Yahoo!

About: Yahoo! is a company organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Web search query. The organization has 26749 authors who have published 29915 publications receiving 732583 citations. The organization is also known as: Yahoo! Inc. & Maudwen-Yahoo! Inc.

Declarative information extraction using datalog with embedded extraction predicates

Abstract: In this paper we argue that developing information extraction (IE) programs using Datalog with embedded procedural extraction predicates is a good way to proceed. First, compared to current ad-hoc composition using, e.g., Perl or C++, Datalog provides a cleaner and more powerful way to compose small extraction modules into larger programs. Thus, writing IE programs this way retains and enhances the important advantages of current approaches: programs are easy to understand, debug, and modify. Second, once we write IE programs in this framework, we can apply query optimization techniques to them. This gives programs that, when run over a variety of data sets, are more efficient than any monolithic program because they are optimized based on the statistics of the data on which they are invoked. We show how optimizing such programs raises challenges specific to text data that cannot be accommodated in the current relational optimization framework, then provide initial solutions. Extensive experiments over real-world data demonstrate that optimization is indeed vital for IE programs and that we can effectively optimize IE programs written in this proposed framework.

Inhibitory Activities of Cyanidin and Its Glycosides and Synergistic Effect with Acarbose against Intestinal α-Glucosidase and Pancreatic α-Amylase

Abstract: Cyanidin and its glycosides are naturally dietary pigments which have been indicated as promising candidates to have potential benefits to humans, especially in the prevention and treatment of diabetes mellitus. We investigated the structure activity relationships of cyanidin and its glycosides to inhibit intestinal α-glucosidases and pancreatic α-amylase in vitro. The results found that cyanidin and its glycosides are more specific inhibitors of intestinal sucrase than intestinal maltase. Cyanidin-3-galactoside and cyanidin-3-glucoside were the most potent inhibitors against intestinal sucrase and pancreatic α-amylase with IC(50) values of 0.50 ± 0.05 and 0.30 ± 0.01 mM, respectively. Our findings indicate that the structural difference between glucose and galactose at the 3-O-position of cyanidin was an important factor for modulating the inhibition of intestinal sucrase and pancreatic α-amylase. The combination of cyandin-3-glucoside, cyanidin-3- galactoside or cyanidin-3,5-diglucosides with a low concentration of acarbose showed synergistic inhibition on intestinal maltase and sucrase. The synergistic inhibition was also found for a combination of cyanidin or cyanidin-3-glucoside with a low concentration of acarbose. The findings could provide a new insight into a use for the naturally occurring intestinal α-glucosidase and pancreatic α-amylase inhibitors for the prevention and treatment of diabetes and its complications.

Social networking for mobile devices

Abstract: A mobile device, system, and method are directed towards enabling an integrated display of live views. The integrated live views are generated by employing social networking information, including moods of a person, avatars, status of a member's activities including whether they are in an IM session, or the like. Integrated live views may include a live contact list, a group view, a friend view, an activity oriented view, a list of content, or the like, based on the mobile user's social networking information. By providing the mobile user with integrated live views of their social network, the mobile user may be able communicate with other members within the mobile social networking context, to obtain, and respond to invites from a social network member, provide opportunities for activities to other members, to grow their social network, and to consume content that is displayed relative to their social network.

Analyzing patterns of user content generation in online social networks

Abstract: Various online social networks (OSNs) have been developed rapidly on the Internet. Researchers have analyzed different properties of such OSNs, mainly focusing on the formation and evolution of the networks as well as the information propagation over the networks. In knowledge-sharing OSNs, such as blogs and question answering systems, issues on how users participate in the network and how users "generate/contribute" knowledge are vital to the sustained and healthy growth of the networks. However, related discussions have not been reported in the research literature.In this work, we empirically study workloads from three popular knowledge-sharing OSNs, including a blog system, a social bookmark sharing network, and a question answering social network to examine these properties. Our analysis consistently shows that (1) users' posting behavior in these networks exhibits strong daily and weekly patterns, but the user active time in these OSNs does not follow exponential distributions; (2) the user posting behavior in these OSNs follows stretched exponential distributions instead of power-law distributions, indicating the influence of a small number of core users cannot dominate the network; (3) the distributions of user contributions on high-quality and effort-consuming contents in these OSNs have smaller stretch factors for the stretched exponential distribution. Our study provides insights into user activity patterns and lays out an analytical foundation for further understanding various properties of these OSNs.

A Survey of Signed Network Mining in Social Media

Abstract: Many real-world relations can be represented by signed networks with positive and negative links, as a result of which signed network analysis has attracted increasing attention from multiple disciplines. With the increasing prevalence of social media networks, signed network analysis has evolved from developing and measuring theories to mining tasks. In this article, we present a review of mining signed networks in the context of social media and discuss some promising research directions and new frontiers. We begin by giving basic concepts and unique properties and principles of signed networks. Then we classify and review tasks of signed network mining with representative algorithms. We also delineate some tasks that have not been extensively studied with formal definitions and also propose research directions to expand the field of signed network mining.