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 characterization of online browsing behavior

Abstract: In this paper, we undertake a large-scale study of online user behavior based on search and toolbar logs. We propose a new CCS taxonomy of pageviews consisting of Content (news, portals, games, verticals, multimedia), Communication (email, social networking, forums, blogs, chat), and Search (Web search, item search, multimedia search). We show that roughly half of all pageviews online are content, one-third are communications, and the remaining one-sixth are search. We then give further breakdowns to characterize the pageviews within each high-level category.We then study the extent to which pages of certain types are revisited by the same user over time, and the mechanisms by which users move from page to page, within and across hosts, and within and across page types. We consider robust schemes for assigning responsibility for a pageview to ancestors along the chain of referrals. We show that mail, news, and social networking pageviews are insular in nature, appearing primarily in homogeneous sessions of one type. Search pageviews, on the other hand, appear on the path to a disproportionate number of pageviews, but cannot be viewed as the principal mechanism by which those pageviews were reached.Finally, we study the burstiness of pageviews associated with a URL, and show that by and large, online browsing behavior is not significantly affected by "breaking" material with non-uniform visit frequency.

Mining Graph Evolution Rules

Abstract: In this paper we introduce graph-evolution rules , a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequence of snapshots of an evolving graph, we aim at discovering rules describing the local changes occurring in it. Adopting a definition of support based on minimum image we study the problem of extracting patterns whose frequency is larger than a minimum support threshold. Then, similar to the classical association rules framework, we derive graph-evolution rules from frequent patterns that satisfy a given minimum confidence constraint. We discuss merits and limits of alternative definitions of support and confidence, justifying the chosen framework. To evaluate our approach we devise GERM (Graph Evolution Rule Miner), an algorithm to mine all graph-evolution rules whose support and confidence are greater than given thresholds. The algorithm is applied to analyze four large real-world networks (i.e., two social networks, and two co-authorship networks from bibliographic data), using different time granularities. Our extensive experimentation confirms the feasibility and utility of the presented approach. It further shows that different kinds of networks exhibit different evolution rules, suggesting the usage of these local patterns to globally discriminate different kind of networks.

On the value of temporal information in information retrieval

Abstract: Time is an important dimension of any information space and can be very useful in information retrieval. Current information retrieval systems and applications do not take advantage of all the time information available in the content of documents to provide better search results and user experience. In this paper we show some of the areas that can benefit from exploiting such temporal information.

Impact of the administration of probiotics on the incidence of ventilator-associated pneumonia: a meta-analysis of randomized controlled trials.

Abstract: Background:Previous reviews showed no benefit for the administration of probiotics in critically ill patients, but they did not focus on ventilator-associated pneumonia.Design:Meta-analysis of randomized controlled trials comparing probiotics and control in patients undergoing mechanical ventilation

The Sinus, Allergy and Migraine Study (SAMS).

Abstract: Objective.—The objective of this study is to classify (according to the current International Headache Society's criteria [ICHD-II]) the headache types that those with self-diagnosed sinus headache experience and to determine barriers to correct diagnosis. Background.—The American Migraine Study II estimates that 28 million Americans suffer from migraine headache. The majority of these patients remain undiagnosed and many are erroneously diagnosed as having sinus headache. Despite this common diagnosis, the concept of sinus headache remains an enigma with a relative paucity of information in the literature. Methods.—Advertising in the greater Phoenix, U.S. metropolitan area was used to recruit 100 willing and consecutive subjects to participate in this descriptive clinical study (The Sinus, Allergy and Migraine Study [SAMS]). All patients who believed they suffered from sinus headache and were over 18 years of age were enrolled without exclusion. A detailed history and exam was performed in each patient, and patients were given headache diagnoses based on the current International Headache Society's (IHS) criteria. Results.—Of the 100 subjects with self-diagnosed headache, IHS diagnoses mistaken as sinus headache included migraine with or without aura (52%), chronic migraine associated with medication overuse versus probable medication overuse headache (11%), probable migraine (23%), cluster headache (1%), hemicrania continua (1%), headache secondary to rhinosinusitis (3%), and headaches nonclassifiable (9%). Weather changes (83%), seasonal variation (73%), exposure to allergens (62%), and changes in altitude (38%) were frequent migraine triggers. Seventy-six percent of migraine subjects reported pain in the distribution of the second division of the trigeminal nerve (either unilateral or bilateral), and 62% experienced bilateral forehead and maxillary pain with their headaches. The most common associated features included nasal congestion (56%), eyelid edema (37%), rhinorrhea (25%), conjunctival injection (22%), lacrimation (19%), and ptosis (3%). The headaches nonclassifiable were characterized by a bilateral maxillary pressure of mild to moderate intensity associated with at least one cranial autonomic symptom. Features suggestive of migraine were absent in all 9 of these nonclassifiable cases. Conclusions.—The majority of those with self-diagnosed sinus headache have migraine or probable migraine. In those patients with migraine, the most common reasons for misdiagnosis include headache triggers, pain location, and associated features (“guilt by provocation, location, and association”) commonly attributed to sinus headache. The clinician must be aware of these unique presentations of migraine so that a correct diagnosis can be made and effective treatment instituted. A portion of patients with self-diagnosed sinus headache suffer from a headache type, which is unclassifiable by the current IHS criteria. These headaches are characterized by bilateral maxillary pressure, mild to moderate pain intensity, cranial autonomic symptoms, and the complete absence of migraine features.