An intelligent web search framework for performing efficient retrieval of data

There are numerous search engines available in today's world to search and retrieve the required information. However retrieval of meaningful and appropriate formation as per the user requirement is always a challenging task. The foremost intention of any search engine is to provide the information with in a quick span of time. Since the nature of data available in World-Wide-Web shows heterogeneity in common and the sources of data are also distinct with each other, issues pertaining to schema structure and data representational are also there. In such circumstances, to eliminate inconsistencies and for enabling seamless integration of multiple data sources while retrieving web data, an efficient web search mechanism that fulfils the customer requirement is always needed. To enable the integration of multiple data sources while performing efficient retrieval of web data, an intelligent web search framework has been proposed in this paper.

[1]  Pablo de la Fuente,et al.  Context-Based Personalization for Mobile Web Search , 2008, PersDB.

[2]  Peter Nordin,et al.  Enhancing information retrieval by automatic acquisition of textual relations using genetic programming , 2000, IUI '00.

[3]  Tim Furche,et al.  Web and Semantic Web Query Languages: A Survey , 2005, Reasoning Web.

[4]  Djoerd Hiemstra,et al.  Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002 , 2003, SIGF.

[5]  D. Shalini Punithavathani,et al.  Evaluation and Study of Transition Techniques Addressed on IPv4-IPv6 , 2013 .

[6]  Sriram Raghavan,et al.  Searching the Web , 2001, ACM Trans. Internet Techn..

[7]  Hai Jin,et al.  Topic-centric and semantic-aware retrieval system for internet of things , 2015, Inf. Fusion.

[8]  Douglas K. Barry,et al.  Web Services and Service-Oriented Architecture: The Savvy Manager's Guide , 2003 .

[9]  Patrick Baudisch,et al.  Summary thumbnails: readable overviews for small screen web browsers , 2005, CHI.

[10]  David M. Mountain,et al.  Spatial filters for mobile information retrieval , 2007, GIR '07.

[11]  Yuxia Huang.  A Latent Semantic Analysis-Based Approach to Geographic Feature Categorization from Text , 2011, 2011 IEEE Fifth International Conference on Semantic Computing.

[12]  Alok Gupta,et al.  Managing computing resources in active intranets , 2002, Int. J. Netw. Manag..

[13]  James Snell,et al.  Introduction to Web services architecture , 2002, IBM Syst. J..

[14]  Michel Beigbeder,et al.  An information retrieval model using the fuzzy proximity degree of term occurences , 2005, SAC '05.

[15]  K R Baskaran.  STUDY OF COMBINED WEB PRE-FETCHING WITH WEB CACHING BASED ON MACHINE LEARNING TECHNIQUE , 2013 .

[16]  Shumeet Baluja,et al.  Browsing on small screens: recasting web-page segmentation into an efficient machine learning framework , 2006, WWW '06.

[17]  Nicolás Marín,et al.  Review of Data on the Web: from relational to semistructured data and XML by Serge Abiteboul, Peter Buneman, and Dan Suciu. Morgan Kaufmann 1999. , 2003, SGMD.

[18]  Ismailcem Budak Arpinar,et al.  Mobile web search personalization using ontological user profile , 2010, ACM SE '10.

[19]  Heather Kreger,et al.  Fulfilling the Web services promise , 2003, CACM.

[20]  Andrei Z. Broder,et al.  Graph structure in the Web , 2000, Comput. Networks.

[21]  Farhat Jahan,et al.  Towards the Next Generation of Web of Things: A Survey on Semantic Web of Things’ Framework , 2016 .