Understanding novelty: how task structure and tool familiarity moderate performance

Consumers and corporate end users are regularly faced with the challenge of adapting to new technology tools and their user interfaces. Understanding the role of user experience in using these new interfaces is an important aspect of assessing and planning for how new innovations are received. Through a controlled laboratory experiment in the information retrieval domain, we find that the effect of task (web search) familiarity on performance depends on the task structure (open-ended versus closed-ended) and the degree of tool familiarity (a traditional textual list versus a novel graphical interface for presenting web search results). Our results show that task experience has a positive effect on performance when the task structure is closed-ended and the interface is familiar, and a negative effect when the task structure is open-ended and the interface is unfamiliar. This study not only adds to the literature on user experience in the context of IT use, but also has practical implications for the testing and adoption of new technologies, indicating that novices may be better, or at least an important group, for testing truly novel tools and their interfaces.     

Relevance- and interface-driven clustering for visual information retrieval

Search results of spatio-temporal data are often displayed on a map, but when the number of matching search results is large, it can be time-consuming to individually examine all results, even when using methods such as filtered search to narrow the content focus. This suggests the need to aggregate results via a clustering method. However, standard unsupervised clustering algorithms like $K$-means (i) ignore relevance scores that can help with the extraction of highly relevant clusters, and (ii) do not necessarily optimize search results for purposes of visual presentation. In this article, we address both deficiencies by framing the clustering problem for search-driven user interfaces in a novel optimization framework that (i) aims to maximize the relevance of aggregated content according to cluster-based extensions of standard information retrieval metrics and (ii) defines clusters via constraints that naturally reflect interface-driven desiderata of spatial, temporal, and keyword coherence that do not require complex ad-hoc distance metric specifications as in $K$-means. After comparatively benchmarking algorithmic variants of our proposed approach – RadiCAL – in offline experiments, we undertake a user study with 24 subjects to evaluate whether RadiCAL improves human performance on visual search tasks in comparison to $K$-means clustering and a filtered search baseline. Our results show that (a) our binary partitioning search (BPS) variant of RadiCAL is fast, near-optimal, and extracts higher-relevance clusters than $K$-means, and (b) clusters optimized via RadiCAL result in faster search task completion with higher accuracy while requiring a minimum workload leading to high effectiveness, efficiency, and user satisfaction among alternatives.     

Simulated evaluation of faceted browsing based on feature selection

In this paper we explore the limitations of facet based browsing which uses sub-needs of an information need for querying and organising the search process in video retrieval. The underlying assumption of this approach is that the search effectiveness will be enhanced if such an approach is employed for interactive video retrieval using textual and visual features. We explore the performance bounds of a faceted system by carrying out a simulated user evaluation on TRECVid data sets, and also on the logs of a prior user experiment with the system. We first present a methodology to reduce the dimensionality of features by selecting the most important ones. Then, we discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. Facets created by users are simulated by clustering video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness.     

An evaluation of semantic fisheye views for opportunistic search in an annotated image collection

Visual interfaces are potentially powerful tools for users to explore a representation of a collection and opportunistically discover information that will guide them toward relevant documents. Semantic fisheye views (SFEVs) are focus + context visualization techniques that manage visual complexity by selectively emphasizing and increasing the detail of information related to the users focus and deemphasizing or filtering less important information.In this paper we describe a prototype for visualizing an annotated image collection and an experiment to compare the effectiveness of two distinctly different SFEVs for a complex opportunistic search task. The first SFEV calculates relevance based on keyword-content similarity and the second based on conceptual relationships between images derived using WordNet. The results of the experiment suggest that semantic-guided search is significantly more effective than similarity-guided search for discovering and using domain knowledge in a collection.     

Interactive search and browsing interface for large-scale visual repositories

Due to the rapid proliferation of both user-generated and broadcasted content, the interfaces for search and browsing of visual media have become increasingly important. This paper presents a novel intuitive interactive interface for browsing of large-scale image and video collections. It visualises underlying structure of the dataset by the size and spatial relations of displayed images. In order to achieve this, images or video key-frames are initially clustered using an unsupervised graph-based clustering algorithm. By selecting images that are hierarchically laid out on the screen, user can intuitively navigate through the collection or search for specific content. The extensive experimental results based on user evaluation of photo search, browsing and selection as well as interactive video search demonstrate good usability of the presented system and improvement when compared to the standard methods for interaction with large-scale image and video collections.     

