will be a matter of years before the big search engines start annotating webpages purely by using semantic ontologies.

By: Loredana Sargu

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