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.

A word at a time: computing word relatedness using temporal semantic analysis

Abstract: Computing the degree of semantic relatedness of words is a key functionality of many language applications such as search, clustering, and disambiguation. Previous approaches to computing semantic relatedness mostly used static language resources, while essentially ignoring their temporal aspects. We believe that a considerable amount of relatedness information can also be found in studying patterns of word usage over time. Consider, for instance, a newspaper archive spanning many years. Two words such as "war" and "peace" might rarely co-occur in the same articles, yet their patterns of use over time might be similar. In this paper, we propose a new semantic relatedness model, Temporal Semantic Analysis (TSA), which captures this temporal information. The previous state of the art method, Explicit Semantic Analysis (ESA), represented word semantics as a vector of concepts. TSA uses a more refined representation, where each concept is no longer scalar, but is instead represented as time series over a corpus of temporally-ordered documents. To the best of our knowledge, this is the first attempt to incorporate temporal evidence into models of semantic relatedness. Empirical evaluation shows that TSA provides consistent improvements over the state of the art ESA results on multiple benchmarks.

Is There a Relationship between Physical Fitness and Academic Achievement? Positive Results from Public School Children in the Northeastern United States.

Abstract: OBJECTIVES: To determine relationships between physical fitness and academic achievement in diverse, urban public school children. METHODS: This cross-sectional study used public school data from 2004 to 2005. Academic achievement was assessed as a passing score on Massachusetts Comprehensive Assessment System (MCAS) achievement tests in Mathematics (fourth, sixth, and eighth grade, n = 1103) and in English (fourth and seventh grade, n = 744). Fitness achievement was assessed as the number of physical fitness tests passed during physical education (PE). Multivariate logistic regression analyses were conducted to assess the probability of passing the MCAS tests, controlling for students’ weight status (BMI z score), ethnicity, gender, grade, and socioeconomic status (school lunch enrollment). RESULTS: The odds of passing both the MCAS Mathematics test and the MCAS English test increased as the number of fitness tests passed increased (p < .0001 and p < .05, respectively). CONCLUSIONS: Results show statistically significant relationships between fitness and academic achievement, though the direction of causation is not known. While more research is required, promoting fitness by increasing opportunities for physical activity during PE, recess, and out of school time may support academic achievement.

A Survey on PageRank Computing

Abstract: This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much more complex challenge. Recently, significant effort has been invested in building sets of personalized PageRank vectors. PageRank is also used in many diverse applications other than ranking. We are interested in the theoretical foundations of the PageRank formulation, in the acceleration of PageRank computing, in the effects of particular aspects of web graph structure on the optimal organization of computations, and in PageRank stability. We also review alternative models that lead to authority indices similar to PageRan...

Search-based Structured Prediction

Abstract: We present Searn, an algorithm for integrating search and learning to solve complex structured prediction problems such as those that occur in natural language, speech, computational biology, and vision. Searn is a meta-algorithm that transforms these complex problems into simple classification problems to which any binary classifier may be applied. Unlike current algorithms for structured learning that require decomposition of both the loss function and the feature functions over the predicted structure, Searn is able to learn prediction functions for any loss function and any class of features. Moreover, Searn comes with a strong, natural theoretical guarantee: good performance on the derived classification problems implies good performance on the structured prediction problem.

Comparison of antioxidant and antimicrobial activities of tilia (Tilia argentea Desf ex DC), sage (Salvia triloba l.), and black tea (Camellia sinensis) extracts.

Abstract: The antioxidant activity of the water extract of Tilia argentea Desf ex DC was determined by the thiocyanate method. The antioxidant activity of the water extract increased with the increasing amount of lyophilized extract (50-400 microg) added into the linoleic acid emulsion. Statistically significant effect was determined in 100 microg and higher amounts. Antioxidant activities of water extracts of tilia (Tilia argentea Desf ex DC), sage (Salvia triloba L.), and two Turkish black teas commercially called Rize tea and young shoot tea (Camellia sinensis) were compared. For comparison studies, 100 microg portions of extracts were added into test samples. All samples were able to show statistically significant antioxidant effect. Both of the tea extracts showed highest antioxidant activities, nevertheless, differences between tilia and sage and tilia and tea were not statistically significant (for both cases p > 0.05). Like antioxidant activity, the reducing power of water extract of Tilia argentea Desf ex DC was also concentration dependent. Even in the presence of 50 microg of extract, the reducing power was significantly higher than that of the control (p 0.05). From these results, we could suggest that although the reducing power of a substance may be an indicator of its potential antioxidant activity, there may not always be a linear correlation between these two activities. In addition, antimicrobial activities of each of the above extracts were studied by disk diffusion methods on different test microorganisms. None of the extracts showed antibacterial activity on the studied microorganisms.