32 resultados para Course de demi-fond -- Belgique -- Anvers (Belgique)
em University of Southampton, United Kingdom
Resumo:
In this lecture, we will focus on analyzing user goals in search query logs. Readings: M. Strohmaier, P. Prettenhofer, M. Lux, Different Degrees of Explicitness in Intentional Artifacts - Studying User Goals in a Large Search Query Log, CSKGOI'08 International Workshop on Commonsense Knowledge and Goal Oriented Interfaces, in conjunction with IUI'08, Canary Islands, Spain, 2008.
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Search engines - such as Google - have been characterized as "Databases of intentions". This class will focus on different aspects of intentionality on the web, including goal mining, goal modeling and goal-oriented search. Readings: M. Strohmaier, M. Lux, M. Granitzer, P. Scheir, S. Liaskos, E. Yu, How Do Users Express Goals on the Web? - An Exploration of Intentional Structures in Web Search, We Know'07 International Workshop on Collaborative Knowledge Management for Web Information Systems in conjunction with WISE'07, Nancy, France, 2007. [Web link] Readings: Automatic identification of user goals in web search, U. Lee and Z. Liu and J. Cho WWW '05: Proceedings of the 14th International World Wide Web Conference 391--400 (2005) [Web link]
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In this class, we will discuss metadata as well as current phenomena such as tagging and folksonomies. Readings: Ontologies Are Us: A Unified Model of Social Networks and Semantics, P. Mika, International Semantic Web Conference, 522-536, 2005. [Web link] Optional: Folksonomies: power to the people, E. Quintarelli, ISKO Italy-UniMIB Meeting, (2005)
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In this class, we will discuss the nature of network evolution and some selected network processes. We will discuss graph generation algorithms that generate networks with different interesting characteristics. Optional : The Structure and Function of Complex Networks (chapter 8), M.E.J. Newman, SIAM Review 45 167--256 (2003); Optional: Emergence of Scaling in Random Networks, A.L. Barabasi and R. Albert, Science 286, 509 (1999)
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In this class, we will discuss network theory fundamentals, including concepts such as diameter, distance, clustering coefficient and others. We will also discuss different types of networks, such as scale-free networks, random networks etc. Readings: Graph structure in the Web, A. Broder and R. Kumar and F. Maghoul and P. Raghavan and S. Rajagopalan and R. Stata and A. Tomkins and J. Wiener Computer Networks 33 309--320 (2000) [Web link, Alternative Link] Optional: The Structure and Function of Complex Networks, M.E.J. Newman, SIAM Review 45 167--256 (2003) [Web link] Original course at: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/
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In this class, we will discuss the course organization and provide a basic motivation for and introduction to the course. Readings: Web science: a provocative invitation to computer science, B. Shneiderman, Communications of the ACM 50 25--27 (2007) [Web link] Readings: Chapter 1 & 2, A Framework for Web Science, T. Berners-Lee and W. Hall and J. A. Hendler and K. O'Hara and N. Shadbolt and D. J. Weitzner Foundations and Trends® in Web Science 1 (2006) [Web link] Originally from: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/
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The semantic web represents a current research effort to increase the capability of machines to make sense of content on the web. In this class, Peter Scheir will give a guest lecture on the basic principles underlying the semantic web vision, including RDF, OWL and other standards.
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How can we analyze and understand affiliation networks? In this class, we will discuss properties of affiliation networks and we will investigate the use of Galois lattices for the exploration of structural patterns in bi-partite graphs. Optional : L.C. Freeman and D.R. White. Using Galois Lattices to Represent Network Data. Sociological Methodology, (23):127--146, (1993)
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What are fundamental entities in social networks and what information is contained in social graphs? We will discuss some selected concepts in social network analysis, such as one- and two mode networks, prestige and centrality, and cliques, clans and clubs. Readings: Web tool predicts election results and stock prices, J. Palmer, New Scientist, 07 February (2008) [Protected Access] Optional: Social Network Analysis, Methods and Applications, S. Wasserman and K. Faust (1994)
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We will discuss several examples and research efforts related to the small world problem and set the ground for our discussion of network theory and social network analysis. Readings: An Experimental Study of the Small World Problem, J. Travers and S. Milgram Sociometry 32 425-443 (1969) [Protected Access] Optional: The Strength of Weak Ties, M.S. Granovetter The American Journal of Sociology 78 1360--1380 (1973) [Protected Access] Optional: Worldwide Buzz: Planetary-Scale Views on an Instant-Messaging Network, J. Leskovec and E. Horvitz MSR-TR-2006-186. Microsoft Research, June 2007. [Web Link, the most recent and comprehensive study on the subject!] Originally from: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/
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What are ways of searching in graphs? In this class, we will discuss basics of link analysis, including Google's PageRank algorithm as an example. Readings: The PageRank Citation Ranking: Bringing Order to the Web, L. Page and S. Brin and R. Motwani and T. Winograd (1998) Stanford Tecnical Report
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This class focuses on a selected subset of web technologies that are of interest to the topics of this course. Readings: Chapter 5 "Representational State Transfer (REST)", in "Architectural Styles and the Design of Network-based Software Architecture", Roy Fielding, Dissertation, University of California Irvine, 2000 Optional: Chapter "Representational State Transfer (REST)" in "Pro PHP XML and Web Services", R. Richards 633--672, 2006
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This class introduces basics of web mining and information retrieval including, for example, an introduction to the Vector Space Model and Text Mining. Guest Lecturer: Dr. Michael Granitzer Optional: Modeling the Internet and the Web: Probabilistic Methods and Algorithms, Pierre Baldi, Paolo Frasconi, Padhraic Smyth, Wiley, 2003 (Chapter 4, Text Analysis)
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Six Degrees: The New Science of Networks (Sociology, W3233, Spring 2006) Original URL: http://cdg.columbia.edu/cdg/courses/spring06/sixDegrees/syllabus.jsp
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The Networks and Complexity in Social Systems course commences with an overview of the nascent field of complex networks, dividing it into three related but distinct strands: Statistical description of large scale networks, viewed as static objects; the dynamic evolution of networks, where now the structure of the network is understood in terms of a growth process; and dynamical processes that take place on fixed networks; that is, "networked dynamical systems". (A fourth area of potential research ties all the previous three strands together under the rubric of co-evolution of networks and dynamics, but very little research has been done in this vein and so it is omitted.) The remainder of the course treats each of the three strands in greater detail, introducing technical knowledge as required, summarizing the research papers that have introduced the principal ideas, and pointing out directions for future development. With regard to networked dynamical systems, the course treats in detail the more specific topic of information propagation in networks, in part because this topic is of great relevance to social science, and in part because it has received the most attention in the literature to date.
