Websom for Textual Data Mining

New methods that are user-friendly and efficient are needed for guidanceamong the masses of textual information available in the Internet and theWorld Wide Web. We have developed a method and a tool called the WEBSOMwhich utilizes the self-organizing map algorithm (SOM) for organizing largecollections of text documents onto visual document maps. The approach toprocessing text is statistically oriented, computationally feasible, andscalable – over a million text documents have been ordered on a single map.In the article we consider different kinds of information needs and tasksregarding organizing, visualizing, searching, categorizing and filteringtextual data. Furthermore, we discuss and illustrate with examples howdocument maps can aid in these situations. An example is presented wherea document map is utilized as a tool for visualizing and filtering a stream ofincoming electronic mail messages.     

Information provision for challenging markets: The case of the accessibility requiring market in the context of tourism

The paper investigates the requirements of users with disabilities and the implications that these tourists have for developing accessible tourism information systems. A series of focus groups and interviews revealed the informational needs of people with disabilities, as well as the relevant technical difficulties involved in addressing these needs. The results indicated that the indispensable requirements include the following: (1) the veto or absolutely minimal prerequisites principle; (2) an indication of holistic accessibility paths; and (3) door-to-door access maps. The technical challenges identified focus on interoperability, content integration and personalization. The paper concludes by demonstrating how the tourism industry can overcome these challenges and address disabled travelers’ needs.     

Combining national forest inventory field plots and remote sensing data for forest databases

Information about forest cover is needed by all of the nine societal benefit areas identified by the Group of Earth Observation (GEO). In particular, the biodiversity and ecosystem areas need information on landscape composition, structure of forests, species richness, as well as their changes. Field sample plots from National Forest Inventories (NFI) are, in combination with satellite data, a tremendous resource for fulfilling these information needs. NFIs have a history of almost 100 years and have developed in parallel in several countries. For example, the NFIs in Finland and Sweden measure annually more than 10,000 field plots with approximately 200 variables per plot. The inventories are designed for five-year rotations. In Finland nationwide forest cover maps have been produced operationally since 1990 by using the k-NN algorithm to combine satellite data, field sample plot information, and other georeferenced digital data. A similar k-NN database has also been created for Sweden. The potentials of NFIs to fulfil diverse information needs are currently analyzed also in the COST Action E43 project of the European Union. In this article, we provide a review of how NFI field plot information has been used for parameterization of image data in Sweden and Finland, including pre-processing steps like haze correction, slope correction, and the optimization of the estimation variables. Furthermore, we review how the produced small-area statistics and forest cover data have been used in forestry, including forest biodiversity monitoring and habitat modelling. We also show how remote sensing data can be used for post-stratification to derive the sample plot based estimates, which cannot be directly estimated from the spectral data.     

Computer aided generation of stylized maps

Geographic maps have existed from early stages of human civilization. Various styles of visualizing the geographic information have evolved depending on the nature of information and the technology available for visualization. This has led to innumerable map styles. In this work we develop a technique to create maps by combining two‐dimensional and three‐dimensional information such that the resulting maps are both functional and aesthetically appealing. Our technique requires geographical information in vector form and aerial images as inputs. We use computer vision based approaches and user defined inputs to augment the vector data with information that is required to create stylized maps. We define procedural graphics methods to generate a range of geographic elements that can be composed together into a stylized map. We demonstrate our technique by generating example maps of a region in Las Vegas. Copyright © 2007 John Wiley & Sons, Ltd.     

COPERNICUS: Context‐Preserving Engine for Route Navigation with Interactive User‐modifiable Scaling

In this paper, we present an automated system for generating context‐preserving route maps that depict navigation routes as a path between nodes and edges inside a topographic network. Our application identifies relevant context information to support navigation and orientation, and generates customizable route maps according to design principles that communicate all relevant context information clearly visible on one single page. Interactive scaling allows seamless transition between the original undistorted map and our new map design, and supports user‐specified scaling of regions of interest to create personalized driving directions according to the drivers needs.     

