Research on the Current Development Situation of the Third-Generation Search Engine

Li Na Zhang; Zhi Yin Yang; Bo Yang

doi:10.4028/www.scientific.net/AMR.905.655

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 905Research on the Current Development Situation of...

Research on the Current Development Situation of the Third-Generation Search Engine

Abstract:

Taking the search engines mentioned in Related Documents, Alexa website and100 best alternative search engines as the basic samples, this paper selects 43 third-generation search engines according with the definition standard from 148 basic samples, and makes the investigation on selected third-generation search engines from two aspects of basic features and functions, and analyzes the investigation results from five aspects of types distribution, functions distribution , languages distribution , popularities distribution and searching effects evaluation.

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Advances in Applied Materials and Electronics Engineering III

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Periodical:

Advanced Materials Research (Volume 905)

Pages:

655-658

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.905.655

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Online since:

April 2014

Authors:

Li Na Zhang*, Zhi Yin Yang, Bo Yang

Keywords:

Intellectualization, Personalization, Socialization, Third-Generation Search Engine

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References

[1] Q Yang H W. Towards a Next-Generation Search Engine [M]. Heidelberg: Springer Berlin, 2007. 16.

Google Scholar

[2] Raisinghani M S. Search Engine Technology: A Closer Look at Its Future[J]. Information Resources Management Journal. 2005, (6): 45.

Google Scholar

[3] Nadjla Hariri. Do natural language search engines really understand what users want?: A comparative study on three natural language search engines and Google[J]. Online Information Review, 2013, (5): 372.

DOI: 10.1108/oir-12-2011-0210

Google Scholar

[4] Anonymous. Research and Markets: Search Engine Optimization Strategies for Financial Advisors - Getting Your Name at the Top of Search Engine Results as a Way to Help Land New Referrals [J]. M2 Presswire, 2010, (1): 37.

Google Scholar

[5] Lervik J M. Search Engine Technology Applied in Digital Libraries [J]. ERCIM News. 2006(03): 68.

Google Scholar

[6] VATTANI A. K-means requires exponentially many iterations even in the plane[J]．Discrete and Computational Geometry, 2011, 45 (4): 596-616.

DOI: 10.1007/s00454-011-9340-1

Google Scholar

[7] GARCIA E. Vector models based on normalized frequencies [EB/OL]．[2012-11-27]. http: /www. miislita. com/termvector /term-vector-4. html.

Google Scholar

[8] DAVID M. An example inference task: clustering. Information theory, inference and learning algorithms[M]. Cambridge University Press, 2003: 284-292.

Google Scholar