اسدی، مریم (1394). تأثیر سبک شناختی، نوع وظیفه، و میزان تجربه بر عملکرد جستجوی کاربران در وب. مطالعات ملی کتابداری و سازماندهی اطلاعات،26 (3)، 39-63.
تولایی، روح‌الله؛ خلیلی، حسن؛ و ابوالعباسی، احسان (1397). مدل‌سازی ساختاری تفسیری مأموریت‌های دانشی، پژوهشی و فناوری دانشگاه‌ها (مورد مطالعه: دانشگاه جامع امام حسین (ع)). مدیریت راهبردی دانش سازمانی، 1 (1)، 115-132.
حیاتی، زهیر؛ طاهریان، آمنه سادات (1388). بررسی مقایسه‌ای الگوی جستجوی کلیدواژه‌ای با دریافت کمک و الگوی جستجوی بدون دریافت کمک در موتور کاوش گوگل از دیدگاه کاربران. مطالعات تربیتی و روانشناسی دانشگاه فردوسی مشهد، 10 (2)، 91-112.
خسروی، عبدالرسول؛ فتاحی؛ رحمت‌الله؛ پریرخ، مهری؛ و دیانی، محمدحسین (1391). تحلیل بسط جستجوی کاربران در موتور کاوش گوگل برپایه نظریۀ بار شناختی. کتابداری و اطلاع‌رسانی، 16 (2)، 9-34.
خسروی، عبدالرسول؛ فتاحی، رحمت‌الله؛ پریرخ، مهری؛ و دیانی، محمدحسین (1392). بررسی کارآمدی کلیدواژه‌ها و عبارت‌های پیشنهادی موتور کاوش گوگل در بسط جستجو و افزایش ربط از دیدگاه دانشجویان تحصیلات تکمیلی. پژوهش‌نامه کتابداری و اطلاع‌رسانی، 3 (1)، 133-150.
فیروزجائیان، علی‌اصغر؛ فیروزجائیان، مجتبی؛ هاشمی پطرودی، سیدحمید؛ و غلامرضازاده، فاطمه (1392). کاربرد تکنیک مدل‌سازی ساختاری تفسیری (ISM) در مطالعات گردشگری (تحلیلی با رویکرد آسیب‌شناسانه). برنامه‌ریزی و توسعه گردشگری، 2 (6)، 129-159.
معتمدی‌‌مهر، شهرزاد؛ تاران، مجید؛ برادران هاشمی، علی؛ و میبدی، محمدرضا (1389، آبان). سیستم پیشنهاددهنده وب با استفاده از اتومای یادگیر توزیع‌شده و پارتیشن‌بندی گراف. مقاله ارائه‌شده در چهارمین کنفرانس داده کاوی، تهران. بازیابی 13 خرداد 1398، از https://www.civilica.com/Paper-IDMC04-IDMC04_051.html
Abbache, A., Meziane, F., & Belalem, G. (2016). Arabic query expansion using wordNet and association rules. International journal of intelligent information technologies, 12 (3), 51-64
Allen, B. (1991). Topic knowledge and online catalog search formulation. Library Quarterly, 61 (2), 188-213.
Allen, B. (1992). Cognitive differences in end user searching of a CD-ROM index. In Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, June 21-24, (pp. 298-309). New York: ACM.
Al-Maskari, A., &
Sanderson, M. (2011). The effect of user characteristics on search effectiveness in information retrieval.
Information Processing and Management, 47 (5), 719-729.
Amin, A., Hildebrand, M., van Ossenbruggen, J., Evers, V., & Hardman, L. (2009). Organizing suggestions in autocompletion interfaces. In Proceedings of the 31th European Conference on Information Retrieval, ECIR, April 6-9, (pp. 521-529). Berlin, Germany: Springer-Verlag.
Aula, A., Khan, R., & Guan, Z. (2010). How does search behavior change as search becomes more difficult? In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems, April 10-15, (pp. 35-44). New York: ACM.
Baraglia, R., Castillo, C., Donato, D., Nardini, F. M., Perego, R., & Silvestri, F. (2009). Aging effects on query flow graphs for query suggestion. In Proceedings of the 18th ACM Conference on Information and Knowledge Management, November 2-6, (pp. 1947-1950). New York: ACM.
Bar-Yossef, Z., & Kraus, N. (2011). Context-sensitive query auto-completion. In Proceedings of the 20th International Conference on World Wide Web, March 28 - April 1, (pp. 107-116). New York: ACM.