Interactivity Improves Usability of Geographic Maps for Visually Impaired People

Tactile relief maps are used by visually impaired people to acquire mental representation of space, but they retain important limitations (limited amount of information, braille text, etc.). Interactive maps may overcome these limitations. However, usability of these two types of maps has never been compared. It is then unknown whether interactive maps are equivalent or even better solutions than traditional raised-line maps. This study presents a comparison of usability of a classical raised-line map versus an interactive map composed of a multitouch screen, a raised-line overlay, and audio output. Both maps were tested by 24 blind participants. We measured usability as efficiency, effectiveness, and satisfaction. Our results show that replacing braille with simple audio-tactile interaction significantly improved efficiency and user satisfaction. Effectiveness was not related to the map type but depended on users’ characteristics as well as the category of assessed spatial knowledge. Long-term evaluation of acquired spatial information revealed that maps, whether interactive or not, are useful to build robust survey-type mental representations in blind users. Altogether, these results are encouraging as they show that interactive maps are a good solution for improving map exploration and cognitive mapping in visually impaired people.     

Hybrid transformation for indexing and searching web documents in the cartographic paradigm

As information becomes available on the World Wide Web in larger quantities and in more disparate formats and media, adequate search engines and portal services providing search and filtering modalities tailored to the needs of the various communities of users become essential components of the global information infrastructure. Global-Atlas is a geographical search engine leveraging the cartographic paradigm for the indexing and searching of World Wide Web documents. Documents are indexed according to their geographical footprint, i.e. the bounding box of the geographical region to which they are related. Documents are searched by interactively drawing bounding boxes on maps. The effectiveness of Global-Atlas depends on the capability to quickly and to accurately index documents and maps. Maps, however, come in a variety of unspecified coordinate systems and projections. In this paper, we evaluate various surface-fitting techniques for the calibration of maps and devise an original hybrid calibration method from the empirical results obtained.     

Towards adaptive maps

A “standard” map provides a simplified representation of the real world but is not able to adapt to the needs of different users having different preferences. On the contrary, adaptive maps are aimed at representing the world as seen through the eyes of the user depicting the suitability/difficulty of the paths between points of interest according to the user's preferences. Adaptive maps consider, simultaneously, multiple attributes like travel time, distance, slopes, etc. In this paper, a model for adaptive maps is presented. A generation and a visualization methods are proposed. To illustrate the results, five different adaptive maps are generated and visualized considering different attributes and preferences.     

What a machine should know about philosophical problems?

This paper maps out some of the few remaining challenges to artificial intelligence from the point of view of philosophy and fuzzy logic. Certain key ideas of Lotfi Zadeh are used as a point of reference. Human reasoning is a complex procedure which is able to handle such problems as the counterfactual truth and the supervenience relation, which are difficult to explain in terms of the classical logical theory. To achieve this, one needs to understand them in a more natural manner than the standard positivistic logic is able to do. Next some examples taken from ethical theory are discussed, such as the fact/value-distinction and supererogation. These provide typically hard cases to the positivist methodology, as its representatives have always admitted. The results are applied to the philosophical problems of robotics, especially to the notion of a Cyborg on the information web. A Cyborg on the Web should be able to combine human-like reasoning with unlimited information processing.     

Application of self-organising maps for data mining with incomplete data sets

Self-organising maps (SOM) have become a commonly-used cluster analysis technique in data mining. However, SOM are not able to process incomplete data. To build more capability of data mining for SOM, this study proposes an SOM-based fuzzy map model for data mining with incomplete data sets. Using this model, incomplete data are translated into fuzzy data, and are used to generate fuzzy observations. These fuzzy observations, along with observations without missing values, are then used to train the SOM to generate fuzzy maps. Compared with the standard SOM approach, fuzzy maps generated by the proposed method can provide more information for knowledge discovery.     

