PPT-Exploring Web Scale Language Models for Search Query Proces

Jianfeng Gao MSR Joint work with Jian Huang Jiangbo Miao Xiaolong Li Kuansan Wang and Fritz Behr Outline Ngram language model LM ABC Ngram LM at Microsoft BingItOn Ngram Building Web scale Ngram LM. INST 734. Module 11. Doug . Oard. Agenda. CLIR. Dictionary-Based CLIR. Corpus-Based CLIR. Interactive CLIR. Cross-Language “Retrieval”. Search. Translated Query. Ranked List. Query. Translation. Query. Jaime . Teevan. , Microsoft . Reseach. dub 2013. David Foster Wallace. Mark Twain. Cowards die many times . before their deaths. . Annotated by Nelson Mandela. I . have discovered a truly marvelous proof . Vagelis Hristidis. School of Computing and Information Sciences. Florida International University. Roadmap. Why is it challenging to search EMRs?. XOntoRank. : Leveraging Ontologies to improve sensitivity in EMR search. Ann . Arbor/Detroit . NLPers. (A2D-NLP. ) Meetup. Alex Dorman, CTO. alex. at . magnetic. dot com. . Michal . Laclav. í. k, Sr. Data Scientist. m. ichal.laclavik. at . magnetic. dot com. Who We . Kristina . Lerman. What can we learn from web search queries?. Characteristics. Length has steadily grown over the years. 1990’s: < 2 terms. 2001: 2.4 terms. 2014: long search queries, e.g., “where is the nearest coffee shop”. THOMAS FUNKHOUSER, PATRICK MIN, MICHAEL KAZHDAN, JOYCE CHEN,. ALEX HALDERMAN, and DAVID DOBKIN. Princeton University. and. DAVID JACOBS. NEC Research Institute. ACM Transactions on Graphics, Vol. 22, No. 1, January 2003, Pages 83–105.. Jaime . Teevan. , Microsoft . Reseach. JITP 2011. David Foster Wallace. Mark Twain. Cowards die many times . before their deaths. . Annotated by Nelson Mandela. I . have discovered a truly marvelous proof . Kristina . Lerman. What can we learn from web search queries?. Characteristics. Length has steadily grown over the years. 1990’s: < 2 terms. 2001: 2.4 terms. 2014: long search queries, e.g., “where is the nearest coffee shop”. All slides ©Addison Wesley, 2008. Retrieval Models. Provide a mathematical framework for defining the search process. includes explanation of assumptions. basis of many ranking algorithms. can be implicit. Community Question . Answering. Date. ： . 2014/09/25. Author . ： . Haocheng. Wu, Wei Wu, Ming Zhou, . Enhong. Chen, Lei . Duan. , . Heung-Yeung Shum. Source. ： . WSDM’14. Advisor: . Student Writers as Corpus Users. (. H. yland 2003). Example:. Pérez-Paredes et al . 2013. Focus on form activities. It. -cleft sentences . Tracking . software. Example:. Tono. . et al . 2014. Coded error feedback. Course Goal. The goal of this course is to teach end users of ctcLink PeopleSoft to find and retrieve Queries and Reports in the most effective manner.. Course Learning Objectives. At the end of this course users will:. Scott Wen-tau Yih. Joint work with. Kristina Toutanova, John Platt, Chris Meek. Microsoft Research. Cross-language Document Retrieval. English Query Doc. Spanish Document Set. Web Search & Advertising. Laboratory of Mathematical Chemistry,. Bourgas University “Prof. Assen Zlatarov”. Bulgaria. 2. What is Query Tool?. Environmental fate - examples (BCF, BOD) . Human health hazard - examples (AMES and Carcinogenicity) .