Skip to main content
SpringerLink
Log in

Intelligent system for visual web content analytics: A new approach and case study

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

The accuracy of searches for visual data elements, as well as other types of information, depends on the terms used by the user in the input query to retrieve the relevant results and to reduce the irrelevant ones. Most of the results that are returned are relevant to the query terms, but not to their meaning. For example, certain types of web contents hold hidden information that traditional search engines are unable to retrieve. Searching for the mathematical construct of 1/x using Google will not result in the retrieval of the documents that contain the mathematically equivalent expressions (i.e. x−1). Because conventional search engines fall short of providing math-search capabilities. One of these capabilities is the ability of these search engines to detect the mathematical equivalence between users’ quires and math contents. In addition, users sometimes need to use slang terms, either to retrieve slang-based visual data (e.g. social media content) or because they do not know how to write using classical form. To solve such a problem, this paper proposed an AI-based system for analysing multilingual slang web contents so as to allow a user to retrieve web slang contents that are relevant to the user’s query. The proposed system presents an approach for visual data analytics, and it also enables users to analyse hundreds of potential search results/web pages by starting an informed friendly dialogue and presenting innovative answers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Abd Elraouf E, Badr N, Tolba M (2010) An efficient ranking module for an Arabic search engine. International Journal of Computer Science and Network Security 10(2):218–225

  2. Ahmed F and Nurnberger A (2008) Arabic/English word translation disambiguation approach based on Naïve Bayesian classifier. Proceeding of the international Multiconference on computer science and information technology (IMCSIT); Wisia. 331-338

  3. Al-Kuyam F (2009) Expanding the grammar of equivalence rules (GER) for mathematical search. Thesis, Jordan University of Science and Technology

  4. Al-Rashdan B (2008) Time expressions in Jordanian spoken Arabic: an ethno-linguistic statement. Jordan Journal of Modern Languages and Literature 1(1):61–80

    Google Scholar 

  5. Al-Saidat E, Al-Momani I (2010) Future markers in modern standard Arabic and Jordanian Arabic: a contrastive study. Eur J Soc Sci 12(3):397–408

    Google Scholar 

  6. Al-Shalabi R, Kanaan G, Al-Sarayreh B, Khanfar K, Al-Ghonmein A, Talhouni H, and Al-Azazmeh S. Proper Noun (2009) Extracting algorithm for Arabic language. Proceedings of the international Conference on information technology to celebrate S. Charmonman's 72nd birthday. Thailand 28.1–28.9

  7. Clough P, Sanderson M (2013) Evaluating the performance of information retrieval systems using test collections Information Research, http://InformationR.net/ir/18-2/paper582.html. Accessed 23 October 2016

  8. Drost I (2005) Developing intelligent search engines. Proceeding of 22nd chaos communication congress; private investigations; berlin

  9. El Sayed KN (2015) An Arabic natural language Interface system for a database of the holy Quran. International Journal of Advanced Research in Artificial Intelligence 4(7):9–14

  10. Elabd E, Alshari E, Abdulkader H (2015) Semantic Boolean Arabic information retrieval. Proceeding of The International Arab Journal of Information Technology 12:3

    Google Scholar 

  11. Google (2016) http://www.google.com. Accesses December 11 2016

  12. Grehan M (2003) Search Engine Marketing: The Essential Best Practice Guide www.search-engine-book.co.uk. Accessed December 16 2016.

  13. Inamdar SA, Shinde GN (2008) An Agent Based Intelligent Search Engine System For Web Mining. Research, Reflections and Innovations in Integrating ICT in Education, Lisbon, pp 1062–1065. https://pdfs.semanticscholar.org/9be6/0e3666d165cd191f7d3b621d12a07463ff16.pdf

  14. Interactive - Intelligent (AI Powered) Technologies- The Web New Frontier. http://www.gaset-gbset.com. Accessed 10 November 2016

  15. Kowalski J and Maybury T (2000) Information storage and retrieval systems: theory and implementation. 2nd Edition. Springer, New York

  16. Luo G (2009) Design and Evaluation of the iMed Intelligent Medical Search Engine. In: Proceeding of ICDE’09, pp. 1379–1390

  17. Mahafza R. (2010) Retrieving Arabic textual documents based on queries written in Arabic slang language. Thesis, Jordan University of Science and Technology, Jordan

  18. Nwesri A (2008) Effective retrieval techniques for Arabic text. Dissertation, RMIT University

  19. Sanan M, Rammal M, Zreik K (2008) Internet Arabic search engines studies. Proceeding of the 3rd international Conference on information and communication technologies,1-8. doi: 10.1109/ICTTA.2008.4530003

  20. Shaikh F, Siddiqui UA, Shahzadi I, Jami SI, Shaikh ZA (2010) SWISE: semantic web based intelligent search engine. 2nd IEEE international Conference on information and emerging technologies, Karachi

  21. Shatnawi MQ, Abuein Q (2012) A Digital Ecosystem-based Framework for Math Search Systems. International Journal of Advanced Computer Science and Applications 3:3

    Google Scholar 

  22. Shatnawi MQ, Youssef A (2007) Equivalence Detection Using Parse-tree Normalization for Math Search. IEEE 2nd International Conference on Digital Information Management, 643–648, France

  23. Shatnawi MQ, Yassein MB, Mahafza R (2012) A framework for retrieving Arabic document based on queries written in Arabic slang language. Journal of Information Science 38(4):350–365

    Article  Google Scholar 

  24. Shatnawi MQ, Abuein Q, Mahafza R (2014a) Classical to slang conversion for retrieving Arabic documents using slang queries. Journal of Information Science 40(2):146–153

    Article  Google Scholar 

  25. Shatnawi M, Alrousan M, Amareen S (2014b) Content-based image retrieval for medical applications using low level image descriptors. International Conference on computational and experimental science and engineering, October 2014, Turkey

  26. Sun L. (2009) Smart search engine for information retrieval. Dissertation, Durham University

  27. Web Search Engines (2016) Wikipedia-the free encyclopaedia http://en.wikipedia.org/wiki/Web_search_engine. Accessed January 3 2017

  28. Zhang H, Ma Y, Zhang Q, Xie P, Bao Z (2009) Personalized intelligent search engine based on web data mining. International Workshop on Information Security and Application, China

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Computer and Information Technology, Jordan University of Science and Technology, P. O. Box 3030, Irbid, 22110, Jordan

    Qusai Q. Abuein, Mohammed Q. Shatnawi & Muneer Bani Yassein

  2. Computer Science Department, Shaqra University, Shaqra, Kingdom of Saudi Arabia

    Reem Mahafza

Authors
  1. Qusai Q. Abuein
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohammed Q. Shatnawi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Muneer Bani Yassein
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Reem Mahafza
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammed Q. Shatnawi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abuein, Q.Q., Shatnawi, M.Q., Yassein, M.B. et al. Intelligent system for visual web content analytics: A new approach and case study. Multimed Tools Appl 77, 17557–17571 (2018). https://doi.org/10.1007/s11042-017-4740-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-4740-8

Keywords

Search

Navigation