Multimedia displays for conceptual discovery: information seeking with strand maps

This article explores the use of a multimedia search interface for digital libraries based on strand maps developed by the American Association for the Advancement of Science. As semantic-spatial displays, strand maps provide a visual organization of relevant conceptual information that may promote the use of science content during digital library use. A study was conducted to compare users' cognitive processes during information seeking tasks when using a multimedia strand maps interface, versus the textual search interface currently implemented in the Digital Library for Earth System Education. Quantitative and qualitative data from think-aloud protocols revealed that students were more likely to engage with science content (e.g., analyzing the relevance of science concepts with regard to task needs) during search when using the strand maps interface compared to those using textual searching. In contrast, students using a textual search interface engaged more frequently with surface-level information (e.g., the type of a resource regardless of its science content) during search and retrieval. As a multimedia search interface for digital libraries, strand maps appear to be promising tools to promote conceptual discovery and learning through content-based processes that promote learner engagement with relevant science knowledge.     

Super-resolution land-cover mapping using multiple sub-pixel shifted remotely sensed images

Super-resolution land-cover mapping is a promising technology for prediction of the spatial distribution of each land-cover class at the sub-pixel scale. This distribution is often determined based on the principle of spatial dependence and from land-cover fraction images derived with soft classification technology. However, the resulting super-resolution land-cover maps often have uncertainty as no information about sub-pixel land-cover patterns within the low-resolution pixels is used in the model. Accuracy can be improved by incorporating supplemental datasets to provide more land-cover information at the sub-pixel scale; but the effectiveness of this is limited by the availability and quality of these additional datasets. In this paper, a novel super-resolution land-cover mapping technology is proposed, which uses multiple sub-pixel shifted remotely sensed images taken by observation satellites. These satellites take images over the same area once every several days, but the images are not identical because of slight orbit translations. Low-resolution pixels in these remotely sensed images therefore contain different land-cover fractions that can provide useful information for super-resolution land-cover mapping. We have constructed a Hopfield Neural Network (HNN) model to solve it. Maximum spatial dependence is the goal of the proposed model, and the fraction maps of all images are constraints added to the energy function of HNN. The model was applied to synthetic artificial images as well as to a real degraded QuickBird image. The output maps derived from different numbers of images at different zoom factors were compared visually and quantitatively to the super-resolution map generated from a single image. The resulting land-cover maps with multiple remotely sensed images were more accurate than was the single image map. The use of multiple remotely sensed images is therefore a promising method for decreasing the uncertainty of super-resolution land-cover mapping. Moreover, remotely sensed images with similar spatial resolution from different satellite platforms can be used together, allowing a fusion of information obtained from remotely sensed imagery.     

Geographic Information Systems: An Emerging Component of Decision Support

Quietly, yet productively, geographic information systems(GISs) have introduced new decision support capabilities in organizations whose demands for spatially oriented data bases are important. These systems will have a substantive impact in selected industries, government units, and businesses by integrating maps with spatially oriented data base information and enabling decision makers (i.e., IS and senior managers) to access forms of information not previously available.     

Conveying identity with mobile content

A series of mobile phone prototypes, called The Swarm, have been developed in response to the user needs identified in a 3-year empirical study of young people’s use of mobile phones. The prototypes take cues from user led innovation and provide multiple avatars that allow individuals to define and manage their own virtual identity. This paper briefly maps the evolution of the prototypes and then describes how the pre-defined, colour-coded avatars in the latest version are being given greater context and personalization through the use of digital images. This not only gives ‘serendipity a nudge’ by allowing groups to come together more easily, but also provides contextual information that can reduce gratuitous contact.     

Creating realistic map-like visualisations: Results from user studies

Maps have traditionally been used for displaying geographical information. However, apart from this obvious purpose, the metaphor of maps has been applied to other uses, such as information visualisation and novel user interfaces, since the map metaphor is easy-to-understand and allows users to explore data intuitively. There are several methods for creating these map-like visualisations and user interfaces, but there is little understanding on how people perceive these non-geographical maps, and how to make the visualisation output more realistic. As such, we aim to find preliminary answers on these issues by conducting user studies with a series of map-like visualisations. In this paper, we report on the results of the studies and reveal the factors that have an impact on the human perception of visualisations that are designed to resemble geographic maps. Based on these results, we propose design suggestions for building realistic map-like visualisations.     

