Real Language Users

The idea of a perfectly competent but resource limited language user is the basis of many models of sentence comprehension. It is widely assumed that linguistic competence is a) uniform; b) generative; c) autonomous; d) automatic and e) constant. It is also believed that the free expression of these properties is frustrated by limits in the availability of computational resources. However, no firm experimental evidence for the classical language user appears to exist. Negative evidence for each assumption is reviewed here and the notion of resource limitations is shown to be suspect. An experiment is reported which tested each of the five assumptions underlying the conventional notion of linguistic competence. It was found that native speakers of English a) differed in grammatical skill; b) often failed to display productivity; c) violated syntax in favour of plausibility; d) expended conscious effort to comprehend some sentences and e) appeared to adapt to novel structures as the experiment progressed. In line with previous studies, a relationship was found between comprehension skill and formal education. A new finding is that highly educated non-native speakers of English can outperform less educated native speakers of English in comprehending grammatically challenging English sentences. The results indicate that the classical language user is an inaccurate model of real language users, who appear to differ considerably in linguistic skill. A number of specific questions for further research are raised

Spartan Daily, March 30, 1953

Volume 41, Issue 111https://scholarworks.sjsu.edu/spartandaily/11857/thumbnail.jp

Constrained Signaling in Auction Design

We consider the problem of an auctioneer who faces the task of selling a good (drawn from a known distribution) to a set of buyers, when the auctioneer does not have the capacity to describe to the buyers the exact identity of the good that he is selling. Instead, he must come up with a constrained signalling scheme: a (non injective) mapping from goods to signals, that satisfies the constraints of his setting. For example, the auctioneer may be able to communicate only a bounded length message for each good, or he might be legally constrained in how he can advertise the item being sold. Each candidate signaling scheme induces an incomplete-information game among the buyers, and the goal of the auctioneer is to choose the signaling scheme and accompanying auction format that optimizes welfare. In this paper, we use techniques from submodular function maximization and no-regret learning to give algorithms for computing constrained signaling schemes for a variety of constrained signaling problems

The Cowl - v.23 - n.9 - Dec 14, 1960

The Cowl - student newspaper of Providence College. Volume 23, Number 9 - December 14, 1960. 6 pages

Adaptive Processing of Spatial-Keyword Data Over a Distributed Streaming Cluster

The widespread use of GPS-enabled smartphones along with the popularity of micro-blogging and social networking applications, e.g., Twitter and Facebook, has resulted in the generation of huge streams of geo-tagged textual data. Many applications require real-time processing of these streams. For example, location-based e-coupon and ad-targeting systems enable advertisers to register millions of ads to millions of users. The number of users is typically very high and they are continuously moving, and the ads change frequently as well. Hence sending the right ad to the matching users is very challenging. Existing streaming systems are either centralized or are not spatial-keyword aware, and cannot efficiently support the processing of rapidly arriving spatial-keyword data streams. This paper presents Tornado, a distributed spatial-keyword stream processing system. Tornado features routing units to fairly distribute the workload, and furthermore, co-locate the data objects and the corresponding queries at the same processing units. The routing units use the Augmented-Grid, a novel structure that is equipped with an efficient search algorithm for distributing the data objects and queries. Tornado uses evaluators to process the data objects against the queries. The routing units minimize the redundant communication by not sending data updates for processing when these updates do not match any query. By applying dynamically evaluated cost formulae that continuously represent the processing overhead at each evaluator, Tornado is adaptive to changes in the workload. Extensive experimental evaluation using spatio-textual range queries over real Twitter data indicates that Tornado outperforms the non-spatio-textually aware approaches by up to two orders of magnitude in terms of the overall system throughput

The Grizzly, October 23, 2008

Professors\u27 Performance to Jazz Up Your Friday Night • Cafe Nia Event Brings Spirit of Poetry to Homecoming • Active Minds to Spread Mental Health Awareness at UC • Safe to Use Internet to Play Doctor? • UC Popularity Growing Steadily • Stand Up: STAND Rallies Ursinus Students for Darfur • Another Night of Artistry in Philadelphia • Omega Chi Blood Drive Takes the UC Campus by Storm, Highest Turnout Yet • Alpha Paintball Company: Fun for the Whole Family • Assassins Players Still on the Lookout • Opinions: GSA Members Call for Respect; Breakaway Presents Ten Minute Play Festival, Take Two • Senior Spotlight: Lisa Clark, Senior Women\u27s Soccer Playerhttps://digitalcommons.ursinus.edu/grizzlynews/1772/thumbnail.jp