Ontology-based Query Construction for GeoCLEF
This paper describes experiments with geographical information retrieval (GIR). Being different from the traditional information IR, we focus more on the query expansion instead of document ranking. We parse each topic into the event part and the geographic part and use different ontologies to expand both parts respectively. The results show promising results of our strategy for this task.

title: Information Synthesis for Answer Validation
abstract: This paper proposes an integration of Recognizing Textual Entailment (RTE) with other additional information to deal with the Answer Validation task. The additional information used in our participation in the Answer Validation Exercise (AVE 2008) is from named-entity (NE) recognizer, question analysis component, etc. We have submitted two runs, one run for English and the other for German, achieving f-measures of 0.64 and 0.61 respectively. Compared with our system last year, which purely depends on the output of the RTE system, the extra information does show its effectiveness.

title: Recognizing Textual Entailment Using a Subsequence Kernel Method
abstract: We present a novel approach to recognizing Textual Entailment. Structural features are constructed from abstract tree descriptions, which are automatically extracted from syntactic dependency trees. These features are then applied in a subsequence-kernel-based classifier to learn whether an entailment relation holds between two texts. Our method makes use of machine learning techniques using a limited data set, no external knowledge bases (e.g. WordNet), and no handcrafted inference rules. We achieve an accuracy of 74.5% for text pairs in the Information Extraction and Question Answering task, 63.6% for the RTE-2 test data, and 66.9% for the RET-3 test data.

title: Experimental Investigation of Co-Presence Factors in a Mixed Reality-Mediated Collaborative Design System
abstract: This paper argues how a Mixed Reality-Mediated collaborative design system should be featured after considering co-presence factors. This paper also presents an experiment to examine some of the co-presence factors, with a focus on the image size and viewing distance. The experimental results show that larger images and appropriate viewing distance could bring better sense of being in the Mixed Reality space and participants feel more involved in the design tasks. Therefore, by considering the co-presence factors, higher level of copresence and better effects in the Mixed Reality-mediated collaborative design system could be achieved.

title: Precomputed Visibility Cuts for Interactive Relighting with Dynamic BRDFs
abstract: This paper presents a novel PRT-based method that uses precomputed visibility cuts for interactive relighting with all-frequency environment maps and arbitrary dynamic BRDFs. Our method is inspired by the recent Lightcuts approach  and we parameterize distant environment lighting onto uniformly distributed sample points over the sphere. Using a binary tree structure of the points, we precompute and approximate each vertex's visibility function into clusters that we call the precomputed visibility cuts. These cuts are iteratively selected with bounded approximation error and confined cluster size. At run-time, a GPU-based relighting algorithm quickly computes the view-dependent shading color by accessing a dynamically built light tree, the precomputed visibility cuts, and a direct sampling of an arbitrary BRDF using each visibility cluster's average direction and the dynamic view direction. Compared to existing PRT techniques, our method guarantees uniform sampling of the lighting, requires no precomputed BRDF data, and can be easily extended to handle one-bounce glossy indirect transfer effects in real-time.

title: Interactive Glossy Reflections using GPU-based Ray Tracing with Adaptive LOD
abstract: We present an interactive GPU-based algorithm for accurately rendering high-quality, dynamic glossy reflection effects from both HDR environment maps and local scene objects. Our method uses hardware rasterization to produce primary pixels, and GPU-based BRDF importance sampling [CK07] to quickly generate reflected rays. We utilize a fast GPU ray tracer proposed by Carr et al. [CHCH06] to compute reflection hits. Our main contribution is an adaptive level-of-detail (LOD) control algorithm that greatly improves ray tracing performance during reflection shading. Specifically, we use the solid angle represented by each reflected ray to adaptively pick the level of termination in the BVH traversal step during ray tracing. This leads to 2 ∼ 3x speedup over an unmodified implementation of [CHCH06]. Based on the same solid angle measure, we derive a texture filtering formula to reduce reflection aliasing artifacts, taking advantage of hardware MIP mapping. This extends the filtering algorithm presented in [CK07] from environment mapping to local scene reflection. Using our algorithm, we demonstrate interactive rendering rates for several scenes featuring dynamic lighting and material changes, spatially varying BRDF parameters, and rigid-body object movement.

title: A Cognitive Study on the Effectiveness of an Augmented Virtuality-Based Collaborative Design Space
abstract: This paper presents one empirical study on an Augmented Virtuality (AV)-based virtual environment dedicated for remote collaboration. This AV-based system enables a remote designer to explore a virtual counterpart of a remote built environment that needs to be re-designed. Results of the study demonstrate that the AV system is effective and achieves good overall satisfaction, but involves some issues. Results also reveals that the participants all gain a similar sense in the AV environment as experienced in the real space.

title: A Market-Based Adaptation for Resolving Competing Needs for Scarce Resources
abstract: The dynamic nature of many real-world domains (e.g., military, emergency first response and hurricane relief, etc) requires adaptive resource allocation to respond to changes in the environment that trigger additional resource requirements. Since the total resources are limited, there are often conflicts among various tasks regarding their resource needs. Thus, resources must be reallocated in order to maximize global utility for the current situation. This problem is further complicated when scarce resources are owned by distributed teams, each of which needs to allocate resources among tasks assigned to them, because each team has limited information about the other teams' resources and states. In this paper, we propose a market-based approach that uses an agent-based auction mechanism to enable teams to communicate and coordinate their utility information about possibly competing resource needs. As a result, the teams can collaboratively assess trade-offs among competing needs to allocate resources efficiently.