Tractatus de regia protectione vi oppresorum appellantium a causis & judicibus ecclesiasticis : utrique Reipublicae, tam, ecclesiasticae, quam temporali, valde utilis .

UANL

Dissertationum iuris controversi, tam in hispalensi, quam granatensi senatu

UANL

Catechismi romani expositio variis praelectionibus secuadum novam methodum tam in dioecesi Toletana, quam in aliss Hispaniarum, et Indiarumpraescriptam.

UANL

Aurifodina universalis scientiarum divinarum atque humanarum exfontibus aureis sanctorum patrum concilorum, doctorum, nec non paganorum fere ducentorum tam in theologia, quam in philosophia persententias plusquam ...

UANL

Analyse des rendements et des volatilités des indices S&P 500 et TSE 300.

Rapport de recherche

Projecte d’una nau d’emmagatzematge i comercialització de productes hortofructícoles d’una capacitat de 300.000 kg/any, situada al terme municipal de Gualta, al Baix Empordà (Girona)

L’objectiu del projecte és la construcció d’una nau industrial al terme municipal de Gualta, Baix Empordà (Girona), amb la finalitat de conservar i comercialitzar fruita dolça ( poma i pera). La nau disposarà de tres cambres d’atmosfera controlada, la capacitat de les quals serà de tres-centes tones de fruita l’any. L’edifici, de 1.000 m2, s’utilitzarà per emmagatzemar, manipular i comercialitzar la fruita però també hi haurà una part important de l’edifici destinat a ser utilitzat com a magatzem de les eines del camp i de diferents productes fitosanitaris i adobs

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 12: User Intentions and Intentional Structures on the Web II

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.

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 11: User Intentions and Intentional Structures on the Web

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]

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 9: Metadata, Tagging and Folksonomies

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)

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 6: Network Evolution and Process

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)

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 3: Network Theory and Terminology

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/

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 1

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/

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 13: Web Technologies 2 - The Semantic Web

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.

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 5: Affiliation Networks

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)

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 4: Social Network Analysis

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)