PPT-Information Retrieval and Question-Answering

Julia Hirschberg CS 4705 Today Information Retrieval Review of Methods TREC IR Tracks Question Answering Factoid QA A Sample System UT Dallas Harabagiu A simpler alternative from MSR Information Retrieval. iaaccn Abstract Community question answering cQA which pro vides a platform for people with diverse back ground to share information and knowledge has become an increasingly popular research topic In this paper we focus on the task of question re tri Hui Fang , Tao . Tao. , . ChengXiang. . Zhai. University of Illinois at Urbana Champaign. SIGIR 2004 Best Paper. Presented by Lingjie Zhang. Outline. Formal Definitions of Heuristic Retrieval Constraints. Introduction. Ling 573. NLP Systems and Applications. March 29, 2011. Roadmap. Motivation. 573 Structure. Question-Answering. Shared Tasks. Motivation. Information retrieval is very powerful. Search engines index and search enormous doc sets. By . Rong. Yan, Alexander G. and . Rong. Jin. Mwangi. S. . Kariuki. 2008-11629. Quiz. What’s Negative Pseudo-Relevance feedback in multimedia retrieval?. Introduction. As a result of high demand of content based access to video information.. INST 734. Doug . Oard. Module 13. Agenda. Image retrieval. Video retrieval. Multimedia retrieval. Multimedia. A set of time-synchronized modalities. Video. Images, object motion, camera motion, scenes. By: Paniz Adiban. Introduction. Introduction. In a digital answering machine, principles are used to convert a caller's message into a stream of bytes. A microcontroller digitizes the caller's voice using an analog-to-digital converter and stores it in RAM (random-access memory). . Information. Miles Efron, Jana . Diesner. , Peter . Organisciak. , Garrick Sherman, Ana . Lucic. {. mefron. , et al.}@. illinois.edu. GSLIS 2012. TREC: The Text REtrieval Conference. NIST. Web. Legal. Introduction. Ling 573. NLP Systems and Applications. April 1, 2013. Roadmap. Motivation. 573 Structure. Question-Answering. Shared Tasks. Motivation. Information retrieval is very powerful. Search engines index and search enormous doc sets. Lin Ma, . Zhengdong. Lu, and Hang Li. Huawei Noah’s Ark Lab, Hong Kong. http://. www.ee.cuhk.edu.hk. /~lma. /. . Mine the relationships between multiple modalities. Association different modalities. SWBAT . make . inferences about the character by answering a question.. Get the Close Reader turn to page 3 and preview the text.. Make a prediction. What is the story, “Golden Glass” going to be about?. Kai-Wei Chang. CS @ University of Virginia. kw@kwchang.net. Couse webpage: . http://kwchang.net/teaching/NLP16. 1. CS6501-NLP. Question answering. CS6501– Natural Language Processing. 2. credit: ifunny.com. What is IR?. Sit down before fact as a little child, . be prepared to give up every conceived notion, . follow humbly wherever and whatever abysses nature leads, . or you will learn nothing. . . -- Thomas Huxley --. Fatemeh. Azimzadeh. Books. (Manning et al., 2008). Christopher D. Manning, . Prabhakar. . Raghavan. , and . Hinrich. . Schütze. . Introduction to Information Retrieval. Cambridge University Press, 2008. . (including a sketch of Information Retrieval. ). Slides adapted from Dan . Jurafsky. , . Jim . Martin and Ed . Hovy. Web-based Question . Answering. Information Retrieval (briefly. ). Today. The notion of getting computers to give reasonable answers to questions has been around for quite awhile.