The effects and interaction of spatial visualization and domain expertise on information seeking

Information seeking skills are becoming increasingly important as rapid and widespread developments in technology have made information available in more formats and from more sources than ever before. Research in human computer interaction (HCI) has demonstrated that primary cognitive abilities represent a powerful predictor of information-seeking success in electronic information systems. Specifically, spatial visualization ability (SVA) seems to be particularly related to hierarchical menus systems navigation within databases, online learning environments, information archival systems, and virtually all internet web sites. Research indicates that individuals with low SVA take longer to complete tasks and experience more errors on first attempts to find information in hierarchical databases compared to those with high SVA. Understanding the influences of SVA as well as its interaction with other aspects of individual differences, such as domain expertise, is critical to the design of systems intended to accommodate individual differences in users.Thirty-five college students (23 males and 12 females) were selected from the general student body of two universities and assigned to groups based upon their self-reported membership in one of two specific disciplines: business (n=26) or biology (n=9). Participants were then assigned to groups based upon scores on tests of SVA using a median-split. Each participant conducted five searches: one neutral search, two searches for business related information, and two searches for biology related information using the FirstSearch archival search tool.A 2×2 factorial Analysis of Variance with one between-groups variable (high vs. low SVA) and one within-group variable (high vs. low domain expertise) indicated a significant main effect of SVA as well as a significant main effect of Domain Expertise on the time required to find their first relevant article on the search topic. The analysis also revealed that there was no main effect for SVA on the total number of relevant articles found during the search period but there was a significant main effect of Domain Expertise on the total total-number-of-relevant-articles found. There was no interaction between SVA and Domain Expertise on either time to first article or total number of articles found.Results of the study extend existing knowledge regarding the effects of SVA and domain expertise on information seeking by demonstrating a strong effect of SVA and domain expertise on information seeking skills. The results of this study also provide evidence in support of interface designs that are friendlier to information seekers who have low SVA. Related findings and suggestions for further research are discussed.     

基于细粒度特征交互的推荐模型

随着电子商务的兴起,用户在网购的同时留下了大量的评论。用户评论通常包含丰富的用户兴趣和项目属性等语义信息,反应了用户对项目特征的偏好。近年来,许多基于深度学习的方法通过利用评论进行推荐,并取得了巨大成功。这些工作主要是采用注意机制来识别对评分预测很重要的词或方面。它们单一的从评论中提取特征信息,并通过用户和物品的特征交互得到预测分数。然而,过度的聚合可能会导致评论中细粒度信息的丢失。此外,现有的模型要么忽略了用户和项目评论的相关性,要么只在单个粒度上构建评论特性交互,这导致用户和项目的特征信息不能被有效而全面地捕获。针对上述问题,在本文我们考虑通过从评论的多个粒度捕获特征信息,然后为用户和物品进行多粒度下的特征交互,可以实现更好的评分预测和解释性。
为此,我们提出了一种新的用于评分预测的细粒度特征交互网络（FFIN）。首先,模型并没有将用户的所有评论聚合成一个统一的向量,而是将用户和物品的每条评论单独建模,通过堆叠的扩展卷积分层地为每个评论文本构建多层次表示,充分地捕获了评论的多粒度语义信息;其次,模型在每个语义层次上构建用户和物品评论的细粒度特征交互,这有效避免了单粒度交互导致的次级重要信息被忽略的问题;最后,由于用户的评论行为通常是主观且个性化的,我们没有使用注意力机制来识别重要信息,而是通过类似于图像识别的层次结构来识别高阶显著信号,并将其用于最终的评分预测。我们在6个来自Amazon和Yelp的具有不同特征的真实数据集上进行了广泛的实验。我们的结果表明,与最近提出的最先进的模型相比,所提出的FFIN在预测精度方面获得了显著的性能提升。进一步的实验分析表明,多粒度特征的交互,不仅突出了评论中的相关信息,还大大提高了评分预测的可解释性。     

Review-driven configuration scheme evaluation methodology with configuration interaction effects

This study focuses on configuration scheme evaluation (CSE) based on customer perceptions deduced from online reviews. It is noteworthy that customers in different market segments often hold significant differences in their perceptions of the same configuration. Meanwhile, there may exist a potential dependency relationship between configurations referred to as configuration interaction increasing the complexity of CSE. This paper proposes a review-driven interacting CSE methodology fusing with review texts and configuration documents to address these challenges. First, three indexes, namely configuration differentiation, price consistency, and usage scenario similarity, are defined to identify targeted segments. Second, a differentiated calculation strategy is designed to measure configuration performances based on the configuration data and review data in the identified segments. Third, a configuration performance aggregation function that considers configuration interaction is developed based on the Choquet integral. Finally, two CSE problem about car and laptop products is analyzed using the proposed methodology to verify its applicability. Three comparative studies are also conducted to show the effectiveness and stability of the proposals.     

