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.

Web site activity monitoring system with tracking by categories and terms

Abstract: A traffic monitor provides statistics of traffic using an activity input for receiving data related to activity on a server system. Events being monitored are binned by topic or term, where the terms are associated with categories. The categories can be a hierarchy of categories and subcategories, with terms being in one or more categories. The categorized events include page views and search requests and the results might be normalized over a field of events and a result output for outputting results of the normalizer as the statistical analyses of traffic.

Hypothalamic involvement in chronic migraine

Abstract: Objectives—Chronic migraine (CM), previously called transformed migraine, is a frequent headache disorder that aVects 2%-3% of the general population. Analgesic overuse, insomnia, depression, and anxiety are disorders that are often comorbid with CM. Hypothalamic dysfunction has been implicated in its pathogenesis, but it has never been studied in patients with CM. The aim was to analyze hypothalamic involvement in CM by measurement of melatonin, prolactin, growth hormone, and cortisol nocturnal secretion. Methods—A total of 338 blood samples (13/patient) from 17 patients with CM and nine age and sex matched healthy volunteers were taken. Melatonin, prolactin, growth hormone, and cortisol concentrations were determined every hour for 12 hours. The presence of comorbid disorders was also evaluated. Results—An abnormal pattern of hypothalamic hormonal secretion was found in CM. This included: (1) a decreased nocturnal prolactin peak, (2) increased cortisol concentrations, (3) a delayed nocturnal melatonin peak in patients with CM, and (4) lower melatonin concentrations in patients with CM with insomnia. Growth hormone secretion did not diVer from controls. Conclusion—These results support hypothalamic involvement in CM, shown by a chronobiologic dysregulation, and a possible hyperdopaminergic state in patients with CM. Insomnia might be an important variable in the study findings. (J Neurol Neurosurg Psychiatry 2001;71:747‐751)

A regression framework for learning ranking functions using relative relevance judgments

Abstract: Effective ranking functions are an essential part of commercial search engines. We focus on developing a regression framework for learning ranking functions for improving relevance of search engines serving diverse streams of user queries. We explore supervised learning methodology from machine learning, and we distinguish two types of relevance judgments used as the training data: 1) absolute relevance judgments arising from explicit labeling of search results; and 2) relative relevance judgments extracted from user click throughs of search results or converted from the absolute relevance judgments. We propose a novel optimization framework emphasizing the use of relative relevance judgments. The main contribution is the development of an algorithm based on regression that can be applied to objective functions involving preference data, i.e., data indicating that a document is more relevant than another with respect to a query. Experimental results are carried out using data sets obtained from a commercial search engine. Our results show significant improvements of our proposed methods over some existing methods.

E-commerce in Your Inbox: Product Recommendations at Scale

Abstract: In recent years online advertising has become increasingly ubiquitous and effective. Advertisements shown to visitors fund sites and apps that publish digital content, manage social networks, and operate e-mail services. Given such large variety of internet resources, determining an appropriate type of advertising for a given platform has become critical to financial success. Native advertisements, namely ads that are similar in look and feel to content, have had great success in news and social feeds. However, to date there has not been a winning formula for ads in e-mail clients. In this paper we describe a system that leverages user purchase history determined from e-mail receipts to deliver highly personalized product ads to Yahoo Mail users. We propose to use a novel neural language-based algorithm specifically tailored for delivering effective product recommendations, which was evaluated against baselines that included showing popular products and products predicted based on co-occurrence. We conducted rigorous offline testing using a large-scale product purchase data set, covering purchases of more than 29 million users from 172 e-commerce websites. Ads in the form of product recommendations were successfully tested on online traffic, where we observed a steady 9% lift in click-through rates over other ad formats in mail, as well as comparable lift in conversion rates. Following successful tests, the system was launched into production during the holiday season of 2014.

Presentation of Organized Personal and Public Data Using Communication Mediums

Abstract: Systems, methods and computer program products for providing information associated with an attachment (e.g., attachment received through an instant message system, online collaboration tool, electronic message and the like). A sidebar may allow a user to view comprehensive profile and content information associated with the attachment using an attachment information viewer. The sidebar also may allow the user to switch between a message attachment information view (e.g., to facilitate browsing of the document or attachment) and a person profile information view (e.g., to facilitate browsing of personal or public data).