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Computational Analysis and Deep Learning for Medical Care. Группа авторов
Читать онлайн.Название Computational Analysis and Deep Learning for Medical Care
Год выпуска 0
isbn 9781119785736
Автор произведения Группа авторов
Жанр Программы
Издательство John Wiley & Sons Limited
References
1. Baeza-Yates, R., Hurtado, C., Mendoza, M., Query recommendation using query logs in search engines, in: EDBT, pp. 588–596, 2004.
2. Beeferman, D. and Berger, A., Agglomerative clustering of a search engine query log, in: KDD, pp. 407–416, 2000.
3. Cao, H., Jiang, D., Pei, J., He, Q., Liao, Z., Chen, E., Li, H., Context-aware query suggestion by mining click-through and session data, in: KDD, pp. 875–883, 2008.
4. Qi, S., Wu, D., Mamoulis, N., Location aware keyword Query suggestion based on document proximity. IEEE Trans. Knowl. Data Eng., 28, 1, 82–97, 2016.
5. Berkhin, P., Bookmark-coloring algorithm for personalized pagerankcomputing. Internet Math., 3, 41–62, 2006.
6. Craswell, N. and Szummer, M., Random walks on the click graph, in: Proc. 30th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 239–246, 2007.
7. Mei, Q., Zhou, D., Church, K., Query suggestion using hitting time, in: Proc. 17th ACM Conf. Inf. Knowl. Manage, pp. 469–478, 2008.
8. Song, Y. and He, L.-W., Optimal rare query suggestion with implicit user feedback, in: Proc. 19th Int. Conf. World Wide Web, pp. 901–910, 2010.
9. Miyanishi, T. and Sakai, T., Time-aware structured query suggestion, in: Proc. 36th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 809–812, 2013.
10. Tong, H., Faloutsos, C., Pan, J.-Y., Fast random walk withrestart and its applications, in: Proc. 6th Int. Conf. Data Mining, pp. 613–622, 2006.
11. Boldi, P., Bonchi, F., Castillo, C., Donato, D., Gionis, A., Vigna, S., The query-flow graph: Model and applications, in: Proc. 17thACM Conf. Inf. Knowl. Manage, pp. 609–618, 2008.
12. Song, Y., Zhou, D., He, L.-w., Query suggestion by constructing term-transition graphs, in: Proc. 5th ACM Int. Conf. Web Search Data Mining, pp. 353–362, 2012.
13. Kato, M.P., Sakai, T., Tanaka, K., When do people use query suggestion? A query suggestion log analysis. Inf. Retr., 16, 6, 725–746, 2013.
14. Liu, Y., Song, R., Chen, Y., Nie, J.-Y., Wen, J.-R., Adaptive query suggestion for difficult queries, in: Proc. 35th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 15–24, 2012.
15. Zhang, Z. and Nasraoui, O., Mining search engine query logs for query recommendation, in: Proc. 15th Int. Conf. World Wide Web, pp. 1039–1040, 2006.
16. Cucerzan, S. and White, R.W., Query suggestion based on user landing pages, in: Proc. 30th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 875–876, 2007.
17. J. Myllymaki, D. Singleton, A. Cutter, M. Lewis, S. Eblen, Location based query suggestion. U.S. Patent 8 301 639, Oct. 30, 2012.
18. Gaasterland, T., Cooperative answering through controlled query relaxation. IEEE Expert, 12, 5, 48–59, Sep. 1997.
19. Song, Y., Zhou, D., He, L.-w., Post-ranking query suggestion by diversifying search results, in: Proc. 34th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 815–824, 2011.
20. Zhu, X., Guo, J., Cheng, X., Du, P., Shen, H.-W., A unified framework for recommending diverse and relevant queries, in: Proc. 20th Int. Conf. World Wide Web, pp. 37–46, 2011.
21. Wen, J.-R., Nie, J.-Y., Zhang, H.-J., Clustering user queries of asearch engine, in: Proc. 10th Int. Conf. World Wide Web, pp. 162–168, 2001.
22. Dhillon, I.S., Co-clustering documents and words using bipartite spectral graph partitioning, in: Proc. ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, pp. 269–274, 2001.
23. Pass, G., Chowdhury, A., Torgeson, C., A picture of search, in: Proc. 1st Int. Conf. Scalable Inf. Syst, 2006.
24. Bhatia, S., Majumdar, D., Mitra, P., Query suggestions in the absence of query logs, in: Proc. Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 795–804, 2011.
25. Baeza-Yates, R. and Tiberi, A., Extracting semantic relations from query logs, in: Proc. 13th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, pp. 76–85, 2007.
26. http://www.statisticbrain.com/google-searches
27. Salton, G., A theory of indexing, vol. 18, SIAM, New York, 1975.
28. Emtage, A., Archie: An electronic directory service for the internet. Proc. Winter 1992 USENIX Conf., 1992.
29. Smith, R.G. and Farquhar, A., The road ahead for knowledge management: an AI perspective. AI Mag., 21, 4, 17–17, 2000.
30. Ghafghazi, H. et al., Location-aware authorization scheme for emergency response. IEEE Access, 4, 4590–4608, 2016.
31. Tyagi, A.K. and Chahal, P., Artificial Intelligence and Machine Learning Algorithms, in: Challenges and Applications for Implementing Machine Learning in Computer Vision, pp. 188–219, IGI Global, Chennai, India, 2020.
1 *Corresponding author: [email protected]
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