Personalizing user–agent interaction

Interface agents are computer programs that provide personalized assistance to users with their computer-based tasks. The interface agents developed so far have focused their attention on learning a user's preferences in a given application domain and on assisting him according to them. However, in order to personalize the interaction with users, interface agents should also learn how to best interact with each user and how to provide them assistance of the right sort at the right time. To fulfil this goal, an interface agent has to discover when the user wants a suggestion to solve a problem or deal with a given situation, when he requires only a warning about it and when he does not need any assistance at all. In this work, we propose a learning algorithm, named WoS, to tackle this problem. Our algorithm is based on the observation of a user's actions and on a user's reactions to the agent's assistance actions. The WoS algorithm enables an interface agent to adapt its behavior and its interaction with a user to the user's assistance requirements in each particular context.     

An approach to intelligent automated window management

The CUBRICON Intelligent Window Manager (CIWM) is a knowledge-based system that automates windowing operations. The CIWM is a component of CUBRICON, a prototype knowledge-based multi-media human-computer interface. CUBRICON accepts inputs and generates outputs using integrated multiple media/modalities including speech, printed/typed natural language, tables, forms, maps, graphics, and pointing gestures. The CIWM automatically performs window management functions on CUBRICON's color and monochrome screens. These functions include window creation, sizing, placement, removal, and organization. These operations are accomplished by the CIWM without direct human inputs, although the system provides for user override of the CIWM decisions.The motivation for automated window management is based on the premise that, by freeing the user's cognitive and temporal resources from the task of managing the human-computer interface, more of these resources are available for the user's application domain activities. As the problems and tasks confronting computer users become more complex and information intensive, the potential of this approach for improving overall performance is enhanced. Recent research discussed in this paper indicates that, for some database management tasks, a significant portion of the user's time is spent in managing the window-based interface. If these findings are representative of the larger range of computer-based tasks that use windowing systems, the concept of automated window management offers great potential for enhancing human performance on these computer-based tasks.This paper provides a brief overview of the CUBRICON system and describes the CIWM and its underlying design principles and premises. The following important CIWM features are discussed: the hybrid tiled and overlapped approach to window layout; an algorithm for determining the importance of a window based on its contents, relation to the ongoing dialogue, time of creation, frequency of use, and recency of use; and an approach to determining window size based on clutter and object resolution requirements. Actual interactive examples are provided to illustrate the CIWM functionality. Results of an evaluation of CUBRICON support the design. Those results which pertain specifically to the CIWM are presented. Limitations and applicability of this research are also discussed.     

Building respectful interface agents

To provide personalized assistance to users, interface agents have to learn not only a user's preferences and interests with respect to a software application, but also when and how the user prefers to be assisted. Interface agents have to detect the user's intention to determine when to assist the user, and the user's interaction and interruption preferences to provide the right type of assistance without hindering the user's work. In this work we describe a user profiling approach that considers these issues within a user profile and a decision making approach that enables the agent to choose the best type of assistance for a given user in a given situation. We also describe the results obtained when evaluating our proposal in the tourism domain, and we compare these results with some previous ones in the calendar management domain.     

多用户眼动跟踪数据的可视化共享与协同交互

随着数字图像处理技术的发展,以及计算机支持的协同工作研究的深入,眼动跟踪开始应用于多用户协同交互.但是已有的眼动跟踪技术主要针对单个用户,多用户眼动跟踪计算架构不成熟、标定过程复杂,眼动跟踪数据的记录、传输以及可视化共享机制都有待深入研究.为此,建立了基于梯度优化的协同标定模型,简化多用户的眼动跟踪标定过程;然后提出面向多用户的眼动跟踪计算架构,优化眼动跟踪数据的传输和管理.进一步地,探索眼动跟踪数据的可视化形式在协同交互环境下对用户视觉注意行为的影响,具体设计了圆点、散点、轨迹这3种可视化形式,并验证了圆点形式能够有效地提高多用户协同搜索任务的完成效率.在此基础上,设计与开发了基于眼动跟踪的代码协同审查系统,实现了代码审查过程中多用户眼动跟踪数据的同步记录、分发,以及基于实时注视点、代码行边框和背景灰度、代码行之间连线的可视化共享.用户实验结果表明,代码错误的平均搜索时间比没有眼动跟踪数据可视化分享时减少了20.1%,显著提高了协同工作效率,验证了该方法的有效性.     

