基于交互感知的探索式搜索中资源的推荐方法

基于关键词匹配的信息搜索技术日渐成熟,人们期待搜索引擎更加智能,能够根据模糊需求启发用户找到正确的信息,探索式搜索由此出现。已有依据关键词之间的语义关联进行搜索推荐的探索式搜索方式,能够启发用户找到与当前查询相关的其他信息。然而,这种随机式的推荐方式仅适用于用户对不熟悉的领域进行初步了解的应用场景。针对有特定搜索意图的用户,如何有效利用用户提供的信息,让信息推荐以符合认知规律的方式进行,并且能够使计算机智能地理解用户的下一步信息需求的意图是研究的关键。提出一种基于交互感知的信息推荐方法,设定交互的基本规则,便于系统尽快确定模糊用户需求的搜索意图。示例展示这种方式能够对有效交互进行定量分析,并能有效减少用户与系统之间交互的步数。     

Cracking the Incremental Paradigm of Japanese Creativity

This paper points out the differences between incremental and paradigm shift approaches to creativity in management that exists between Japanese and Western schools of thought. A number of examples are used to illustrate how a systematic incremental process that places emphasis on continuous improvement is key to Japanese creativity in management. A framework that captures the cornerstones of Japanese creativity is outlined. The paper concludes by discussing the contribution of this research and outlines a plan for further work.     

Exploratory Study of Organizational Creativity in Creative Organizations

The creative industries represent an important and growing sector of the UK economy. This paper explores organizational creativity in firms within the creative industries. A questionnaire based on both Amabile's ‘Organizational Creativity’ model and Ekvall's ‘Creative Climate’ model was completed in ten firms in different sectors of the creative industries. Follow‐up interviews with five firms were also conducted, to compare the outputs from each model as well as the variation in responses from firms in different sectors. The results indicate that both models of organizational creativity are complementary, although not necessarily fully applicable in the creative industries. Specific differences between firms in the graphic design/branding sector and firms in product design were also observed.     

Triggering Creativity in Teams: An Exploratory Investigation

Triggering, developing and maintaining creativity in teams is critical to the economic performance of the firm. This article presents an exploratory action research effort in a health care organization that focused on interaction patterns amongst team members, creativity and performance. The results indicate that the teams’ inquiry and dialogue into their interaction patterns have the potential of influencing creativity. Team interaction patterns were found to influence team performance. Directions for future research are discussed.     

交互式学习的布谷鸟搜索算法

针对布谷鸟搜索算法在求解旅行商问题时,存在初期信息缺乏严重和收敛速度慢等问题,提出一种交互式学习的布谷鸟搜索算法（Interactive Learning Cuckoo Search Algorithm,ILCSA）。为提高布谷鸟搜索算法的搜索效率,结合蚁群优化算法构建双层交互学习模型,将蚁群作为底层种群,布谷鸟作为高层种群,双种群互相学习,合作寻优,提高搜索速度;此外,在布谷鸟搜索算法中引入强化学习策略,自适应更新步长,并对发现概率进行动态调整,深度优化最优解,进一步提高解的质量。最后采用多组不同规模的标准TSPLIB算例与其他优化算法进行对比,结果表明ILCSA算法在求解精度和稳定性方面表现更优。     

Supporting Exploratory Analysis with the Select & Slice Table

In interactive visualization, selection techniques such as dynamic queries and brushing are used to specify and extract items of interest. In other words, users define areas of interest in data space that often have a clear semantic meaning. We call such areas Semantic Zones, and argue that support for their manipulation and reasoning with them is highly useful during exploratory analysis. An important use case is the use of these zones across different subsets of the data, for instance to study the population of semantic zones over time. To support this, we present the Select & Slice Table. Semantic zones are arranged along one axis of the table, and data subsets are arranged along the other axis of the table. Each cell contains a set of items of interest from a data subset that matches the selection specifications of a zone. Items in cells can be visualized in various ways, as a count, as an aggregation of a measure, or as a separate visualization, such that the table gives an overview of the relationship between zones and data subsets. Furthermore, users can reuse zones, combine zones, and compare and trace items of interest across different semantic zones and data subsets. We present two case studies to illustrate the support offered by the Select & Slice table during exploratory analysis of multivariate data.     