Representation of time in digital calendars: An argument for a unified,continuous and multi-granular calendar view

Digital calendars have been heavily influenced by the design of the physical calendar and have invariably adopted their grid representation of days in the month. We argue that the alternative of a continuous list representation of successive days would offer several advantages such as faster calendar search, a more natural linear view of time, a scrollable and zoomable interface and better scalability for devices of different size. This alternative, linear calendar appears to be well suited to modern touch-centric platforms with their refined support for scrolling and zooming.We tested search performance and navigation with digital calendars in a comparison of grid and list representations by employing a remote, web-based method. On their personal computers, participants performed a series of search tasks in a fictitious calendar. The results show that calendar search is faster in list view when searching for dates, between month breaks and in the next month (with and without navigation). Searching for days is faster in grid view, however, highlighting days in list view eliminates this difference. The results indicate substantial promise for the list view digital calendar and we describe a high fidelity rendering of the user interface for a digital calendar with a list view.     

GeneShelf: A Web-based Visual Interface for Large Gene Expression Time-Series Data Repositories

A widespread use of high-throughput gene expression analysis techniques enabled the biomedical research community to share a huge body of gene expression datasets in many public databases on the web. However, current gene expression data repositories provide static representations of the data and support limited interactions. This hinders biologists from effectively exploring shared gene expression datasets. Responding to the growing need for better interfaces to improve the utility of the public datasets, we have designed and developed a new web-based visual interface entitled GeneShelf (http://bioinformatics.cnmcresearch.org/GeneShelf). It builds upon a zoomable grid display to represent two categorical dimensions. It also incorporates an augmented timeline with expandable time points that better shows multiple data values for the focused time point by embedding bar charts. We applied GeneShelf to one of the largest microarray datasets generated to study the progression and recovery process of injuries at the spinal cord of mice and rats. We present a case study and a preliminary qualitative user study with biologists to show the utility and usability of GeneShelf.     

Using visual spatial search interface for WWW applications

Most Internet search engines are keyword-based. They are not efficient for the queries where geographical location is important, such as finding hotels within an area or close to a place of interest. A natural interface for spatial searching is a map, which can be used not only to display locations of search results but also to assist forming search conditions. A map-based search engine requires a well-designed visual interface that is intuitive to use yet flexible and expressive enough to support various types of spatial queries as well as aspatial queries. Similar to hyperlinks for text and images in an HTML page, spatial objects in a map should support hyperlinks. Such an interface needs to be scalable with the size of the geographical regions and the number of websites it covers. In spite of handling typically a very large amount of spatial data, a map-based search interface should meet the expectation of fast response time for interactive applications. In this paper we discuss general requirements and the design for a new map-based web search interface, focusing on integration with the WWW and visual spatial query interface. A number of current and future research issues are discussed, and a prototype for the University of Queensland is presented.     

Interactive ads recommendation with contextual search on product topic space

The rapid popularization of various online media services have attracted large amounts of consumers and shown us a large potential market of video advertising. In this paper, we propose interactive service recommendation based on ad concept hierarchy and contextual search. Instead of traditional ODP (Open Directory Project) based approach, we built a ad domain based concept hierarchy to make the most of the product details over the e-commerce sites. Firstly, we capture the summarization images related to the advertising product in the video content and search visually similar product images from the built product image database. Then, we aggregate the visual tags and textual tags with K-line clustering. Finally, we map them to the product concept space and make keywords suggestion, and users can interactively select keyframes or keywords to personalize their intentions by textual re-search. Experiments and comparison show that the system can accurately provide effective advertising suggestions.     

