Echolocation — From range to outline segments

A ring of ultrasonic sensors mounted on a mobile robot is used to map a room. The sensors are modelled with an arc model: the object causing the reflection lies on an arc with radius equal to the range and arc angle equal to twice the beam angle. By fusing sensing with motion, a surface is displayed as a sequence of arcs. In this paper, the algorithm for obtaining outline segments from the arcs is presented.     

The importance of glossaries

Standards cannot be set, specifications cannot be written uniformly and unambiguously, and methods cannot be described succinctly, without an agreed terminology. Producing a glossary is a painstaking process and the fundamental principles involved are described. Some difficulties and misunderstandings are identified.     

Best analytic approximation of rational functions of degree 2: Symmetrization of formulae of N. J. Young

Formulae, explicitly symmetric in the roots of the denominator, are derived for the best approximation to a rational function of degree 2 by an analytic function and by a function with at most one pole.     

Matching treatment focus to patient social investment and support: 18-month follow-up results.

Patients were randomly assigned to 1 of 3 treatments: brief broad-spectrum (BBS), extended relationship enhancement (ERE), or extended cognitive–behavioral (ECB). A hierarchical latent growth model was used to analyze the data of 188 patients (82%) followed for 18 months. ERE treatment was significantly more effective in increasing abstinence of patients entering treatment with a network unsupportive of abstinence or with a low level of investment in their network, whereas BBS treatment was more effective for patients with either (a) both a social network unsupportive of abstinence and a low level of network investment or (b) high investment in a network supportive of abstinence. ECB outcomes were neither as good as those matched nor as bad as those mismatched to the different exposures of relationship enhancement. This suggests that dose of relationship enhancement should be determined after assessing patient relationships. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Exploring latent browsing graph for question answering recommendation

In this paper, we develop a framework of Question Answering Pages (referred to as QA pages) recommendation. Our proposed framework consists of the two modules: the off-line module to determine the importance of QA pages and the on-line module for on-line QA page recommendation. In the off-line module, we claim that the importance of QA pages could be discovered from user click streams. If the QA pages are of higher importance, many users will click and spend their time on these QA pages. Moreover, the relevant relationships among QA pages are captured by the browsing behavior on these QA pages. As such, we exploit user click streams to model the browsing behavior among QA pages as QA browsing graph structures. The importance of QA pages is derived from our proposed QA browsing graph structures. However, we observe that the QA browsing graph is sparse and that most of the QA pages do not link to other QA pages. This is referred to as a sparsity problem. To overcome this problem, we utilize the latent browsing relations among QA pages to build a QA Latent Browsing Graph. In light of QA latent browsing graph, the importance score of QA pages (referred to as Latent Browsing Rank) and the relevance score of QA pages (referred to as Latent Browsing Recommendation Rank) are proposed. These scores demonstrate the use of a QA latent browsing graph not only to determine the importance of QA pages but also to recommend QA pages. We conducted extensive empirical experiments on Yahoo! Asia Knowledge Plus to evaluate our proposed framework.     

Faster Approximate String Matching for Short Patterns

We study the classical approximate string matching problem, that is, given strings P and Q and an error threshold k, find all ending positions of substrings of Q whose edit distance to P is at most k. Let P and Q have lengths m and n, respectively. On a standard unit-cost word RAM with word size w≥log n we present an algorithm using time

On the network effect in Web 2.0 applications

In recent years, the proliferation of the world wide web has lead to an increase in a number of applications such as search, social networks and auctions, whose success depends critically upon the number of users of that service. Two examples of such applications are internet auctions and social networks. One of the characteristics of online auctions is that a successful implementation requires a high volume of buyers and sellers at its website. Consequently, auction sites which have a high volume of traffic have an advantage over those in which the volume is limited. This results in even greater polarization of buyers and sellers towards a particular site. The same is true for social networks in which greater use of a given social network increases the use from other participants on the network. This is often referred to as the “network effect” in a variety of interaction-centric applications in networks. While this effect has qualitatively been known to increase the value of the overall network, its effect has never been modeled or studied rigorously. In this paper, we construct a Markov model to analyze the network effect in the case of two important classes of web applications. These correspond to auctions and social networks. We show that the network effect is very powerful and can result in a situation in which an auction or a social networking site can quickly overwhelm its competing sites. Thus, the results of this paper show the tremendous power of the network effect for Web 2.0 applications.