Countering overlapping rectangle privacy attack for moving kNN queries

An important class of LBSs is supported by the moving k nearest neighbor (MkNN) query, which continuously returns the k nearest data objects for a moving user. For example, a tourist may want to observe the five nearest restaurants continuously while exploring a city so that she can drop in to one of them anytime. Using this kind of services requires the user to disclose her location continuously and therefore may cause privacy leaks derived from the user's locations. A common approach to protecting a user's location privacy is the use of imprecise locations (e.g., regions) instead of exact positions when requesting LBSs. However, simply updating a user's imprecise location to a location-based service provider (LSP) cannot ensure a user's privacy for an MkNN query: continuous disclosure of regions enable LSPs to refine more precise location of the user. We formulate this type of attack to a user's location privacy that arises from overlapping consecutive regions, and provide the first solution to counter this attack. Specifically, we develop algorithms which can process an MkNN query while protecting the user's privacy from the above attack. Extensive experiments validate the effectiveness of our privacy protection technique and the efficiency of our algorithm.     

ICOMDT:一个面向动态任务的交互计算模型

近年来,包含动态任务的交互式系统得到了广泛的应用.基于现有对用户与动态任务交互的研究,提出一个面向动态任务的定量化可计算的交互模型ICOM^DT,用于解释用户与动态任务的交互行为,并实现用户意图预测.更具体地,将ICOM^DT应用于运动目标选择任务,设计了两个实验以验证模型的有效性.实验1收集用户数据对模型进行拟合并预测用户选择的错误率,实验结果表明,能够很好地拟合且预测值也与真实值接近;实验2将模型对用户意图的理解拓展为一种辅助运动目标选择技术ICOMPointer,通过在具体的游戏场景中与Windows原本的选择技术及两种现有的增强目标选择技术对比,发现使用ICOMPointer选中目标的平均完成时间更短,完成速度更快.ICOM^DT模型的提出对计算机理解用户意图,提高用户与动态任务的交互效率有着重要意义.     

融合全局和局部特征的下一个兴趣点推荐方法

随着海量移动数据的积累,下一个兴趣点推荐已成为基于位置的社交网络中的一项重要任务.目前,主流方法倾向于从用户近期的签到序列中捕捉局部动态偏好,但忽略了历史移动数据蕴含的全局静态信息,从而阻碍了对用户偏好的进一步挖掘,影响了推荐的准确性.为此,提出一种基于全局和局部特征融合的下一个兴趣点推荐方法.该方法利用签到序列中的顺序依赖和全局静态信息中用户与兴趣点之间、连续签到之间隐藏的关联关系建模用户移动行为.首先,引入两类全局静态信息,即User-POI关联路径和POI-POI关联路径,学习用户的全局静态偏好和连续签到之间的全局依赖关系.具体地,利用交互数据以及地理信息构建异构信息网络,设计关联关系表示学习方法,利用相关度引导的路径采样策略以及层级注意力机制获取全局静态特征.然后,基于两类全局静态特征更新签到序列中的兴趣点表示,并采用位置与时间间隔感知的自注意力机制来捕捉用户签到序列中签到之间的局部顺序依赖,进而评估用户访问兴趣点概率,实现下一个兴趣点推荐.最后,在两个真实数据集上进行了实验比较与分析,验证了所提方法能够有效提升下一个兴趣点推荐的准确性.此外,案例分析表明,建模显式路径有助于提...     

Present-ing the user: constructing the persona

Abstract

During the last few years personas has become an established design technique within the IT-design field. Using personas has proven itself as a valuable approach for designers to switch between a developer's perspective and a user's perspectivein the design process. The technique is claimed to help designers in keeping a clear focus and shaping a consistent user-interface by making ‘the user’ present in the design work. In this paper we report on a number of projects where we have elaborated on the persona approach for collaborative design. With the goalof creating ‘user presence’ in the design process, we have developed an approach building on a combination of ethnographic exploration, participatory inquiry, and collaborative design. This paper carries two interrelated points: the grounding of personasin existing practice; and the notion that ‘the user’ is created as an ongoing process throughout the design work.     

Efficient sketch‐based creation of detailed character models through data‐driven mesh deformations

Creation of detailed character models is a very challenging task in animation production. Sketch‐based character model creation from a 3D template provides a promising solution. However, how to quickly find correct correspondences between user's drawn sketches and the 3D template model, how to efficiently deform the 3D template model to exactly match user's drawn sketches, and realize real‐time interactive modeling is still an open topic. In this paper, we propose a new approach and develop a user interface to effectively tackle this problem. Our proposed approach includes using user's drawn sketches to retrieve a most similar 3D template model from our dataset and marrying human's perception and interactions with computer's highly efficient computing to extract occluding and silhouette contours of the 3D template model and find correct correspondences quickly. We then combine skeleton‐based deformation and mesh editing to deform the 3D template model to fit user's drawn sketches and create new and detailed 3D character models. The results presented in this paper demonstrate the effectiveness and advantages of our proposed approach and usefulness of our developed user interface. Copyright © 2015 John Wiley & Sons, Ltd.     

