In this paper we address a set of important guidelines that web search engines should follow in order to become effective. We refer to the importance of semantic web in the section of search engines which comes up from the better set-up that ontologies offer. Moreover, some of the most known and adaptive learning techniques are described in order to personalize web search engines, including methods for implicit and explicit feedback. In addition, we focus on how these methods can coexist so as to achieve high performance and we investigate the role of metadata in web searching in order to detect user interests and improve the information filtering procedure. Finally, we propose how these can be combined and presented into an interface, which will be considered as user friendly.
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Cetintemel U., Franklin M. and Giles L.: Flexible user profiles for large scale data delivery. Technical report CS-TR-4005, Computer Science Department, University of Maryland, (1999)
Kelly D. and Teevan J.: Implicit Feedback for Inferring User Preference: A Bibliography. SIGIR Forum, vol. 37 (2003) 18–28
Leporini B., Andronico P. and Buzzi M.: Designing search engine user interfaces for the visually impaired. ACM International Conference Proceeding Series. Proceedings of the international cross-disciplinary workshop on Web accessibility (2004)
Gasparetti F. and Micarelli A.: Exploiting Web Browsing Histories to Identify User Needs. In: Proc. International Conference on Intelligent User Interfaces IUI 2007, Hawaii, January (2007) 28–31
Claypool, M., Le, P., Waseda M. and Brown D.: Implicit interest indicators. In: Proceedings of the 6th International Conference on Intelligent User Interfaces (IUI '01), USA, (2001) 33–40
Shen, X., Tan, B., and Zhai, C.: Context-sensitive information retrieval using implicit feedback. In: Proc. of the 28th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2005), Salvador, Brazil (2005) 43–50
Paul-Alexandru Chirita, Claudiu Firan and Wolfgang Nejdl: Summarizing Local Context to Personalize Global Web Search. In: Proceedings of the 15th ACM International CIKM Conference on Information and Knowledge Management, Arlington, United States
Salton G. and Buckley C.: Improving retrieval performance by relevance feedback. JASIS 41, 4 (1990) 288–297
Page L., Brin S., Motwani R. and T. Winograd. The PageRank citation ranking: Bringing order to the Web. Technical report, Stanford University Database Group (1998)
Haveliwala T.: Topic-sensitive pagerank. In: Proceedings of the Eleventh International World Wide Web Conference, Honolulu, Hawaii (2002)
Jeh G. and Widom J.: Scaling personalized web search. In: Proceedings of the 12th Intl. World Wide Web Conference (2003)
Sugiyama K., Hatano K., and Yoshikawa M.: Adaptive web search based on user profile constructed without any effort from users. In: Proceedings of the 13th international conference on World Wide Web (2004) 675–684
Chirita P.-A., Nejdl W., Paiu R. and Kohlschütter Chr.: Using ODP metadata to personalize search. In Proc. of the 28th Intl. ACM SIGIR Conf. (2005)
Joachims T., Granka L., Pan B., Hembrooke H. and Gay G.: Accurately interpreting clickthrough data as implicit feedback. In: Proceedings of SIGIR (2005)
Granka L., Joachims T., and Gay G.: Eye-Tracking Analysis of User Behavior in WWW Search. In: Proceedings of the Conference on Research and Development in Information Retrieval (SIGIR) (2004)
Shen Xuehua: User-Centered Adaptive Information Retrieval. In: Proceedings of ACM Conference on Research and Development on Information Retrieval (SIGIR) (2006)
Doulaverakis C., Nidelkou E., Gounaris A. and Kompatsiaris Y.: An Ontology and Content-Based Search Engine For Multimedia Retrieval, 10th East-European Conference on Advances in Databases and Information Systems, ADBIS 2006, Thessaloniki, Hellas (2006)
White R.W., Ruthven I. and Jose J.M.: A study of factors affecting the utility of implicit relevance feedback. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Salvador, Brazil (2005)
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Papoutsidakis, M., Sampati, S., Ledakis, I., Sotiropoulou, A., Giannopoulos, S. (2009). Guidelines for Web Search Engines: From Searching and Filtering to Interface. In: Sicilia, MA., Lytras, M.D. (eds) Metadata and Semantics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77745-0_37
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DOI: https://doi.org/10.1007/978-0-387-77745-0_37
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