基于频繁词义序列的检索结果聚类算法研究

目前大多搜索引擎结果聚类算法针对用户查询生成的网页摘要进行聚类,由于网页摘要较短且质量良莠不齐,聚类效果难以保证。提出了一种基于频繁词义序列的检索结果聚类算法,利用WordNet结合句法和语义特征对搜索结果构建聚类及标签。不像传统的基于向量空间模型的聚类算法,考虑了词语在文档中的序列模式。算法首先对文本进行预处理,生成压缩文档以降低文本数据维度,构建广义后缀树,挖掘出最大频繁项集,然后获取频繁词义序列。从文档中获取的有序频繁项集可以更好地反映文档的主题,把相同主题的搜索结果聚类在一起,与用户查询相关度高的优先排序。实验表明,该算法可以获得与查询相关的高质量聚类及基于语义的聚类标签,具有更高的聚类准确度和更高的运行效率,并且可扩展性良好。     

Evaluation of Methods for the Determination of Factors Inducing Fatigue in Man at Work

The aim of the study was to determine the influence of textual feedback on the content and outcome of spoken interaction with a natural language dialogue system. More specifically, the assumption that textual feedback could disrupt spoken interaction was tested in a human–computer dialogue situation. In total, 48 adult participants, familiar with the system, had to find restaurants based on simple or difficult scenarios using a real natural language service system in a speech-only (phone), speech plus textual dialogue history (multimodal) or text-only (web) modality. The linguistic contents of the dialogues differed as a function of modality, but were similar whether the textual feedback was included in the spoken condition or not. These results add to burgeoning research efforts on multimodal feedback, in suggesting that textual feedback may have little or no detrimental effect on information searching with a real system.

Statement of Relevance: The results suggest that adding textual feedback to interfaces for human–computer dialogue could enhance spoken interaction rather than create interference. The literature currently suggests that adding textual feedback to tasks that depend on the visual sense benefits human–computer interaction. The addition of textual output when the spoken modality is heavily taxed by the task was investigated.     

Visual search for grouped versus ungrouped icons in a computer interface

The paradigm of visual search was used to investigate how participants looked for a target file among distracter files in an icon-based computer interface. The purpose of these experiments was to study the effect of icons and spatial grouping on scanning speed. Does spatial grouping of identical icons increase the scanning speed? Do icons themselves speed up the search for a target file when compared with a condition in which the files are indicated with mere textual labels? Our results showed that both the presence of icons and their grouping had a significant positive effect on the scanning speed. Potential applications of this research include the design of graphics-based interfaces, such as the effective arrangement of icons in an interface.     

网络信息检索中相关反馈技术的Java实现

介绍了相关反馈技术的基本思想,设计了网络信息检索中相关反馈系统的功能与结构,探索如何在现有的公共网络搜索引擎基础上,利用Java语言实现具有相关反馈功能的搜索引擎接口.     

基于超链接信息的搜索引擎检索结果聚类方法研究

针对目前搜索引擎返回候选信息过多从而使用户不能准确查找与主题有关结果的问题,提出了基于超链接信息的搜索引擎检索结果聚类方法,通过对网页的超链接锚文档和网页文档内容挖掘,最终将网页聚成不同的子类别。这种方法在依据网页内容进行聚类的同时,充分利用了Web结构和超链接信息,比传统的结构挖掘方法更能体现网站文档的内容特点,从而提高了聚类的准确性。     

Visual and textual consistency checking tools for graphical userinterfaces

Designing user interfaces with consistent visual and textual properties is difficult. To demonstrate the harmful effects of inconsistency, we conducted an experiment with 60 subjects. Inconsistent interface terminology slowed user performance by 10 to 25 percent. Unfortunately, contemporary software tools provide only modest support for consistency control. Therefore, we developed SHERLOCK, a family of consistency analysis tools, which evaluates visual and textual properties of user interfaces. It provides graphical analysis tools such as a dialog box summary table that presents a compact overview of visual properties of all dialog boxes. SHERLOCK provides terminology analysis tools including an interface concordance, an interface spellchecker, and terminology baskets to check for inconsistent use of familiar groups of terms. Button analysis tools include a button concordance and a button layout table to detect variant capitalization, distinct typefaces, distinct colors, variant button sizes, and inconsistent button placements. We describe the design, software architecture, and the use of SHERLOCK. We tested SHERLOCK with four commercial prototypes. The outputs, analysis, and feedback from designers of the applications are presented     

