in the future based on the location and the movement of the public, the AI will predict what kind of activity is going in that location also will predict.
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]
Конец ознакомительного фрагмента.
Текст предоставлен ООО «ЛитРес».
Прочитайте эту книгу целиком, купив полную легальную версию на ЛитРес.
Безопасно оплатить книгу можно банковской картой Visa, MasterCard, Maestro, со счета мобильного телефона, с платежного терминала, в салоне МТС или Связной, через PayPal, WebMoney, Яндекс.Деньги, QIWI Кошелек, бонусными картами или другим удобным Вам способом.