VirtualDesk: A Comfortable and Efficient Immersive Information Visualization Approach

3D representations are potentially useful under many circumstances, but suffer from long known perception and interaction challenges. Current immersive technologies, which combine stereoscopic displays and natural interaction, are being progressively seen as an opportunity to tackle this issue, but new guidelines and studies are still needed, especially regarding information visualization. Many proposed approaches are impractical for actual usage, resulting in user discomfort or requiring too much time or space. In this work, we implement and evaluate an alternative data exploration metaphor where the user remains seated and viewpoint change is only realisable through physical movements. All manipulation is done directly by natural mid‐air gestures, with the data being rendered at arm's reach. The virtual reproduction of the analyst's desk aims to increase immersion and enable tangible interaction with controls and two dimensional associated information. A comparative user study was carried out against a desktop‐based equivalent, exploring a set of 9 perception and interaction tasks based on previous literature and a multidimensional projection use case. We demonstrate that our prototype setup, named VirtualDesk, presents excellent results regarding user comfort and immersion, and performs equally or better in all analytical tasks, while adding minimal or no time overhead and amplifying user subjective perceptions of efficiency and engagement. Results are also contrasted to a previous experiment employing artificial flying navigation, with significant observed improvements.     

A Study on Automatic Classification of Users’ Desktop Interactions

Knowledge workers frequently change activities, either by choice or through interruptions. With an increasing number of activities and activity switches, it is becoming more and more difficult for knowledge workers to keep track of their desktop activities. This article presents our efforts to achieve activity awareness through automatic classification of user's everyday desktop activities. For getting a deeper understanding, we investigate performance of various classifiers with respect to discriminative power of time-, interaction-, and content-based feature sets for different work scenarios and users. Specifically, by viewing an activity as a sequence of desktop interactions we present (1) a methodology for translating a user's desktop interactions into activities, (2) evaluation of the discriminative power of different activity features and feature types, and (3) analysis of supervised classification models for classifying desktop activity under two different scenarios, i.e., an activity-centric scenario and a user-centric scenario. The experiments are carried out on a real-world dataset, and the results show satisfactory accuracy using relatively few and simple types of features.     

Beyond performance: Feature awareness in personalized interfaces

Personalized graphical user interfaces have the potential to reduce visual complexity and improve interaction efficiency by tailoring elements such as menus and toolbars to better suit an individual user's needs. When an interface is personalized to make useful features more accessible for a user's current task, however, there may be a negative impact on the user's awareness of the full set of available features, making future tasks more difficult. To assess this tradeoff we introduce awareness as an evaluation metric to be used in conjunction with performance. We then discuss three studies we have conducted, which show that personalized interfaces tradeoff awareness of unused features for performance gains on core tasks. The first two studies, previously published and presented only in summary, demonstrate this tradeoff by measuring awareness using a recognition test of unused features in the interface. The studies also evaluated two different types of personalized interfaces: a layered interfaces approach and an adaptive split menu approach. The third study, presented in full, focuses on adaptive split menus and extends results from the first two studies to show that different levels of awareness also correspond to an impact on performance when users are asked to complete new tasks. Based on all three studies and a survey of related work, we outline a design space of personalized interfaces and present several factors that could affect the tradeoff between core task performance and awareness. Finally, we provide a set of design implications that should be considered for personalized interfaces.     

Performance‐Based Biped Control using a Consumer Depth Camera

We present a technique for controlling physically simulated characters using user inputs from an off‐the‐shelf depth camera. Our controller takes a real‐time stream of user poses as input, and simulates a stream of target poses of a biped based on it. The simulated biped mimics the user's actions while moving forward at a modest speed and maintaining balance. The controller is parameterized over a set of modulated reference motions that aims to cover the range of possible user actions. For real‐time simulation, the best set of control parameters for the current input pose is chosen from the parameterized sets of pre‐computed control parameters via a regression method. By applying the chosen parameters at each moment, the simulated biped can imitate a range of user actions while walking in various interactive scenarios.     