Fostering group norm development and orientation while creating awareness contents for improving net-based collaborative problem solving

Empirical studies have demonstrated that being aware of the knowledge structures and of the underlying information of other group members improves computer-supported collaborative problem solving. While such studies used pre-made individual concept maps as awareness tools, empirical studies that used individual concept maps created by the group members themselves have not shown an advantage for group performance. An assumed reason is that individual members’ concept maps differ too much structurally so that using them would need a lot of effort. This experimental study compares 20 triads whose members can observe the map creation process of the other members in their group with 20 triads without this possibility. The results demonstrated that access to the map creation process of the other group members while building one’s own concept map led to a group norm of how to create such a map. As a result, group members created more structurally similar maps, which led, as in prior studies with pre-made maps, to improved group performance.     

基于ArcGIS与Illustrator的长城专题影像图制作

长城专题影像图作为长城测量项目重要的成果之一,是以航空遥感影像为基础,负载大量现势性强的基础空间数据和长城专题信息数据,从而可以满足长城修复、保护等各项工作。通过分析当前专题图制作的两种主要技术,提出基于地理信息系统软件（ArcGIS）和专业绘图软件（Illustrator）联合实现专题图制作的方法,以设计和制作长城专题影像图为例,详细介绍了该模式下专题影像图的整体设计、数据组织及处理、图廓整饰等。通过应用说明：这种混合制图方式不仅可提高绘图精度、丰富地图内容表示等方面具有明显优势,而且能提高绘图效率、降低工作成本,在专题地图制作方面具有广阔的应用前景。     

A Graphical Model for Context-Aware Visual Content Recommendation

Existing recommender systems provide an elegant solution to the information overload in current digital libraries such as the Internet archive. Nowadays, the sensors that capture the user's contextual information such as the location and time are become available and have raised a need to personalize recommendations for each user according to his/her changing needs in different contexts. In addition, visual documents have richer textual and visual information that was not exploited by existing recommender systems. In this paper, we propose a new framework for context-aware recommendation of visual documents by modeling the user needs, the context and also the visual document collection together in a unified model. We address also the user's need for diversified recommendations. Our pilot study showed the merits of our approach in content based image retrieval.     

An Optimization Approach to Improving Collections of Shape Maps

Finding an informative, structure‐preserving map between two shapes has been a long‐standing problem in geometry processing, involving a variety of solution approaches and applications. However, in many cases, we are given not only two related shapes, but a collection of them, and considering each pairwise map independently does not take full advantage of all existing information. For example, a notorious problem with computing shape maps is the ambiguity introduced by the symmetry problem — for two similar shapes which have reflectional symmetry there exist two maps which are equally favorable, and no intrinsic mapping algorithm can distinguish between them based on these two shapes alone. Another prominent issue with shape mapping algorithms is their relative sensitivity to how “similar” two shapes are — good maps are much easier to obtain when shapes are very similar. Given the context of additional shape maps connecting our collection, we propose to add the constraint of global map consistency, requiring that any composition of maps between two shapes should be independent of the path chosen in the network. This requirement can help us choose among the equally good symmetric alternatives, or help us replace a “bad” pairwise map with the composition of a few “good” maps between shapes that in some sense interpolate the original ones. We show how, given a collection of pairwise shape maps, to define an optimization problem whose output is a set of alternative maps, compositions of those given, which are consistent, and individually at times much better than the original. Our method is general, and can work on any collection of shapes, as long as a seed set of good pairwise maps is provided. We demonstrate the effectiveness of our method for improving maps generated by state‐of‐the‐art mapping methods on various shape databases.