PPT-How Does Execution Information Help with Information-Retrieval Based Bug Localization?

Tung Dao Lingming Zhang Na Meng Virginia Tech The University of Texas at Dallas Background Bug localization is important in software maintenance Bug localization is challenging and timeconsuming. 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. Module 3. Doug . Oard. Agenda. Ranked retrieval. Similarity-based ranking. Probability-based ranking. Boolean Retrieval. Strong points. Accurate, . if you know the right strategies. Efficient for the computer. CSC . 575. Intelligent Information Retrieval. 2. Source: . Intel. How much information?. Google: . ~100 . PB a . day; 3+ million servers (15 . Exabytes. stored). Wayback Machine has . ~9 . PB + . 100 . ChengXiang. (“Cheng”) . . Zhai. Department of Computer Science. University of Illinois at Urbana-Champaign. http://www.cs.uiuc.edu/homes/czhai. . Email: czhai@illinois.edu. Keynote. at SIGIR 2015. 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. Under the Hood of Localization Services with Applications in Healthcare. Outline. Location-based . services (LBS). Localization techniques. Localization systems. Issues. Why do Companies and Governments Want Your Location Information?. ChengXiang. (“Cheng”) . . Zhai. Department of Computer Science. University of Illinois at Urbana-Champaign. http://www.cs.uiuc.edu/homes/czhai. . Email: czhai@illinois.edu. 1. Yahoo!-DAIS Seminar, UIUC. All slides ©Addison Wesley, 2008. Information Needs. An . information need. is the underlying cause of the query . that a . person submits to a search . engine. sometimes called . information problem . Hongning. Wang. CS@UVa. What is information retrieval?. CS6501: Information Retrieval. CS@UVa. 2. Why information retrieval . Information overload. “. It refers to the . difficulty. a person can have understanding an issue and making decisions that can be caused by the presence of . CSC 575. Intelligent Information Retrieval. Intelligent Information Retrieval. 2. Web Mining. Today. Overview of Web Data Mining. Web Content Mining / Text Mining. Web Usage Mining. Web Personalization. All slides ©Addison Wesley, 2008. How Much Data is Created Every . Minute?. Source: . https. ://www.domo.com/blog/2012/06/how-much-data-is-created-every-minute/. The Search Problem. Search and Information Retrieval. 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. . Session 10 – Information Retrieval and Dissemination. Lecturer: Dr. . Perpetua. S. . Dadzie. , Dept. of Information Studies. Contact Information: psdadzie@ug.edu.gh. Session Overview . At the end of the session, the student will be able to.