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Desktop Data Driven Approach to Personalize Query Recommendation

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成果类型:
期刊论文、会议论文
作者:
Li, Xiao-yun;Yu, Ying*
通讯作者:
Yu, Ying
作者机构:
[Li, Xiao-yun; Yu, Ying] Univ South China, Sch Comp Sci & Technol, Hengyang, Hunan, Peoples R China.
通讯机构:
[Yu, Ying] U
Univ South China, Sch Comp Sci & Technol, Hengyang, Hunan, Peoples R China.
语种:
英文
关键词:
Desktop data;Query recommendation;Search task;User model;Work task
期刊:
Communications in Computer and Information Science
ISSN:
1865-0929
年:
2017
卷:
727
期:
1
页码:
100-109
会议名称:
3rd International Conference of Pioneering Computer Scientists, Engineers and Educators (ICPCSEE)
会议论文集名称:
Data Science
会议时间:
Springer Verlag
会议地点:
Cent S Univ, Changsha, PEOPLES R CHINA
会议主办单位:
Cent S Univ
会议赞助商:
Hunan Higher Educ Federat, Comp Educ Comm
主编:
Broder, A., A taxonomy of web search (2002) 25Th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, August 2002, Tampere, Finland, 36 (2), pp. 3-10; Li, Y., Wang, B., Li, J., A survey of query suggestion in search engine (2010) J. Chin. Inf. Process., 24 (6), pp. 75-84; Carpineto, C., Romano, G., A survey of automatic query expansion in information retrieval (2012) ACM Comput. Surv. (CSUR), 44 (1), pp. 1-50; Verberne, S., Sappelli, M., Kraaij, W., Query term suggestion in academic search (2014) ECIR 2014. LNCS, 8416, pp. 560-566. , de Rijke, M., Kenter, T., de Vries, Arjen P., Zhai, C., de Jong, F., Radinsky, K., Hofmann, K. (eds.), Springer, Cham; Navigli, R., Word sense disambiguation: A survey (2009) ACM Comput. Surv., 41 (2), pp. 1-69; Hienert, D., Schaer, P., Schaible, J., Mayr, P., A novel combined term suggestion service for domain-specific digital libraries (2011) TPDL 2011. LNCS, 6966, pp. 192-203. , Gradmann, S., Borri, F., Meghini, C., Schuldt, H. (eds.), Springer, Heidelberg; Lin, Y., Lin, H., Jin, S., Social annotation in query expansion a machine learning approach (2011) Proceedings of 34Th Annual ACM SIGIR Conference, Beijing, China, July 2011, pp. 405-414; Borisov, A., Markov, I., De Rijke, M., A context-aware time model for web search (2016) Proceedings of 39Th International ACM SIGIR Conference on Research and Development in Information Retrieval, 17–21 July 2016, Pisa, Italy, pp. 205-214; Field, H., Allan, J., Task-aware query recommendation (2013) Proceedings of 36Th International ACM SIGIR Conference on Research and Development in Information Retrieval, 28 July–1 August 2013, Dublin, Ireland, pp. 83-92; Zhang, A., Goyal, A., Kong, W., et al.: AdaQAC: Adaptive query auto-completion via implicit negative feedback (2015) Proceedings of 38Th International ACM SIGIR Conference on Research and Development in Information Retrieval, 9–13 August 2015, Santiago, Chile, pp. 143-152; Yuan, Q., Cong, G., Ma, Z., Time-aware point-of-interest recommendation (2013) Proceedings of 36Th International ACM SIGIR Conference on Research and Development in Information Retrieval, 28 July–1 August 2013, Dublin, Ireland, pp. 363-372; Otsuka, A., Seki, Y., Kando, N., QAque: Faceted query expansion techniques for exploratory search using community QA resources (2012) Proceedings of 21St International Conference on World Wide Web, April 2012, Lyon, France, pp. 799-806; Cheng, C., Yang, H., King, I., A unified point-of-interest recommendation framework in location-based social networks (2016) ACM Trans. Intell. Syst. Technol. (TIST), 8 (1), p. 10; Fang, Q., Xu, C., Hossain, M.S., STCAPLRS: A spatial-temporal context-aware personalized location recommendation system. ACM Trans (2016) Intell. Syst. Technol. (TIST) -Special Issue on Crowd in Intelligent Systems, Research Note/Short Paper and Regular Papers, 7 (4), p. 59; Zhang, J., Chou, C., GeoSoCa: Exploiting geographical, social and categorical correlations for point-of-interest recommendations (2015) Proceedings of 38Th International ACM SIGIR Conference on Research and Development in Information Retrieval, 09–13 August 2015, Santiago, Chile, pp. 443-452; Zhang, W., Wang, J., Location and time aware social collaborative retrieval for new successive point-of-interest recommendation (2015) Proceedings of 24Th ACM International on Conference on Information and Knowledge Management, 18–23 October 2015, Melbourne, Australia, pp. 1221-1230; Zhou, X., Zhang, P., Wang, J., Examining task relationships in multitasking consumer search sessions: A query log analysis In: Proceedings of 79Th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives through Information & Technology, Copenhagen, Denmark, 14–18 October 2016. Article No. 102; Freund, L.S., (2008) Exploiting Task-Document Relations in Support of Information Retrieval in the Workplace. Doctoral Dissertation, University of Toronto; Teevan, J., Dumais, S.T., Horvitz, E., Potential for personalization (2010) ACM Trans. Comput.-Hum. Interact. (TOCHI), 17 (1), p. 4; Belkin, N.J., Helping people find what they don’t know (2000) Commun. ACM, 43 (8), pp. 58-61
出版地:
HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
出版者:
Song X.Xie W.Lu Z.Zou B.Li M.Wang H.
ISBN:
198799
基金类别:
Acknowledgements. This work is supported by the National Natural Science Foundation of China (No. 61402220), Scientific Research Project of Education Bureau of Hunan Province, China (Grant No. 15C1186), the Construct Program for the Key Discipline in University of South China (No. NHxk02), the Construct Program for Innovative Research Team in University of South China.
机构署名:
本校为第一且通讯机构
院系归属:
计算机科学与技术学院
摘要:
Query recommendation is an effective method to help users describe their search intentions. In a personalized system, cold-start and the data sparsity were unavoidable, which directly lead to deficient performance of personalizing. As a significant part of a user’s personal information space, a personal computer owns lots of documents relevant to his or her interest. Therefore, desktop data was introduced to construct a user’s preference model. Furthermore, considering the variety of desktop data, relationship between search task and work task was simultaneously exploited to predic...

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