Bhatia, S., Majumdar, D., & Mitra, P. (2011). Query suggestion in the absence of query logs. In Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, July 24-28, (pp. 795-804). New York: ACM.
Cao, H., Jiang, D., Pei, J., He, Q., Liao, Z., Chen, E., et al. (2008). Context-aware query suggestion by mining click-through and session data. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 24-27, (pp. 875-883). New York: ACM.
Chen, W., Cai, F., Chen, H., & de Rijke, M. (2018). Attention-based hierarchical neural query suggestion. In Proceedings of the 41th Intrnational ACM SIGIR Conference on Research and Development in Information Retrieval, July 8-12, (pp. 1093-1096). New York: ACM.
Chen, W., Hao, Z., Shao, T., & Chen, H. (2018). Personalized query suggestion bansed on user behavior. International Journal of Modern Physics C, 29 (4), 1-15.
Dehghani, M., Rothe, S., Alfonseca, E., & Fleury, P. (2017). Learning to attend, copy, and generate for session-based query suggestion. In Proceedings of the 17th ACM on Conference on Information and Knowledge Management, November 6-10, (pp. 1747-1756). New York: ACM.
Duggan, G. B., & Payne, S. J. (2008). Knowledge in the head and on the web: Using topic expertise to aid search. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, April 5-10, (pp. 39-48). New York: ACM.
Fattahi, R., Parirokh, M., Dayyani, M. H., Khosravi, A., & Zareivenovel, M. (2016). Effectiveness of Google keyword suggestion on user’ relevance judgment. The Electronic Library, 34 (2), 302-314.
Hölscher, G., & Strube, G. (2000). Web search behavior of internet experts and newbies. Computer Networks, 33 (1-6), 337-346.
Hu, S., Xiao, C., & Ishikawa, Y. (2018). An efficient algorithm for location-aware query autocompletion. IEICE Transactions Information and Systems, 101 (1), 181-192.
Huang, Z., & Mamoulis, N. (2017). Location-aware query recommendation for search engines at scale. In Proceedings of the 15th International Symposium Advances in Spatial and Temporal Databases, August 21-23, (pp. 203-220). Berlin, Germany: Springer.
Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N. (2001). Gender and the internet: Women communicating and men searching. Sex Roles, 44 (5), 363-379.
Joho, H., Coverson, C., Sanderson, M., & Beaulieu, M. (2002). Hierarchical presentation of expansion terms. In Proceeding of 2th ACM Symposium on Applied Computing, March 11-14, (pp. 645-649). New York: ACM.
Kamvar, M., & Baluja, S. (2008). Query suggestions for moblie search: Understanding usage patterns. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI, April 5-10, (pp. 1013-1019). New York: ACM.
Kato, M. P., Sakai, T., & Tanaka, K. (2012). Structured query suggestion for specialization and parallel movement: Effect on search behaviors. In Proceedings of the 21st International Conference on World Wide Web, April 16-20, (pp. 389-398). New York: ACM.
Kato, M. P., Sakai, T., & Tanaka, K. (2013). When do people use query suggestion? A query suggestion log analysis. Information Retrieval, 16 (6), 725-746.
Kelly, D., Cushing, M. D., Niu, X., & Gyllstrom K. (2010). Effect of popularity and quality on the usage of query suggestion during information search. In Proceeding of the 28th ACM Conference Human Factors in Computing Systems, April 10-15, (pp. 45-54). New York: ACM.
Kharitonov, E., & Serdyukoy, P. (2012). Demographic context in web search re-ranking. In Proceedings of the 21st ACM International Conference on Information and Knowledge Management, October 29 - November 2, (pp. 2555-2558). New York: ACM.
Kim, K. S. (2001). Information seeking on the web: Effects of user and task variables. Library and Information Science Research, 23 (3), 233-255.
Kim, K. S., & Allen, B. (2002). Cognitive and task influences on web searching behavior. Journal of the American Society for Information Science and Technology, 53 (2), 109-119.
Lazonder, A. W., Biemans, H. J. A., & Wooereis, I. G. H. (2000). Differences between novice and experiences users in searching information on the World Wide Web. Journal of the American Society for Information Science, 51 (6), 576-581.
Lee, A., & Chau, M. (2011). The impact of query suggestion in E-commerce websites. In Lecture Notes in Business Information Processing (Vol. 108, pp. 248-254). Berlin: Springer.