Creativity for Engineering Plant Design: An Exploratory Study

A pilot study of creativity enhancement techniques took place within a large engineering firm in the UK. Exploratory interviews were carried out with professionals in the areas of creativity, mechanical design engineering and management in order to identify informally acquired skills of successful design practice.¹ Engineers participated in an introductory one day training programme applying creative techniques to real design problems from the heavy industrial engineering field. Initial feedback on the programme was recorded in addition to impact studies which took place after a ten-week interval. The impact of the programme was reported during the course of interviews which were complemented with the completion of detailed questionnaires. Results suggest that traditional training programmes for such professionals may need to be modified to become more user-friendly.     

交互式遗传算法的个性化商品搜索

为解决电子商务中存在的用户搜索商品耗时太长的问题,提出了利用交互式遗传算法的个性化商品搜索.根据用户输入的初始搜索字段,利用基于关键词的多层递阶编码结构,构造进化个体,并给出此类编码方式的解码、交叉、变异算子.用户选择的潜在感兴趣的商品信息,提出了用户行为的进化个体适应值评价模型,以获得用户对所有商品的感兴趣度,进而利用交互式遗传算法辅助用户尽快搜索到满意信息.最后,将改进算法应用于JADE平台开发的智能购书系统,通过与现有购物平台在搜索耗时和成功率方面的比较验证了本文方法的有效性.     

Bidirectional Search for Interactive Motion Synthesis

We present an approach to improve the search efficiency for near‐optimal motion synthesis using motion graphs. An optimal or near‐optimal path through a motion graph often leads to the most intuitive result. However, finding such a path can be computationally expensive. Our main contribution is a bidirectional search algorithm. We dynamically divide the search space evenly and merge two search trees to obtain the final solution. This cuts the maximum search depth almost in half and leads to significant speedup. To illustrate the benefits of our approach, we present an interactive sketching interface that allows users to specify complex motions quickly and intuitively.     

Interactive Exploratory Visualization of 2D Vector Fields

In this paper we present several techniques to interactively explore representations of 2D vector fields. Through a set of simple hand postures used on large, touch‐sensitive displays, our approach allows individuals to custom‐design glyphs (arrows, lines, etc.) that best reveal patterns of the underlying dataset. Interactive exploration of vector fields is facilitated through freedom of glyph placement, glyph density control, and animation. The custom glyphs can be applied individually to probe specific areas of the data but can also be applied in groups to explore larger regions of a vector field. Re‐positionable sources from which glyphs—animated according to the local vector field—continue to emerge are used to examine the vector field dynamically. The combination of these techniques results in an engaging visualization with which the user can rapidly explore and analyze varying types of 2D vector fields, using a virtually infinite number of custom‐designed glyphs.     

A Learned Lexicon-Driven Paradigm for Interactive Video Retrieval

Effective video retrieval is the result of interplay between interactive query selection, advanced visualization of results, and a goal-oriented human user. Traditional interactive video retrieval approaches emphasize paradigms, such as query-by-keyword and query-by-example, to aid the user in the search for relevant footage. However, recent results in automatic indexing indicate that query-by-concept is becoming a viable resource for interactive retrieval also. We propose in this paper a new video retrieval paradigm. The core of the paradigm is formed by first detecting a large lexicon of semantic concepts. From there, we combine query-by-concept, query-by-example, query-by-keyword, and user interaction into the MediaMill semantic video search engine. To measure the impact of increasing lexicon size on interactive video retrieval performance, we performed two experiments against the 2004 and 2005 NIST TRECVID benchmarks, using lexicons containing 32 and 101 concepts, respectively. The results suggest that from all factors that play a role in interactive retrieval, a large lexicon of semantic concepts matters most. Indeed, by exploiting large lexicons, many video search questions are solvable without using query-by-keyword and query-by-example. In addition, we show that the lexicon-driven search engine outperforms all state-of-the-art video retrieval systems in both TRECVID 2004 and 2005     

