PPT-Log Based Query Recommendation

Author : pamella-moone | Published Date : 2016-03-03

Speaker RuiRui Li Supervisor Prof Ben Kao 1 Outline Introduction Motivation Methods using clickthrough data using session data context aware query suggestion other

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Log Based Query Recommendation: Transcript

Speaker RuiRui Li Supervisor Prof Ben Kao 1 Outline Introduction Motivation Methods using clickthrough data using session data context aware query suggestion other methods Conclusion. . . Bahaeddin. ERAVCI,. . Emre. YILMAZ,. I. zze. d. d. in G. U. R. . Mehmet G. U. VERCIN. Description. Recommendation systems . are used to find relevant . data based on current data. (amazon,last.fm). Query Auto-Completion. WWW 2011 Hyderabad India. Naama. Kraus. Computer Science, . Technion. , Israel. Ziv. Bar-. Yossef. Google Israel &. Electrical Engineering, . Technion. , Israel. Motivating Example. Yuichi Iijima and . Yoshiharu Ishikawa. Nagoya University, Japan. Outline. Background and Problem Formulation. Related Work. Query Processing Strategies. Experimental Results. Conclusions. 1. 2. Imprecise. Basic I/O Relationship. Knowledge-based: "Tell me what fits based on my needs". Why do we need knowledge-based recommendation?. Products with low number of available ratings. Time span plays an important role. Content-based recommendation. While CF – methods do not require any information about the items,. it might be reasonable to exploit such information; and. recommend fantasy novels to people who liked fantasy novels in the past. Content-based recommendation. While CF – methods do not require any information about the items,. it might be reasonable to exploit such information; and. recommend fantasy novels to people who liked fantasy novels in the past. Danielle Lee . April 20, 2011. Three basic recommendations . Collaborative Filtering. : exploiting other likely-minded community data to derive recommendations. Effective, Novel and Serendipitous recommendations . ManetS. Adeela Huma. 02/02/2017. Introduction - MANETs. MANETs- Mobile ad hoc networks . lacks infrastructure and . central . authority to . establish and . facilitate communication . in the . network. (SIGIR2010). IBM Research Lab. Ido. . Guy,Naama. . Zwerdling. Inbal. . Ronen,David. . Carmel,Erel. . Uziel. Social Networks and Discovery(. SaND. ). Direct entity-entity relations. Recommendation Algorithm. Kinan Halloum . 1. Presented paper. 2. Deep content-based music recommendation . by van den Oord et al. NIPS 2013. Outline. Music Recommendation. Collaborative filtering. Weighted Matrix Factorization. Basic I/O Relationship. Knowledge-based: "Tell me what fits based on my needs". Why do we need knowledge-based recommendation?. Products with low number of available ratings. Time span plays an important role. S. OCIAL. N. ETWORKS. Modified from . R. . . Zafarani. , M. A. . Abbasi. , and H. Liu, . Social Networks . Mining: An Introduction. , Cambridge University Press, 2014. . Difficulties of Decision Making. S. OCIAL. N. ETWORKS. Modified from . R. . . Zafarani. , M. A. . Abbasi. , and H. Liu, . Social Networks . Mining: An Introduction. , Cambridge University Press, 2014. . Difficulties of Decision Making. Clinical Practice Guidelines: The Diagnosis, Management, and Prevention of Bronchiolitis. Margaret Thew. Guideline . application. The bronchiolitis guideline is intended for children from 1-23 months.

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