IBM

About: IBM is a company organization based out in Armonk, New York, United States. It is known for research contribution in the topics: Layer (electronics) & Cache. The organization has 134567 authors who have published 253905 publications receiving 7458795 citations. The organization is also known as: International Business Machines Corporation & Big Blue.

Information retrieval on the web

Abstract: In this paper we review studies of the growth of the Internet and technologies that are useful for information search and retrieval on the Web. We present data on the Internet from several different sources, e.g., current as well as projected number of users, hosts, and Web sites. Although numerical figures vary, overall trends cited by the sources are consistent and point to exponential growth in the past and in the coming decade. Hence it is not surprising that about 85% of Internet users surveyed claim using search engines and search services to find specific information. The same surveys show, however, that users are not satisfied with the performance of the current generation of search engines; the slow retrieval speed, communication delays, and poor quality of retrieved results (e.g., noise and broken links) are commonly cited problems. We discuss the development of new techniques targeted to resolve some of the problems associated with Web-based information retrieval and speculate on future trends.

GraphScope: parameter-free mining of large time-evolving graphs

Abstract: How can we find communities in dynamic networks of socialinteractions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity time-points in such streams of graphs, in an on-line, any-time fashion? We propose GraphScope, that addresses both problems, using information theoretic principles. Contrary to the majority of earlier methods, it needs no user-defined parameters. Moreover, it is designed to operate on large graphs, in a streaming fashion. We demonstrate the efficiency and effectiveness of our GraphScope on real datasets from several diverse domains. In all cases it produces meaningful time-evolving patterns that agree with human intuition.

Experimental evidence for vortex-glass superconductivity in Y-Ba-Cu-O.

Abstract: We demonstrate experimentally the existence of a continuous phase transition between a normal and a true superconducting phase (with zero linear resistivity) in epitaxial films of Y-Ba-Cu-O in strong magnetic fields fields, {ital H}{much gt}{ital H}{sub {ital c}1}. The nonlinear {ital I}-{ital V} curves show scaling behavior near the transition and the relevant critical exponents are extracted. These exponents are consistent with values expected for freezing into a superconducting vortex-glass phase.

Star Formation in a Crossing Time

Abstract: Observations suggest that star formation occurs in only one or two crossing times for a range of scales spanning a factor of ~1000. These observations include (1) measurements of embedded cluster ages in comparison with the cloud core dynamical times, (2) measurements of the age difference versus separation for clusters in the Large Magellanic Clouds in comparison with the crossing time versus size correlation for molecular clouds, (3) the hierarchical structure of embedded young clusters, and (4) the high fraction of dense clouds that contain star formation. Such a short overall timescale for star formation implies that sources of turbulent energy or internal feedback are not required to explain or extend cloud lifetimes and that star and protostar interactions cannot be important for the stellar initial mass function. Stars appear in a cloud as if they freeze out of the gas, preserving the turbulent-driven gas structure in their birth locations. The Galaxy-wide star formation rate avoids the Zuckerman-Evans catastrophe, which has long been a concern for molecular clouds that evolve this quickly, because the multifractal structure of interstellar gas ensures that only a small fraction of the mass is able to form stars. Star formation on large scales operates more slowly than on small scales, but in most cases the whole process is over in only a few dynamical times.

Software development cost estimation approaches – A survey

Abstract: This paper summarizes several classes of software cost estimation models and techniques: parametric models, expertisedbased techniques, learningdoriented techniques, dynamicsdbased models, regressiondbased models, and compositedBayesian techniques for integrating expertisedbased and regressiondbased models. Experience to date indicates that neuraldnet and dynamicsdbased techniques are less mature than the other classes of techniques, but that all classes of techniques are challenged by the rapid pace of change in software technology. The primary conclusion is that no single technique is best for all situations, and that a careful comparison of the results of several approaches is most likely to produce realistic estimates.