Toward automated feature model configuration with optimizing non-functional requirements

ContextA software product line is a family of software systems that share some common features but also have significant variabilities. A feature model is a variability modeling artifact, which represents differences among software products with respect to the variability relationships among their features. Having a feature model along with a reference model developed in the domain engineering lifecycle, a concrete product of the family is derived by binding the variation points in the feature model (called configuration process) and by instantiating the reference model.ObjectiveIn this work we address the feature model configuration problem and propose a framework to automatically select suitable features that satisfy both the functional and non-functional preferences and constraints of stakeholders. Additionally, interdependencies between various non-functional properties are taken into account in the framework.MethodThe proposed framework combines Analytical Hierarchy Process (AHP) and Fuzzy Cognitive Maps (FCM) to compute the non-functional properties weights based on stakeholders’ preferences and interdependencies between non-functional properties. Afterwards, Hierarchical Task Network (HTN) planning is applied to find the optimal feature model configuration.ResultOur approach improves state-of-art of feature model configuration by considering positive or negative impacts of the features on non-functional properties, the stakeholders’ preferences, and non-functional interdependencies. The approach presented in this paper extends earlier work presented in [1] from several distinct perspectives including mechanisms handling interdependencies between non-functional properties, proposing a novel tooling architecture, and offering visualization and interaction techniques for representing functional and non-functional aspects of feature models.Conclusionour experiments show the scalability of our configuration approach when considering both functional and non-functional requirements of stakeholders.     

基于知识特征的界面交互模型及事件激活原则

人机关系知识化的发展趋势,使得人机交互过程的本质成为知识作业的过程,借鉴泰勒科学管理的研究思路和团队之前的相关研究,提出了知识界面的概念,并指出人与知识界面的交互过程实际上是对界面所表征的知识网的求解过程,因而其本质是一种知识作业的过程。在此基础上,构建了一个交互模型来表征人与知识界面的交互,并通过对模型的解析得出了一个界面的设计原则：事件激活原则。以手机界面为例,通过仿真实验验证了该设计原则的有效性。     

基于高阶特征交互的点击率预估模型的实现

传统的低阶特征模型不能充分利用大数据,从多个维度描述数据和用户.专注于高阶特征提取,结合显式和隐式特征交互的点击率预估模型可以利用好大数据的特点.使用Tensorflow框架搭建包含深度神经网络、因子压缩交互网络和多重特征自交互网络结构的模型,使用淘宝展示广告点击率预估数据集进行训练.模型采用对数损失值和ROC曲线下面积作为评价指标,与原始的LR、FM、Deep&Wide等典型模型进行比较,对数损失值降低了0.04,AUC值提高了0.05左右.     

The effects of motion and stereopsis on three-dimensional visualization

Previous studies have demonstrated that motion cues combined with stereoscopic viewing can enhance the perception of three-dimensional objects displayed on a two-dimensional computer screen. Using a variant of the mental rotation paradigm, subjects view pairs of object images presented on a computer terminal and judge whether the objects are the same or different. The effects of four variables on the accuracy and speed of decision performances are assessed: stereo vs. mono viewing, controlled vs. uncontrolled object motion, cube vs. sphere construction and wire frame vs. solid surface characteristic. Viewing the objects as three-dimensional images results in more accurate and faster decision performances. Furthermore, accuracy improves although response time increases when subjects control the object motion. Subjects are equally accurate comparing wire frame and solid images, although they take longer comparing wire frame images. The cube-based or sphere-based object construction has no impact on decision accuracy nor response time.     

Enhancing software model encoding for feature location approaches based on machine learning techniques

Software and Systems Modeling - Feature location is one of the main activities performed during software evolution. In our previous works, we proposed an approach for feature location in models...     