Liu, Y., Song, R., Chen, Y., Nie, J.-Y, & Wen, J.-R. (2012). Adaptive query suggestion for difficult queries. In SIGIR '12 Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, August 12-16, (pp. 15-24). New York: ACM.
Liu, C., Zhang, X., & Huang, W. (2016). The exploration of objective task difficulty and domain knowledge effects on users query formulation. In Proceedings of the Association for Information Science and Technology, 53 (1), 1-9.
Lopes, C. T., Paiva, D., & Ribeiro, C. (2017). Effects of language and terminology of query suggestions on medical accuracy considering different user characteristics. Journal of the Association for Information Science and Technology, 68 (9), 2063-2075.
Lopes, C. T., & Ribeiro, C. (2013). Measuring the value of health query translation: an analysis by user language proficiency. Journal of the American Society for Information Science and Technology, 64 (5), 951-963.
Miyanishi, T., & Sakai, T. (2013).
Time-aware structures query suggestion. In
SIGIR '13 Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, July 28 - August 1, (pp. 809-812)
. New York: ACM.
Monchaux, S., Amadieu, F., Chevalier, A., & Marine, C. (2015). Query strategies during information searching: Effects of prior domain knowledge and complexity of the information problems to be solved. Information Processing and Management, 51 (5), 557-569.
Niu, X., & Kelly, D. (2014). Use of query suggestions during information search. Information Processing and Management, 50 (1), 218-234.
Paek, T., Lee, B., & Thiesson, B. (2009). Designing phrase builder: a mobile real-time query expansion interface. In Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services, September 15-18, (pp. 1-7). New York: ACM.
Palmquist, R. A., & Kim, K. S. (2000). Cognitive style and online database search experience as predictors of web search performance. Journal of the American Society for Information Science, 51 (6), 558-566.
Qi, S., Wu, D., & Mamoulis, N. (2016). Location aware keyword query suggestion based on document proximity. IEEE Transactions on Knowledge and Data Engineering, 28 (1), 82-97.
Qiu, L. (1993). Analytical searching vs. Browsing in hypertext information retrieval systems. Canadian Jouranl of Information and Library Science, 18 (4), 1-13.
Shaikh, M. T., Pera, M. S., & Ng, Y.-K. (2013). A probabilistic query suggestion approach without using query logs. I
n Proceedings of the 2013 IEEE International Conference on Tools with Artificial Intelligence, November 4-6, (pp
. 633-639). Piscataway,
New Jersey:
IEEE.
Shokouhi, M. (2013). Learning to personalize query auto-completion. In Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, July 28 - August 1, (pp. 103-112). New York: ACM.
Shokouhi, M., & Randisky, K. (2012). Time-sensitive query auto-completion. In SIGIR '12 Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval,August 12-16, (pp.601-610).New York: ACM.
Vakkari, P., Pennanen, M., & Serola, S. (2003). Changes of search terms and tactics while writing a research proposal: a longitudinal case study. Information Processing and Management, 39 (3), 445-463.
Wacholder, N. (2011). Interactive query formulation. Annual Review of Information Science and Technology, 45 (1), 157-196.
Ward, D., Hahn, J., & Feist, K. (2012). Autocomplete as research tool: a study on providing search suggestion. Information Technology and Libraries, 31 (4), 6-19.
Werber, I., & Castillo, C. (2010). The demographics of web search. In Proceedings of 33rd Inernational ACM SIFIR Conference on Research and Development in Information Retrieval, July 19-23, (pp. 523-530). New York: ACM.
White, R. W., & Marchionini, G. (2007). Examining the effectiveness of real-time query expansion. Information Processing and Management, 43 (3), 685-705.
White, R. W., Ruthven, I., & Jose, J. M. (2005). A study of factors affecting the utility of implicit relevence feedback. In Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, August 15-19, (pp. 35-42). New York: ACM.
Whiting, S., McMinn, J., & Jose, J. M. (2013, April). Exploring real-time temporal query auto-completion. Paper presented at the 13th Dutch-Belgian Workshop on Information Retrieval, Delft, Netherlands. Retrieved June 2, 2019, from http://ceur-ws.org/Vol-986/paper_14.pdf
Wildemuth, B. M. (2004). The effects of domain knowledge on search tactic formulation. Journal of the American Society for Information Science and Technology, 55 (3), 246-258.
Zhang, X., & Peng, L. (2018). Time-aware diversified queyr suggestion. In Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries, June 3-7, (pp. 399-400). New York: ACM.
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