According to a recent survey made by Nielsen NetRatings, searching on news articles is one of the most important activity online. Indeed, Google, Yahoo, MSN and many others have proposed commercial search engines for indexing news feeds. Despite this commercial interest, no academic research has focused on ranking a stream of news articles and a set of news sources. In this paper, we introduce this problem by proposing a ranking framework which models: (1) the process of generation of a stream of news articles, (2) the news articles clustering by topics, and (3) the evolution of news story over the time. The ranking algorithm proposed ranks news information, finding the most authoritative news sources and identifying the most interesting events in the di#erent categories to which news article belongs. All these ranking measures take in account the time and can be obtained without a predefined sliding window of observation over the stream. The complexity of our algorithm is linear in the number of pieces of news still under consideration at the time of a new posting. This allow a continuous on-line process of ranking. Our ranking framework is validated on a collection of more than 300,000 pieces of news, produced in two months by more then 2000 news sources belonging to 13 di#erent categories (World, U.S, Europe, Sports, Business, etc). This collection is extracted from the index of comeToMyHead, an academic news search engine available online. Categories and Subject Descriptors H.3.1 [Information Storage And Retrieval]: Content Analysis and IndexingRetrieval models; Search process; H.3.3 [Information Storage And Retrieval]: Information Search and Retrieval; H.3.5 [Information Storage And Retrieval]: OnlineInformation Services General Terms Algorithms, Experimentat...

This article presents a device which is suitable for a practical and efficient implementation of Double Adaptive Quadrature.The device includes local error estimates and attempts to detect the presence of numerical difficulties in the integrand function.If a family of rules with suitable properties is chosen, then this can be achieved without affecting the overall computational cost.Extensive numerical testing has been performed on a comprehensive set of functions showing the effectiveness of the device and its efficiency.

A set of symmetric, closed, interpolatory integration formulas on the interval [-1, 1] with positive weights and increasing degree of precision is introduced. These formulas, called recursive monotone stable (RMS) formulas, allow applying higher order or compound rules without wasting previously computed functional values. An exhaustive search shows the existence of 27 families of RMS formulas, stemming from the simple trapezoidal rule.

Two automatic adaptive integrators from QUADPACK (namely, QAG, and QAGS) are modified by substituting the Gauss-Kronrod rules used for local quadrature with recursive monotone stable (RMS) formulas. Extensive numerical tests, both for one-dimensional and two-dimensional integrals, show that the resulting programs are faster, perform less functional evaluations, and are more suitable

Let t be a disjoint sum of tensors associated to matrix multiplication. The rank of the tensorial powers of t is bounded by an expression involving the elements of t and an exponent for matrix multiplication. This relation leads to a trascendental equation defining a new exponent for matrix multiplication.

A set of bilinear forms can be evaluated with a multiplicative complexity lower than the rank of the associated tensor by allowing an arbitrarily small error. A topological interpretation of this fact is presented together with the error analysis. A complexity measure is introduced which takes into account the numerical stability of algorithms. Relations are established between the complexities of exact and approximate algorithms.

Bounded integer matrices are matrices whose entries are bounded integers.