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Proceedings of the 15th ACM international conference on Information and knowledge management, With ever growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives to their customers. Toward this end, existing approaches have almost solely focussed on the individual behaviour of customers. Call graphs, that is, graphs induced by people calling each other, can allow telecom operators to better understand the interaction behaviour of their customers, and potentially provide major insights for designing effective incentives. In this paper, we use the Call Detail Records of a mobile operator from four geographically disparate regions to construct call graphs, and analyse their structural properties. Our findings provide business insights and help devise strategies for Mobile Telecom operators. Another goal of this paper is to identify the shape of such graphs. In order to do so, we extend the well-known reachability analysis approach with some of our own techniques to reveal the shape of such massive graphs. Based on our analysis, we introduce the Treasure-Hunt model to describe the shape of mobile call graphs. The proposed techniques are general enough for analysing any large graph. Finally, how well the proposed model captures the shape of other mobile call graphs needs to be the subject of future studies.

Advanced Multimedia Oriented Retrieval Engine (AMORE) [2] is a World-Wide Web image retrieval engine integrating several techniques to facilitate effective retrieval of images from the Web. With the explosive growth of information that is available through the WWW, it is becoming increasingly difficult for the users to find the information of interest. Therefore, search engines are becoming very popular and useful. However, most of the popular search engines today are textual. Although most Web pages have images, the current image search engines on the WWW are primitive.For traditional text retrieval the only way to search for relevant documents is by specifying keywords. However, for multimedia retrieval it is essential that the user is provided with various options for retrieving the target image. AMORE allows the user to retrieve images of interest using various techniques.The effectiveness of an information retrieval engine is also dependent on the user interface to show the retrieved images. In AMORE, the retrieved images are shown using thumbnails. Like traditional WWW search engines the user can browse through pages of results. We also allow the user to click on an interesting thumbnail and retrieve similar images. This visual navigation strategy is helpful in quickly retrieving the target images. To help the user if many images are retrieved we have also developed a Query Result Visualization Environment. This interface allows the search results to be organized in various ways. We believe that the integration of information retrieval with visualization is helpful for the user's retrieval tasks.

In this paper, we present the idea of object-based navigation. Object-based navigation is a navigation style based upon the characteristics at the object level, that is contents of the objects and the relationship among the objects. With objectbased navigation, users can specify a set of objects and their relationship. The system creates queries from the users’ input and determines links dynamically based on matching between this query and indices. Various kinds of attributes including conceptual and media-based characteristics are integrated at the object level. We introduced this navigation style into the content-oriented integration environment to manage a large quantity of multimedia data. COIR (Content Oriented Information Retrieval tool), an object-based navigation tool for content-oriented integrated hypermedia systems is introduced. We show how this tool works in indexing and navigating multimedia data. Using COIR, we have developed the directory service systems for the World-Wide Web and have evaluated the navigational capability and extensibility of our tools. Multimedia search engines including COIR, extract the characteristics from multimedia data at any web site automatically. Extracted characteristics are connected with each other semiautomatically and utilized in the navigational stage. With this system, users can execute the navigation based on the relationship between objects as well as the contents of the objects. In this paper, we present how the COIR tool increases the navigational capabilities for hypermedia systems.

Our work concerns visualizing the information space of hypermedia systems using multiple hierarchical views. Although overview diagrams are useful for helping the user to navigate in a hypermedia system, for any real-world system they become too complicated and large to be really useful. This is because these diagrams represent complex network structures which are very difficult to visualize and comprehend. On the other hand, effective visualizations of hierarchies have been developed. Our strategy is to provide the user with different hierarchies, each giving a different perspective to the underlying information space, to help the user better comprehend the information. We propose an algorithm based on content and structural analysis to form hierarchies from hypermedia networks. The algorithm is automatic but can be guided by the user. The multiple hierarchies can be visualized in various ways. We give examples of the implementation of the algorithm on two hypermedia systems.

This paper talks about clustering related nodes of an overview diagram to reduce its complexity and size. This is because although overview diagrams are useful for helping the user to navigate in a hypermedia system, for any real-world system these become too complicated and large to be really useful. Both structure-based and content-based clustering are used. Since the nodes can be related to each other in different ways, depending on the situation different clustered views will be useful. Hence, it should be possible to interactively specify the clustering conditions and examine the resulting views. We present efficient clustering algorithms which can cluster the information space in real-time. We talk about the Navigational View Builder, a tool that allows the interactive development of overview diagrams. Finally, we propose a 3-dimensional approach for visualizing these abstracted views.