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.

Social network search

Abstract: A device, system and method to enable communications over a network wherein a user may conduct a search directed to target contacts within a social network A knowledge base of prior social search responses may be searched for responses from the target contacts with the results being presented to the user The results of the search can be sorted along with responses received from the target contacts The selection of target contacts and presentation of results can be based on various attributes of target contacts or ranking of the prior search responses The search responses received by the user along with attributes and rankings may be stored in the knowledge base for future use The target contacts and search may be taken from contacts or the knowledge base of the contacts with greater than one degree of separation from the user

Quality of primary health care in Saudi Arabia: a comprehensive review.

Abstract: Objectives. Little is known about the quality of primary care in Saudi Arabia, despite the central role of primary care centers in Saudi health strategy. This study presents an overview of quality of primary care in Saudi Arabia, and identifies factors impeding the achievement of quality, with the aim of determining how the quality of Saudi primary care could be improved. Method. Using a systematic search strategy, data were extracted from the published literature on quality of care in Saudi primary care services, and on barriers to achieving high-quality care. Results. Of the 128 studies initially identified, 31 met the inclusion criteria for the review. Studies identified were diverse in methodology and focus. Components of quality were reviewed in terms of access and effectiveness of both clinical and interpersonal care. Good access and effective care were reported for certain services including: immunization, maternal health care, and control of epidemic diseases. Poor access and effectiveness were reported for chronic disease management programs, prescribing patterns, health education, referral patterns, and some aspects of interpersonal care including those caused by language barriers. Several factors were identified as determining whether high-quality care was delivered. These included management and organizational factors, implementation of evidence-based practice, professional development, use of referrals to secondary care, and organizational culture. Conclusion. There is substantial variation in the quality of Saudi primary care services. In order to improve quality, there is a need to improve the management and organization of primary care services. Professional development strategies are also needed to improve the knowledge and skills of staff.

Apparatus and method for controlling content access based on shared annotations for annotated users in a folksonomy scheme

Abstract: A method for sharing content with a user includes receiving from a user a first set of keywords for annotating an annotated user; receiving from the user a second set of keywords that designate whether annotated content annotated by at least one keyword included in the second set of keywords may be shared with the annotated user; storing in a data store a first association of the first set of keywords with the annotated user, and a second association of the second set of keywords with the annotated user; receiving a keyword selection for a select keyword and an identifier for the annotated user; and displaying on the client system content annotated by the select keyword if the annotated user is annotated by at least one keyword in the first set of keywords, and if the select keyword is included in the second set of keywords.

R-Storm: Resource-Aware Scheduling in Storm

Abstract: The era of big data has led to the emergence of new systems for real-time distributed stream processing, e.g., Apache Storm is one of the most popular stream processing systems in industry today. However, Storm, like many other stream processing systems lacks an intelligent scheduling mechanism. The default round-robin scheduling currently deployed in Storm disregards resource demands and availability, and can therefore be inefficient at times. We present R-Storm (Resource-Aware Storm), a system that implements resource-aware scheduling within Storm. R-Storm is designed to increase overall throughput by maximizing resource utilization while minimizing network latency. When scheduling tasks, R-Storm can satisfy both soft and hard resource constraints as well as minimizing network distance between components that communicate with each other. We evaluate R-Storm on set of micro-benchmark Storm applications as well as Storm applications used in production at Yahoo! Inc. From our experimental results we conclude that R-Storm achieves 30-47% higher throughput and 69-350% better CPU utilization than default Storm for the micro-benchmarks. For the Yahoo! Storm applications, R-Storm outperforms default Storm by around 50% based on overall throughput. We also demonstrate that R-Storm performs much better when scheduling multiple Storm applications than default Storm.

System and method for generating a playlist from a mood gradient

Abstract: Systems and methods for generating and playing a sequence of media objects based on a mood gradient are also disclosed. A mood gradient is a sequence of items, in which each item is media object having known characteristics or a representative set of characteristics of a media object, that is created or used by a user for a specific purpose. Given a mood gradient, one or more new media objects are selected for each item in the mood gradient based on the characteristics associated with that item. In this way, a sequence of new media objects is created but the sequence exhibits a similar variation in media object characteristics. The mood gradient may be presented to a user or created via a display illustrating a three-dimensional space in which each dimension corresponds to a different characteristic. The mood gradient may be represented as a path through the three-dimensional space and icons representing media objects are located within the three-dimensional space based on their characteristics.