基于可视化图形特征的入侵检测方法

入侵检测是保障网络安全的重要措施,网络攻击手段的多样性和隐蔽性不断增强导致入侵检测愈加困难,迫切需要研究新的入侵检测方法。结合可视化技术和k近邻分类算法,提出一种基于图形特征的入侵检测方法。采用信息增益方法对原始特征进行排序选择,并进行雷达图可视化表示,提取雷达图的图形特征构成新的数据集并送入k近邻分类器进行训练和测试。通过KDDCUP99数据集仿真实验表明,该方法不仅能直观显示攻击行为,而且获得较好的攻击检测性能,对DOS攻击的检测率可达97.9%,误报率为1.5%。     

非对称高斯函数的时变体数据特征跟踪及可视化

目的 在传统基于时序曲线的时变体数据特征的识别与跟踪过程中,不仅需要用户具备丰富的先验知识来确定感兴趣特征的时序曲线形状,而且时序曲线段的匹配和抽取过程亦复杂,难以交互,这一定程度上降低了时变体数据可视化及分析效率.提出了一种新的基于高斯时序曲线的时变体数据可视化及分析方法.方法 首先,对时序曲线进行低通滤波,准确地查找极小值点,对时序曲线进行分段;进而,引入非对称高斯函数对时序曲线段进行拟合获得高斯时序曲线;为了进一步方便用户识别感兴趣特征,观察特征在时间域上的演变过程,提供一种便捷的交互技术,由用户单击任一时间步绘制结果图像中感兴趣的特征信息,分析视线方向上的特征可见性,以确定感兴趣特征及其对应的高斯曲线,进而由参数匹配获得所有时间步中感兴趣特征信息.结果 为了验证本文算法的高效性与可行性,对时序仿真的飓风数据进行特征跟踪与交互式可视化,可以看出,本文算法不仅可以准确跟踪飓风中心特征,而且特征分析与可视化效率亦大大提升.结论 相比于传统的时变体数据可视化方法,本文算法不需要用户先验知识的前提下,利用非对称高斯模拟时序曲线变化,进而由高斯参数匹配代替复杂的时序曲线匹配过程,有效地提升了时变体数据可视化及分析效率.     

网络安全可视化研究综述

网络安全可视化是近年来网络安全研究的热点。首先说明网络安全可视化的必要性,并给出网络安全可视化的概念、研究步骤及分类,深入分析了多种网络安全可视化方法的优缺点。最后,讨论了该领域当前存在的问题及今后的研究方向。     

基于顾客需求特征的眼镜产品配置设计研究

基于顾客的脸形特征,面向产品的个性化设计需求,提出了采用参数化建立眼镜结构单元库和变型设计。利用顾客头部的正侧面照片合成人脸的三维模型并提取脸形特征参数,根据脸形特征参数构建顾客需求矩阵,基于顾客需求特征与眼镜产品结构单元之间的映射关系,提出了需求特征匹配算法。最后,给出了网络环境下由顾客、经销商和设计人员协同参与的眼镜配置设计系统的框架结构。     

植物叶缘形态特征的建模和可视化研究

叶片形态模拟是植物建模和可视化的重要组成部分,而叶缘是叶片的一个重要形态特征.提出了一种交互式的叶缘生成方法,该方法首先利用边缘检测法从叶片的数字图片提取叶片的边缘轮廓,然后从边缘轮廓中选取特征点,并构成叶缘的拟合线;最后通过在边缘拟合线段上利用三角折线段和二次曲线等生成各种叶缘特征.系统同时提供了交互式的图形界面,用户能够方便地生成各种常见的叶缘形态特征.实验结果表明,该方法能够产生较强的真实感效果.     

Program entanglement,feature interaction and the feature language extensions

One of the most difficult tasks in software development is that the programmer must implement a feature going through a laborious and error prone process of modifying the programs of other features. The programs of the different features entangle in the same reusable program units of the programming language, making them also difficult to be verified, maintained and reused. We show that if (C1) the features interact, (C2) they are executed by the same process and (C3) they are implemented in a programming language that requires the programmer to specify execution flows, program entanglement is inevitable and the problem cannot be solved by software design alone. Applications with interacting features are common including those that require exception handling.The feature language extensions (FLX) is a set of programming language constructs designed to enable the programmer to develop interacting features as separate and reusable program modules even though the features interact. The programmer uses FLX to specify non-procedural program units, organize the program units into reusable features and integrate features into executable feature packages. He develops a feature based on a model instead of the code of other features. FLX supports an automatic procedure to detect the interaction condition among features; the programmer then resolve the interaction in a feature package without changing feature code. FLX features and feature packages are reusable; the programmer may package different combinations of them and resolve their interactions differently to meet different user needs. An FLX to Java compiler has been implemented; our experience of using it has been very positive.     

