Categories are pages that are used to group other pages on similar subjects together. This is done to help users find the pages they are looking for, even if they do not know whether it exists or what it is called.
Every page should belong to at least one category. A page may often be in several categories. However, putting a page in too many categories may not be useful.
Wikipedia is a terrific knowledge resource, and many recent studies in artificial intelligence, information retrieval and related fields used Wikipedia to endow computers with (some) human knowledge. Wikipedia dumps are publicly available in XML format, but they have a few shortcomings. First, they contain a lot of information that is often not used when Wikipedia texts are used as knowledge (e.g., ids of users who changed each article, timestamps of article modifications). On the other hand, the XML dumps do not contain a lot of useful information that could be inferred from the dump, such as link tables, category hierarchy, resolution of redirection links etc.
Due to an explosion of data, there has been an increasing demand for scalable machine learning and data mining algorithms in many applications, such as social network analysis, information retrieval, recommendation system, biology applications, multimedia, and e-commerce. The objective of this special issue is to connect academia and industry on the methods and experiences of large scale data analysis. We look for scalable machine learning, data mining algorithms, implementations, frameworks and case studies that target at real and practical scenarios for large datasets. The focus is to identify the real challenges in large-scale data mining and to investigate the scalable methods and practical solutions of the core machine learning and data mining problems with respect to both theoretical and experimental perspectives.
The M-tree is an index structure that can be used for the efficient resolution of similarity queries on complex objects to be compared using an arbitrary metric
BitC is a new systems programming language. It seeks to combine the flexibility, safety, and richness of Standard ML or Haskell with the low-level expressiveness of C.
In mathematics and physics, a small-world network is a type of mathematical graph in which most nodes are not neighbors of one another, but most nodes can be reached from every other by a small number of hops or steps. A small world network, where nodes represent people and edges connect people that know each other, captures the small world phenomenon of strangers being linked by a mutual acquaintance.
Project Euler is a series of challenging mathematical/computer programming problems that will require more than just mathematical insights to solve. Although mathematics will help you arrive at elegant and efficient methods, the use of a computer and programming skills will be required to solve most problems.
Producing Open Source Software is a book about the human side of open source development. It describes how successful projects operate, the expectations of users and developers, and the culture of free software. The book is released under an open copyright: it is available in bookstores and from the publisher (O'Reilly Media), or you can browse or download it here.
Welcome to OSDev.org, the largest online community of operating system developers. If you want to learn how to write your own OS we have all the information to get you started. Read our OS development wiki to learn where to start. The forums are a great place to discuss OS theory and ask for help when you get stuck. Don't forget to add a link on the OS List to your OS project once it gets going.
M. Koolen, G. Kazai, and N. Craswell. WSDM '09: Proceedings of the Second ACM International Conference on Web Search and Data Mining, page 44--53. New York, NY, USA, ACM, (2009)
A. Turpin, and F. Scholer. Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, page 11--18. New York, NY, USA, ACM, (2006)
C. Daskalakis, P. Goldberg, and C. Papadimitriou. STOC '06: Proceedings of the thirty-eighth annual ACM symposium on Theory of computing, page 71--78. New York, NY, USA, ACM, (2006)