Tytuł artykułu
Treść / Zawartość
Pełne teksty:
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
This paper reviews user-click models and the typed query profile model in order to investigate principles of faster access to documents which are in a university campus network. There wassynthesized university campus user model that is based on the task-centric click model and determines document pertinence conditions, which relies on a user class. A solution of documents search automation was suggested that assumes that users will enable to avoid wasting of time in scientific materials search.
Czasopismo
Rocznik
Tom
Strony
103--109
Opis fizyczny
Bibliogr. 15 poz., rys., tab., wykr., wz.
Twórcy
autor
- The National Aerospace University Kharkiv Aviation, Sumska St, 124, 61000 Kharkiv, Ukraine
autor
- The National Aerospace University Kharkiv Aviation, Sumska St, 124, 61000 Kharkiv, Ukraine
autor
- The National Aerospace University Kharkiv Aviation, Sumska St, 124, 61000 Kharkiv, Ukraine
autor
- The National Aerospace University Kharkiv Aviation, Sumska St, 124, 61000 Kharkiv, Ukraine
Bibliografia
- 1. Burges C., Shaked T., Renshaw E., Lazier A., Deeds M., Hamilton N., Hullender G. 2005.Learning to rank using gradient descent. Proceedings of the 22nd International Conference on Machine Learning. 89–96.
- 2. Chapelle O., Zhang Y. 2009. A dynamic bayesian network click model for web search ranking. Proceedings of the 18th International World Wide Web Conference. 1–10.
- 3. Craswell N., Zoeter O., Taylor M., Ramsey B. 2008. An experimental comparison of click position-bias models. Proceedings of the 1st ACM International Conference on Web Search and Data Mining. 87–94.
- 4. Dupret G., Liao C. 2010. A model to estimate intrinsic document relevance from the clickthrough logs of a web search engine. Proceedings of the 3rdACM International Conference on Web Search and Data Mining. 181–190.
- 5. Dupret G., Piwowarski B. 2008. A user browsing model to predict search engine click data from past observations. Proceedings of the 31st Annual ACM SIGIR Conference. 331–338.
- 6. Granka L A., Joachims T., Gay G. 2004. Eye-tracking analysis of user behavior in WWW search. Proceedings of the 27th Annual ACM SIGIR Conference. 478–479.
- 7. Guo F., Liu C., Kannan A., Minka T., Taylor M., Wang Y., Faloutsos C. 2009. Click chain model in web search. Proceedings of the 18th International World Wide Web Conference. 11–20.
- 8. Hu B., Zhang Y., Chen W., Wang G., Yang Q. 2011.Characterize search intent diversity into click models. Proceedings of the 20th International World Wide Web Conference. 17–26.
- 9. Karpukhin A., Gritsiv D., Tkachenko A. 2014. Mathematical simulation of infocommunication networks applying chaos theory. Econtechmod. An international quarterly journal.Vol. 3, No. 3, 33-42.
- 10. Piwowarski B., Dupret G., Jones R. 2009. Mining user web search activity with layered bayesian networks or how to capture a click in its context. Proceedings of the 2nd ACM International Conference on Web Search and Data Mining. 162–171.
- 11. Richardson M., Dominowska E., Ragno R. 2007. Predicting clicks: estimating the click-through rate for new ads. Proceedings of the 16th International World Wide Web Conference. 521–530.
- 12. Ryshkovets Yu., Zhezhnych P. 2013. Information model of Web-gallery taking into account user’s interests. Econtechmod. An international quarterly journal. Vol. 2, No. 3, 59–63.
- 13. Srikant R., Basu S., Wang N., Pregibon D. 2010. User browsing models: relevance versus examination. Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 223–232.
- 14. Tao K. 2014. Social Web Data Analytics: Relevance, Redundancy, Diversity. Delft University of Technology. Delft.
- 15. Zhang Y., Chen W., Wang D., Yang Q. 2011. User-click Modeling for Understanding and Predicting Search-behavior.Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 1388-1396.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8d3ae959-c283-4b26-9caf-0758fbffdb5b