嵌入式组态功能算法的构件参数优化

针对嵌入式控制策略的组态过程中存在参数繁多、查找费时、修改极其不方便的问题,提出一种经验模型。在此模型基础上对组态的参数进行排序,部分参数进行隐藏,达到提高组态开发效率的目的。基于.NET开发环境,进行构件参数优化实验,实验证明了该方法对于优化构件参数的可行性与有效性。     

The effects of visualization format and spatial ability on learning star motions

The purpose of this study was to investigate not only the effectiveness of dynamic versus static visualizations on learning star motions but also the influence of students' spatial abilities with these two types of visualizations on their learning. We assigned 155 fifth-grade students to either a dynamic or a static condition. We used a science achievement test to measure student learning outcomes by assessing knowledge acquisition. We classified students as having either a low or high spatial ability based on their test scores for primary mental abilities, specifically spatial relations. The results showed that dynamic visualizations were more effective than static visualizations for learning complex concepts involving star motions. Furthermore, learners' spatial abilities had a positive effect on their learning outcomes but did not moderate the effectiveness of dynamic versus static visualizations for learning in this domain. Our findings suggest that when designing instructional materials, the dynamic properties of visualizations should be aligned with the dynamic nature of the subject matter. We conclude that students' spatial abilities are beneficial to learning, especially when they are studying a complex domain that demands spatial changes and moving processes; therefore, our findings support the importance of assessing spatial ability in learning with visualizations.     

The effects of hierarchical structure and visualization ability on computerized information retrieval

This study examined the effects of visualization ability on search time in databases with different hierarchical structures. It was designed to determine whether manipulation of the hierarchical structures of information could accommodate the needs of low‐visualization ability users. The task consisted of finding specific “target” files in each of the four different data structures that varied in depth of organization. The study found the expected effects of organizational structure and visualization ability on retrieval time from the database. It did not find any evidence of an interaction between the two variables on performance. The results suggest that individual differences in performance are the result of differences in perceptual speed and that altering the structure of the information in a database is not an effective way to accommodate to low‐visualization ability users.     

城市GML文档三维特征的快速获取与可视化

随着网络技术的发展,对城市三维数据的需求愈益增加,然而众多的城市三维数据缺乏统一的模型,使数据不能有效地进行共享与交互。开放式地理信息系统协会（Open GIS Consortium,OGC）提出了地理标记语言（Geography Markup Language,GML）,城市GML规范定义了城市空间信息模型的标准,有利于三维数据在网络上进行传输、共享。通过分析城市GML文件的结构,提出一种适合一般城市GML文件的数据结构集合,使得在采用DOM接口解析文件后,能够快速获取城市GML文件的3D信息。实验部分使用Java 3D编程显示快速获取的3D信息,证明了提出的数据结构集合的有效性。     

An atomistic geometrical model of the B-DNA configuration for DNA–radiation interaction simulations

In this paper, an atomistic geometrical model for the B-DNA configuration is explained. This model accounts for five organization levels of the DNA, up to the 30 nm chromatin fiber. However, fragments of this fiber can be used to construct the whole genome. The algorithm developed in this work is capable to determine which is the closest atom with respect to an arbitrary point in space. It can be used in any application in which a DNA geometrical model is needed, for instance, in investigations related to the effects of ionizing radiations on the human genetic material. Successful consistency checks were carried out to test the proposed model.     

Hardware-assisted feature analysis and visualization of procedurally encoded multifield volumetric data

We take a new approach to interactive visualization and feature detection of large scalar, vector, and multifield computational fluid dynamics data sets that is also well suited for meshless CFD methods. Radial basis functions (RBFs) are used to procedurally encode both scattered and irregular gridded scalar data sets. The RBF encoding creates a complete, unified, functional representation of the scalar field throughout 3D space, independent of the underlying data topology, and eliminates the need for the original data grid during visualization. The capability of commodity PC graphics hardware to accelerate the reconstruction and rendering and to perform feature detection from this functional representation is a powerful tool for visualizing procedurally encoded volumes. Our RBF encoding and GPU-accelerated reconstruction, feature detection, and visualization tool provides a flexible system for visually exploring and analyzing large, structured, scattered, and unstructured scalar, vector, and multifield data sets at interactive rates on desktop PCs.