Enhancing the Relevance of Semantic Web Information Retrieval Results Using Extension Theory By S.Nirmal Chander, P.Ram Prasath, V.Santhosh Kumar
Introduction The &quot; Semantic Web &quot; is a Web that includes documents, or portions of documents, describing explicit relationships between things and containing semantic information intended for automated processing by our machines.
Present Scenario Today’s information retrieval system depends on keyword-based search over entire-text data, which has a set of words in a model. Ex : Google, Bing etc. Disadvantage: The semantic meaning of the original text Is lost.
Ontologies Ontologies provide structured vocabularies that formulate the relationships between different terms, allowing intelligent agents (and humans) to interpret their meaning flexibly yet unambiguously.
Representation Of Ontologies OWL (Web Ontology Language) is a new formal language for representing ontologies in the Semantic Web. It plays an important role in helping agents to process information in Web mining.
Ontology Generation In Semantic web based on ontology, it processes the unstructured resources into structured information and adds it to the knowledgebase. Ontologies are (meta) data schemas, providing a controlled lexicons of concepts, each with an explicitly defined and machine understandable semantics
Automatic knowledge acquisition by machines is in future research. We assume the process of ontology learning as semi-automatic with human hands, adopting a approach of balanced cooperative approach for the generation of ontologies for the Semantic Web.
Problem Of Ontology Mismatch The ontology mismatch problems include : Same terms for different concepts. Different terms for the same concepts. Semantically similar attributes which have different meanings in their domains. Attributes which have different generalization and aggregation level. Same attributes, but different data quality requirements, e.g. accuracy.
Conceptualization mismatches occur as a result of semantic differences that may be due to the difference in the conceptualization of the domain. If we ignore and does not repair these mismatches then we might lose the properties that provide a powerful method for enhanced reasoning about concepts in ontologies. Problem Of Ontology Mismatch
Related Works Ontology tree Domain-ontology based semantic integration , such as Gene Ontology and Unified Medical Language System. Domain independent includes InfoSleut, OBSERVE . Disadvantage: Efficiency and comprehensive issues
Extension Theory It is used to eliminate different kinds of ontology mismatches in semantic web mining. The extension methods are the important part of Extenics, which is a new discipline studying objects’ extensibility and the laws and methods of extension to solve contradiction problems
We suggest the process of semantic conflict elimination be as follows: (i) Analyze what kind of conflict occurs. (ii) (if necessary) Represent objects for different concepts by basic elements. (iii) Choose suitable extension methods to eliminate the conflict. Extension Theory
Extension method acts as a “bridge” between extension theory (Extenics) and its actual application. Extenics is a new discipline that studies rules and methods of solving contradiction problems by employing formalized tools, i.e. qualitative analysis and quantitative analysis. Extension Methods
The basic-element theory includes: Matter-element Affair-element Relation-element. Basic-element concept is the cornerstone of Extenics. Extension Methods
Universe of Discourse To Eliminate the conflicts, a Universe of Discourse can be generated. The Universe of Discourse is used in predicate logic to indicate the relevant set of Entities
Example Example 1: When an agent visits some Web pages, it finds out that in one page a sentence says “ I use my Computer to browse Web pages” while in another page a sentence says “ I use my desktop machine to browse Web pages”. The agent could report a conflict.
Future Work After the elimination of conflicts using extension theory, the information from the knowledgebase can be used in a Query Routing System. By doing so, the system can be used in E-Governance for automated complaint(Query) reporting.
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