基于文本聚类与兴趣衰减的微博用户兴趣挖掘方法

微博平台隐含潜在的用户信息,通过微博数据挖掘用户兴趣具有重要的社会意义。结合用户兴趣与微博信息的特点,提出了一种文本聚类与兴趣衰减的微博用户兴趣挖掘（TCID-MUIM）方法。首先,通过基于词林的同义词合并策略弥补建模时词频信息不足的弊端;其次,利用二次Single-Pass不完全聚类算法将用户微博划分为多个簇,将簇合并为同一文档以弥补微博文本短小难以挖掘主题信息的问题;最后,通过LDA模型建模,并考虑用户兴趣随时间变化的问题,引入时间因子,将微博—主题矩阵压缩为用户—主题矩阵,获取用户兴趣。实验表明,较之传统建模方法与合并用户历史微博为同一文档的建模方法,TCID-MUIM方法挖掘的用户兴趣主题具有更好的主题区分度,且更贴合用户的真实兴趣偏好。     

Secure Group Communication with Hidden Group Key

ABSTRACT

Grid environment is mainly concerned with sharing diverse resources belonging to different administrative domains. Security and scalability are important issues for secure group communication in a grid environment. Secure group communication among group members working on collaborative tasks involves confidentiality and authenticity of the message and the session key. In order to transmit the data in a secure way, a suitable key transfer protocol should be implemented. Key transfer protocols rely on a centralized Key Management Center (KMC), an entity responsible for managing user authentication, generating group keys and distributing it to all the members of the communicating group secretly. In this paper, we proposed a secure key transfer protocol that uses the concepts of soft dipole representation of the image and steganography for transferring password and group key securely to the users. In this protocol, users submit their images at the time of registration with the KMC. First KMC compute the soft dipole representation S_I of every user's image and each user's image can be uniquely represented by its corresponding soft dipole representation. The soft dipole representation of each user's image is used as a password for authentication of corresponding user with KMC. KMC generates the group key using soft dipoles of the images of the group members. To preserve the confidentiality, the group key is embedded into an image (using information hiding technique) and KMC broadcast that image to all the group members.     

Real‐time horse gait synthesis

Horse locomotion exhibits rich variations in gaits and styles. Although there have been many approaches proposed for animating quadrupeds, there is not much research on synthesizing horse locomotion. In this paper, we present a horse locomotion synthesis approach. A user can arbitrarily change a horse's moving speed and direction, and our system would automatically adjust the horse's motion to fulfill the user's commands. At preprocessing, we manually capture horse locomotion data from Eadweard Muybridge's famous photographs of animal locomotion and expand the captured motion database to various speeds for each gait. At runtime, our approach automatically changes gaits based on speed, synthesizes the horse's root trajectory, and adjusts its body orientation based on the horse's turning direction. We propose an asynchronous time warping approach to handle gait transition, which is critical for generating realistic and controllable horse locomotion. Our experiments demonstrate that our system can produce smooth, rich, and controllable horse locomotion in real time. Copyright © 2012 John Wiley & Sons, Ltd.     

WallTop: Managing Overflowing Windows on a Large Display

With the ever increasing amount of digital information, users desire more screen real estate to process daily desktop computing work, and might well benefit from using a large high-resolution display for information management. Unfortunately, we know very little about users' behaviors when using such a display for daily computing, and current user interfaces are mainly designed for normal-sized desktop monitors, which might not well suit a large display. In this article, we first present a longitudinal study that investigates how users manage overflowing digital information on a wall-sized display in a personal desktop computing context by comparing it with single and dual desktop monitors. Results showed users' unanimous preferences of working on a large display and revealed large-display users' unique activity patterns of managing windows. Guided by the study results, we designed a set of interaction techniques that provide greater flexibility in managing multiple windows. They include facile methods for selecting, moving, and resizing multiple windows using an active window boundary called Fringe, rearranging selected windows using multi- and single-window marking menus, packing/unpacking the selected windows using easily activated icons, and freely adjusting the order of overlapping windows with a Jab-to-Lift operation. We coherently integrated these techniques with traditional operations in a large-display window management prototype called WallTop. Two rounds of usability testing showed that users can quickly and easily learn the new interaction techniques and apply them to realistic window management tasks on a large display with increased efficiency.     

基于连续查询的用户轨迹k-匿名隐私保护算法

随着移动服务和移动网络的持续发展,基于LBS的连续查询服务被广泛应用。基于单点的K-匿名位置隐私保护算法已经不能满足连续查询下用户位置隐私需求。针对用户轨迹隐私保护提出新的保护方法,该方法采用不可信第三方中心匿名器,用户获取自己的真实位置后首先在客户端进行模糊处理,然后提交给第三方匿名器,第三方匿名器根据用户的隐私需求结合用户某时刻的真实位置信息生成虚假用户,然后根据历史数据生成虚假轨迹。为了进一步提高虚假轨迹与用户真实轨迹的相似性,该算法提出了虚假轨迹生成的两个约束条件：虚假轨迹距用户真实轨迹的距离约束和相似性约束。经大量实验证明,该算法与传统的不同时刻K-匿名算法相比,不仅可以满足连续查询的用户轨迹隐私保护而且可以满足基于快照的LBS用户位置隐私保护。