平行坐标轴动态排列的地理空间多维数据可视分析

目的 平行坐标是经典的多维数据可视化方法,但在用于地理空间多维数据分析时,往往存在空间位置信息缺失和空间关联分析不确定等问题。对此,本文设计了一种有效关联平行坐标和地图的地理空间多维数据可视分析方法。方法 根据多维属性信息对地理空间位置进行聚类分析,引入Voronoi图和颜色明暗映射对地理空间各类区域进行显著标识,利用平行坐标呈现地理空间多维属性信息,引入互信息度量地理空间聚类与属性类别的相关性,动态地确定平行坐标轴排列顺序,进一步计算属性轴与地图之间数据线的绑定位置,对数据线的布局进行优化处理,降低地图与平行坐标系间数据线分布的紊乱程度。结果 有效集成上述可视化设计及数据分析方法,设计与实现一种基于平行坐标轴动态排列的地理空间多维数据可视化分析系统,提供便捷的用户交互模式,通过2组具有明显地理空间多维属性特征的数据进行测试,验证了本文可视分析方法的有效性和实用性。结论 本文提出的可视分析方法和工具可以帮助用户快速分析地理空间多维属性存在的空间分布特征及其关联模式,为地理空间多维数据的探索提供了有效手段。     

Automatically Determining Semantics for World Wide Web Multimedia Information Retrieval

Search engines are useful because they allow the user to find information of interest from the World Wide Web (WWW). However, most of the popular search engines today are textual; they do not allow the user to find images from the web. For effective retrieval, determining the semantics of the images is essential. In this paper, we describe the problems in determining the semantics of images on the WWW and the approach of AMORE, a WWW search engine that we have developed. AMORE's techniques can be extended to other media like audio and video. We explain how we assign keywords to the images based on HTML pages and the method to determine similar images based on the assigned text. We also discuss some statistics showing the effectiveness of our technique. Finally, we present the visual interface of AMORE with the help of several retrieval scenarios.     

The effects of zoomable user interfaces and user age in searching for a target with a mouse on a two-dimensional information space

A zoomable user interface (ZUI) is a useful function to help users deal with large information spaces displayed within a screen. Although used in many applications, ZUIs have not been sufficiently studied in terms of usability. Usability problems may be more crucial for older people than younger ones. The objective of this study is to examine the effects of a combination of two zoom factors (three zoom focus methods: original-center, re-center, and aiming-point; and two zoom scales: +100% and +400%) for two age groups (younger and older adults) on mouse-based information searching tasks in a map-type two-dimensional information space. Twenty four volunteers (twelve users per age group) participated in the experiments by answering a pair of questions about fifty movie information topics. Task completion time, number of operations, and number of errors were selected as performance measures, and a subjective assessment of satisfaction was collected. Older adults used the tested ZUIs less efficiently and precisely than younger adults. The effects of zoom focus methods vary with zoom scale levels regardless of the age groups. The participants also preferred using the aiming-point focus regardless of zoom scale and using the re-center focus with the +400% scale. We discuss potential implications of the age-related performance differences and the effects of ZUI functions, and suggest some ZUI design guidelines in conclusion. We expect that the findings can be used as basic resources in designing various web services and applications for older computer users.

Relevance to industry

Given that a zoomable user interface is widely used in basic geographic information systems, web services, and various applications, using a selective-focus method such as the aiming-point focus can improve computer users’ usability; in particular, the zooming functions will greatly help older people to explore large information spaces quickly and easily.     

Biases on visual warnings during multiple target visual searches on mine monitoring interface

With the continuous development of human–computer interaction, some industrial monitoring systems have gradually evolved from a single monitoring device to a comprehensive monitoring system platform, and multi-objective visual search is particularly important in the field of industrial monitoring. This study investigates the effect of conceptual and perceptual biases on similarity bias in multiple target visual searches and proposes relevant design strategies that can be applied to warning interfaces. The results of two experiments show that the effect of the similarity bias is due to the combined effects of conceptual and perceptual similarities, and on this basis, we propose a design strategy for the interface of a gas extraction monitoring system used in mines in a third experiment. An existing interface to monitor gas extraction and a proposed interface with modifications made to the existing interface are evaluated. The results confirm that the modified interface effectively improves visual search performance during multiple target visual searches. The research findings are important for reducing cognitive decision errors during related monitoring work and ensuring the performance of the mine gas safety monitoring system interfaces. The findings can also guide the designing of visual warning elements of different targets for other monitoring interfaces.