Semantic Search: On the way to Understand the user’s psychology
The word “Semantic” stands for “related to the meaning” or “ study of the meaning”. Any semantic-based search engine(SBSE) shows the information taking in account the intention and the purpose of any user. It takes the query of the user and when the user click at the search, the user is redirected to a particular webpage that gives the top 10 back to back equivalent open directory project(ODP) categories which are constituted after comparing to the C context string. It uses the DBpedia system which is a setup used for extracting well-structured information from Wikipedia and make it available to the provided system. Some examples of SBSE search engines are :Yebo, Hakia, Kosmix, Swoogle etc.
Serving the user demanded dishes
A special web directory that classifies the web pages according to their demanded content, is used to find those web pages which are related to the demand or query intention of the user. Open directory project is used for this purpose, which is a human-improved system of the web. It uses the DBpedia as the extractor of structured data from Wikipedia, and Wordnet , which is a lexical database used to group words into sets of synonyms(synsets) to make the ODP.
Using web sentiments analysis tools
Web sentiments analysis tools are explored very recently which are mainly used by the social and enterprising sites, however overall implementations of this tools is still in process. It is lagging behind may be due to lack of sufficient quality. But the semantic-backed sentimental analysis are expected to have a better chance of gratifying the social ,Web and the enterprise users. The advantages that are expected to be provided by the semantics are :
- Explanation of the of the sentiment style by disclosing the drivers of the sentiments in users view
- Higher accuracy rates of the attribution of sentiments with the exactness of the entity.
Recovering the related Web addresses(Urls)
The list of all possible categories related to the directory are provided by the ODP’s RDF dumps. The matching is done between the algorithm of query expansion and all the sub categories under ODP to extract the context string with the top 10 matches, which are displayed using the user-interface to that particular user and then many option are provided to him so that he can opt the closest one or the one which tends to satisfy the user’s demand. Correct option is connected to an online connection to extract the url and then provided it.
Advantages of using Semantic Web Technology
It allows data analysis in more advanced way and consolidative information discovery based on the vast ocean of data in the web.
Exposition of the legacy data via a semantic layer to use it more easily and comfortably recombined.
Implementations of the reasoning capacity like transitive property and sub classing at the semantic layer, which increases the data expressiveness for the extraction of more close answers.
Associating information across database limits for enabling search, navigation and intuitive query to the great extent
Every user searches anything through the search engine with a particular purpose or aim, and an ideal search engine is the one which interprets the user’s intention and shows the results according to that. The lack of this facility among the traditional search engines may overcome by the SBSE .
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