SWISE: Semantic Web based intelligent search engine

Shaikh, Faizan; Siddiqui, Usman A.; Shahzadi, Iram; Jami, Syed Imran; Shaikh, Zubair A.

doi:10.1109/iciet.2010.5625670

Cited by 22 publications

(10 citation statements)

References 3 publications

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“…This paper proposed by (Gautam and Kumar, 2012) proposes a framework for a tag-based Academic Information Sharing and Recommender System which shares information such as question papers, assignments, tutorials and quizzes on a specific area. www.ijacsa.thesai.org (Shaikh, Siddiqui and Shahzadi, 2012) (Lee, Kim, and Park 2012) presented some proposals to improve and extend the semantic approach based on conceptual neighborhood"s graphs in order to best preserve the proximity between the adapted and original documents and to deal with models that define delays and distances.…”

Section: The Existing Ranking Methodsmentioning

confidence: 99%

Semantic Web Improved with the Weighted IDF Feature

Gautam¹,

Kumar²

2015

ijacsa

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Abstract-The development of search engines is taking at a very fast rate. A lot of algorithms have been tried and tested. But, still the people are not getting precise results. Social networking sites are developing at tremendous rate and their growth has given birth to the new interesting problems. The social networking sites use semantic data to enhance the results. This provides us with a new perspective on how to improve the quality of information retrieval. As we are aware, many techniques of text classification are based on TFIDF algorithm. Term weighting has a significant role in classifying a text document. In this paper, firstly, we are extending the queries by "keyword+tags" instead of keywords only. In addition to this, secondly, we have developed a new ranking algorithm (JEKS algorithm) based on semantic tags from user feedback that uses CiteUlike data. The algorithm enhances the already existing semantic web by using the weighted IDF feature of the TFIDF algorithm. The suggested algorithm provides a better ranking than Google and can be viewed as a semantic web service in the domain of academics.

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Section: The Existing Ranking Methodsmentioning

confidence: 99%

Semantic Web Improved with the Weighted IDF Feature

Gautam¹,

Kumar²

2015

ijacsa

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“…First, the existing search engines do not fully serve the needs of internet users. This is because in most cases they provide results that are not accurate and relevant to users' queries [14]. Second, most of the existing search engines take a one-sizefits-all approach to ranking results.…”

Section: Issues In the Existing Search Systemsmentioning

confidence: 99%

Intelligent metadata web search engines: A brief review of literature on intelligent metadata based search engines

Mahdi

Ahmad

Ismail

2014

Proceedings of the 6th International Conference on Information Technology and Multimedia

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Search engines are vital in the current digital world. Given the huge amount of information on the internet, search engines are vital tools that internet users are using to search web pages for the required information. However, most of the search engines currently in the market are inadequate and thus do not completely serve the needs of internet users. This is because in most cases they give results that are inaccurate and irrelevant. It is thus important to deploy search engine solutions that are embedded with intelligent agents that enable the search engines to work with enormous amount of information and give the search engines the capability to learn from their environment in order to give accurate and relevant results.

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“…Moreover, search driven by key word matching is unable to return only services and service provider information that is the real requirement of service searcher and consumer. Semantic web is a hopeful technique to tackle the issue [2] . However, the vast majority service related pages are currently written by HTML language, so that search engine for semantic web cannot be extensively used.…”

Section: Introductionmentioning

confidence: 99%

A framework of service oriented semantic search engine

Tang

et al. 2011

2011 International Conference on Computational Problem-Solving (ICCP)

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A service oriented semantic search engine framework is proposed to extract automatically and accurately information on service provider on the Internet. Domain knowledge on theme and abstract service provider are modeled by ontology to guide information extraction. Theme identification for each web page is executed after the page is fetched by search engine. A page or a part of content of a page is assigned a theme. Concrete service provider entity and attributes are extracted from content of web pages based on themes of the pages. Several algorithms are developed. Computational experiments demonstrate that service oriented semantic search engine shows high recall rate and precision. Highest recall rate of concrete service provider entity exceeds 97% on tested web sites. Precision of concrete service provider entity reaches up to 100% on two tested web sites. It also shows good recall rate and precision of concrete service provider attributes.

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SWISE: Semantic Web based intelligent search engine

Cited by 22 publications

References 3 publications

Semantic Web Improved with the Weighted IDF Feature

Semantic Web Improved with the Weighted IDF Feature

Intelligent metadata web search engines: A brief review of literature on intelligent metadata based search engines

A framework of service oriented semantic search engine

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