Analyzing and Tuning User Queries to Search Engines

published in Studia Universitatis Babeş-Bolyai, Seria Informatica, Vol. LVII, No. 3, pp. 41-48, 2012.

Cite as

Full paper

Analyzing and Tuning User Queries to Search Engines


Darius Bufnea
Department of Computer Science, Faculty of Mathematics and Computer Science,
Babeş-Bolyai University of Cluj-Napoca


There are certain situations when a web site’s visitor using a search engine as a referrer will not be correctly redirected to the desired product or information page, although such a page exists within the web site. This paper presents a solution for a web site to locally further analyze and tune user queries to search engines in order to lead the user to the page describing the product he is interested in. This can improve the visibility of products within the website and in the same time increase its conversion rate. Misdirecting the user and failing in satisfying his interest will be reflected in the revenue amount of a website; on the contrary, satisfied visitors can become potential clients and on a long time scale can improve the website’s ranking within a search engine.

Key words

Web Referrer, Search Query, User Experience

BibTeX bib file



  1. Sergey Brin, Rajeev Motwani, Jeffrey D. Ullman, Shalom Tsur, Dynamic itemset counting and implication rules for market basket data, in Proceedings of the 1997 ACM SIGMOD international conference on Management of data 1997 (SIGMOD ’97), New York, NY, USA, pp. 255-264.
  2. Alexandros Nanopoulos, Yannis Manolopoulos, Efficient similarity search for market basket data, The VLDB Journal 11, 2 (October 2002), pp. 138-152.
  3. Alina Campan, Darius Bufnea, Automatic Support for Improving Interaction with a Web Site, in Studia Universitatis Babeș-Bolyai, Informatica, Vol. XLV(2), pp. 95-103, 2000.
  4. Poonam Goyal, Navneet Goyal, Ashish Gupta, T. S. Rahul, Designing self-adaptive websites using online hotlink assignment algorithm, in Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia 2009 (MoMM ’09), ACM, New York, NY, USA, pp. 579-583.
  5. Martin Hepp, GoodRelations: An Ontology for Describing Products and Services Offers on the Web, in Proceedings of the 16th International Conference on Knowledge Engineering and Knowledge Management (EKAW2008), Acitrezza, Italy, September 29 – October 3, 2008, Springer LNCS, Vol. 5268, pp. 332-347.
  6. R. Fielding, J. Gettys, J. Mogul, H. Frystyk, L. Masinter, P. Leach, T. Berners-Lee, Hypertext Transfer Protocol — HTTP/1.1, RFC 2616, June 1999.
  7. Google Analytics, Google Inc.,

Darius Bufnea