2011 ADomainSpecificOntologyBasedSem
- (Mukhopadhyay et al., 2011) ⇒ Debajyoti Mukhopadhyay, Aritra Banik, Sreemoyee Mukherjee, Jhilik Bhattacharya, and Young-Chon Kim. (2011). “A Domain Specific Ontology Based Semantic Web Search Engine.” In: Proceedings of 7th International Workshop on MSPT (MSPT 2007).
Subject Headings: Ontology Search System; Semantic Search System.
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Abstract
Since its emergence in the 1990s the World Wide Web (WWW) has rapidly evolved into a huge mine of global information and it is growing in size everyday. The presence of huge amount of resources on the Web thus poses a serious problem of accurate search. This is mainly because today's Web is a human-readable Web where information cannot be easily processed by machine. Highly sophisticated, efficient keyword based search engines that have evolved today have not been able to bridge this gap. So comes up the concept of the Semantic Web which is envisioned by Tim Berners-Lee as the Web of machine interpretable information to make a machine processable form for expressing information. Based on the semantic Web technologies we present in this paper the design methodology and development of a semantic Web search engine which provides exact search results for a domain specific search. This search engine is developed for an agricultural Website which hosts agricultural information about the state of West Bengal.
1. INTRODUCTION
A search engine is a document retrieval system designed to help find information stored in a computer system, such as on the World Wide Web, inside a corporate or proprietary network, or in a personal computer. The search engine allows one to ask for content meeting specific criteria (typically those containing a given word or phrase) and retrieves a list of items that match those criteria. Regardless of the underlying architecture, users specify keywords that match words in huge search engine databases, producing a ranked list of URLs and snippets of Web-pages in which the keywords matched. Although such technologies are mostly used, users are still often faced with the daunting task of sifting through multiple pages of results, many of which are irrelevant. Surveys indicate that almost 25% of Web searchers are unable to find useful results in the first set of URLs that are returned 6. Tim Berners-Lee, the inventor of the World Wide Web, defines the Semantic Web as “The Web of data with meaning in the sense that a computer program can learn enough about what the data means in order to process it” 1. Rather than a Web filled only with human-interpretable information, Berners-Lee’s vision includes an extended Web that incorporates machine interpretable information, enabling machines to process the volumes of available information, acting on behalf of their human counterparts 7. In this paper, we discuss the basic idea of the semantic Web and describe a design and development methodology for a domain specific semantic Web search engine based on ontology matching which not only overcomes the problem of knowledge overhead but also supports complex queries. Further, it is able to produce exact answers that in one hand satisfy user queries and on the other hand are selfexplanatory and understandable by end users.
2. SEMANTIC WEB SEARCH ENGINE
2.1 The working of a regular search engine
For most internet users, a search engine is the starting point of finding desired information in the Web. The most common form of text search used by the majority of popular search engines on the Web is keyword based search that is, they do their text query and retrieval using keywords. The working of any regular search engine may be summarized as follows:
- Search engine searches its enormous database for the keyword - entered by the user (after pressing the search button.)
- Every engine has its own collection system to fill its database.
- Indexing system is used to organize the database - permits faster searching.
- Returns a list of hit - includes relevant (as well as irrelevant) pages
This keyword based search technique gives rise to several problems listed as follows:
- The Web is growing much faster than any present-technology search engine can possibly index.
In 2006, some users found major search-engines became slower to index new Web-pages. Keyword searches have a tough time distinguishing between words that are spelled the same way, but mean something different. This often results in hits that are completely irrelevant to the query.
- Some search engines also have trouble with stemming, i.e., if the word " big" is entered, should it return a hit on the word, " bigger? " What about singular and plural word]]s?
What about verb tenses that differ from the word someone entered by only an " s" or an "ed"?
- Search engines also cannot return hits on keywords that mean the same, but are not actually entered in the query.
A query on heart disease would not return a document that used the word "cardiac" instead of "heart".
- Users are returned thousands to millions of Web pages in return of their queries, of which majority prove to be irrelevant to the query submitted and is impossible for any user to go through.
In view of the above mentioned problems, come up the concept of semantic Web and semantic Web search engines.
2.2 Semantic Web and Semantic Search Engine
3. ONTOLOGY
4. OUR APPROACH
4.1. What is RDF (Resource Description Framework)
4.2. The Design of the Semantic Web Search Engine
5. EXPERIMENTAL RESULTS
5.1. Performance Analysis:
5.2 Graph Plotting:
6. CONCLUSIONS AND FUTURE WORK
References
1. Berners-Lee.T,1999. Weaving the Web:The Original Design and Ultimate Destiny of the World Wide Web by its Inventor, New York:Harper San Francisco.
2. A Guide to Creating Your First Ontology:Natalya F. Noy and Deborah L. McGuinness; Stanford U. Report.
3. T. R. Gruber. A translation approach to portable ontologies. Knowledge Acquisition,5(2):199-220, 1993.
4. T. Berners-Lee et al 2001. The Semantic Web. Scientific American. May 2001.
5. Swoogle 2005. http://swoogle.umbc.edu/.
6. W.Roush, Search beyond Google. Technology Review. March 2004. http://www.technologyreview.com/articles/print_versio n/roush0304.asp.
7. David E. Goldschmidt and Mukkai Krishnamoorthy; Architecting a Search Engine for the Semantic Web.
8. Tim Bray, What is RDF? http://www.xml.com/lpt/a/2001/01/24/rdf.html
9. W3C, RDF Primer, W3C Working Draft 23 January 2003, http://www.w3.org/TR/2003/WD-rdfprimer-20030123/
10. W3C, Resource Description Framework (RDF) Model and Syntax Specification, W3Crecommendation February 1999, http://www.w3.org/TR/1999/REC-rdfsyntax-19990222
11. W3C, RDF Vocabulary Description Language 1.0: RDF Schema, W3C Working Draft 23 January 2003, http://www.w3.org/TR/rdf-schema/.
12. Sean B Palmer,The Semantic Web: An Introduction,2001,http://infomesh.net/2001/swintro/ .
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2011 ADomainSpecificOntologyBasedSem | Debajyoti Mukhopadhyay Aritra Banik Sreemoyee Mukherjee Jhilik Bhattacharya Young-Chon Kim | A Domain Specific Ontology Based Semantic Web Search Engine | 2011 |