From Echo to Ring doorbell and Fire TV, are you comfortable Amazon with controlling your smart home?

USATODAY

A link has been posted to your Facebook feed. Amazon acquired another startup this week, the maker of the beloved tech product Eero, a mesh router that improves dead Wi-Fi spots in the home. To that, you might have said, OK, so? But, more importantly, it's an indication of how Amazon wants to go further than just making our homes "smart." It wants to turn our dwellings into the "Amazon Home."


Apple's WWDC unveils ways to help you put the iPhone down — and then get sucked back in

USATODAY

Attendees take pictures before the start of the opening keynote during the 2018 Apple Worldwide Developer Conference at the San Jose Convention Center on June 4, 2018 in San Jose, Calif. Apple CEO Tim Cook will kick off the WWDC that runs through June 8. SAN JOSE -- Apple unveiled new ways to limit your screen time on iPhones and other mobile gadgets at its annual developers conference here -- and at the same time unleashed new ways to spend more time on its devices. That seeming contradiction highlights the growing dilemma for Silicon Valley giants such as Apple, Facebook and Google as they pitch their ubiquitous products while acknowledging growing concerns about tech addiction and consumer privacy. Apple tackled the latter with new settings in its Safari browser that allow users to limit Facebook and others apps from following their trails around the Web -- a pointed knock against the social network, which fended off a new round of privacy breach allegations this weekend.


Google sets the bar high for its Oct. phone reveal

USATODAY

Google has helped build intense speculation for its October 4 event in San Francisco, where it's expected to reveal new phones aimed at consumers that will power a new virtual reality platform, and possibly other smart home devices. Now that the buzz has reached a football-stadium roar, here comes the hard part: living up to the hype. Google has been teasing the event as one for the history books. A tweet Monday from Hiroshi Lockheimer, the company's senior vice president of Android, Chrome OS and Google Play, turned up the volume on the buzz. We announced the 1st version of Android 8 years ago today.


Predicting Appropriate Semantic Web Terms from Words

AAAI Conferences

The Semantic Web language RDF was designed to unambiguously define and use ontologies to encode data and knowledge on the Web. Many people find it difficult, however, to write complex RDF statements and queries because doing so requires familiarity with the appropriate ontologies and the terms they define. We describe a system that suggests appropriate RDF terms given semantically related English words and general domain and context information. We use the Swoogle Semantic Web search engine to provide RDF term and namespace statistics, the WorldNet lexical ontology to find semantically related words, and a naïve Bayes classifier to suggest terms. A customized graph data structure of related namespaces is constructed from Swoogle's database to speed up the classifier model learning and prediction time.


HodgeRank with Information Maximization for Crowdsourced Pairwise Ranking Aggregation

arXiv.org Machine Learning

Recently, crowdsourcing has emerged as an effective paradigm for human-powered large scale problem solving in various domains. However, task requester usually has a limited amount of budget, thus it is desirable to have a policy to wisely allocate the budget to achieve better quality. In this paper, we study the principle of information maximization for active sampling strategies in the framework of HodgeRank, an approach based on Hodge Decomposition of pairwise ranking data with multiple workers. The principle exhibits two scenarios of active sampling: Fisher information maximization that leads to unsupervised sampling based on a sequential maximization of graph algebraic connectivity without considering labels; and Bayesian information maximization that selects samples with the largest information gain from prior to posterior, which gives a supervised sampling involving the labels collected. Experiments show that the proposed methods boost the sampling efficiency as compared to traditional sampling schemes and are thus valuable to practical crowdsourcing experiments.