An Exploratory Study: Supporting Collaborative Multimedia Systems Design

Multimedia systems design generally requires a collaborative effort from a group of designers with a variety of backgrounds and tasks, such as content experts, instructional designers, media specialists, users, and so forth. However, currently available design tools on the market are mainly designed for a single user. Tools intended to support a collaborative design process should coordinate independent activities of individual designers.This research investigated support for work groups engaged in designing multimedia systems. Specifically, it discussed a new collaborative design environment, called the KMS (Knowledge Management System)-based design environment, in which multimedia designers could share their design knowledge freely. Through two experimental groups, the research investigated impacts of the KMS-based design environment on their collaborative design activities (knowledge creating, knowledge securing, knowledge distributing, and knowledge retrieving activities). The research findings showed that the KMS-based design environment was a promising environment for collaborative multimedia systems design. More specifically, the research findings indicated that the KMS-based design environment supported creating, securing, and retrieving knowledge, but it did not support distributing knowledge. In addition, the research found that the social interactions between group members played important roles in the success of the collaborative multimedia systems design and that the KMS-based design environment did not support the socialization of group members. Furthermore, the research found that the inability of the KMS-based design environment to support the socialization was linked to its low performance level in supporting the knowledge distributing activity. The research explored the desired features of a collaborative support tool for multimedia systems design.     

支持多关键字搜索的条件代理重加密

为了实现细粒度的访问控制和多个关键字数据搜索,本文引入满足条件树和强一次性签名,提出一个可用于多个关键字搜索的条件代理重加密方案。与已有的方案相比,本文方案在计算效率上有明显的提升。该方案可抵抗选择密文攻击,在随机预言机模型下,满足选择密文攻击安全性。本文提出的方案对解决金融等行业中的敏感数据安全问题有重要的作用。     

Interactive Near Duplicate Search in Software Documentation

Programming and Computer Software - Various software features such as classes, methods, requirements, and tests often have similar functionality. This can lead to emergence of duplicates in their...     

支持嵌入式Web服务器的多层级力觉交互仿真

针对传统力觉交互操作过程复杂、模拟物理场景不真实的问题,提出支持嵌入式Web服务器的多层级力觉交互仿真研究方法.在嵌入式Web服务器的基础上添加离散LOD模型,计算相对交互速度,获得目标多层级的序列号进行碰撞计算,构建速度驱动模型.将碰撞检验离散速度驱动模型与SCP层级映射算法相结合,判定映射约束线段、映射约束包围盒单...     

支持协同感知的人—人交互界面的设计

描述了有关人-人交互界面中协同感知的基本概念和支持协同感知的常用方法,并在一般远程光标的基础上,提出了自适应远程光标的概念,使之不仅可以表现成员的身份、聚焦注意力,并且能够适应不同的工作模式及对象的不同表现形式。     

Interactive Search by Direct Manipulation of Dissimilarity Space

In this paper, we argue to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the feature space by feature selection, feature weighting or by adjusting the parameters of a function of the features. Other than existing techniques, we use feedback to adjust the dissimilarity space independent of feature space. This has the great advantage that it manipulates dissimilarity directly. To create a dissimilarity space, we use the method proposed by Pekalska and Duin, selecting a set of images called prototypes and computing distances to those prototypes for all images in the collection. After the user gives feedback, we apply active learning with a one-class support vector machine to decide the movement of images such that relevant images stay close together while irrelevant ones are pushed away (the work of Guo ). The dissimilarity space is then adjusted accordingly. Results on a Corel dataset of 10000 images and a TrecVid collection of 43907 keyframes show that our proposed approach is not only intuitive, it also significantly improves the retrieval performance.     

Improving Shape from Shading with Interactive Tabu Search

Optimisation based shape from shading (SFS) is sensitive to initialization: errors in initialization are a significant cause of poor overall shape reconstruction. In this paper, we present a method to help overcome this problem by means of user interaction. There are two key elements in our method. Firstly, we extend SFS to consider a set of initializations, rather than to use a single one. Secondly, we efficiently explore this initialization space using a heuristic search method, tabu search, guided by user evaluation of the reconstruction quality. Reconstruction results on both synthetic and real images demonstrate the effectiveness of our method in providing more desirable shape reconstructions.     

交互式Agent在文本搜索中的应用

介绍了一个嵌入了Agent的文本编辑器,名为SmartTag,它能够通过与用户的一系列交互推理出通用模式。用户通过提供一些文本搜索的例子,Agent会推理出一个能够覆盖这些例子的通用模式,并且用户可以通过弹出菜单手工调整当前的模式以得到最终模式。然后,Agent可以通过得到的模式自动匹配当前文档中的其余文本字符串,这一交互过程简化了动态文本搜索的复合程度,并且使得人机之间的交互更加自然。