Sinem Guven

Authoring 3D hypermedia for wearable augmented and virtual reality

Most existing authoring systems for wearable augmentedand virtual reality experiences concentrate oncreating separate media objects and embedding themwithin the users surroundings. In contrast, designingnarrative multimedia experiences for such environmentsis still largely a tedious manual task. We present an authoringtool for creating and editing 3D hypermedia narrativesthat are interwoven with a wearable computerusers surrounding environment. Our system is designedfor use by authors who are not programmers, and allowsthem to preview their results on a desktop workstation, aswell as with an augmented or virtual reality system.

Social mobile Augmented Reality for retail

Consumers are increasingly relying on web-based social content, such as product reviews, prior to making to a purchase. Recent surveys in the Retail Industry confirm that social content is indeed the #1 aid in a buying decision. Currently, accessing or adding to this valuable web-based social content repository is mostly limited to computers far removed from the site of the shopping experience itself. We present a mobile Augmented Reality application, which extends such social content from the computer monitor into the physical world through mobile phones, providing consumers with in situ information on products right when and where they need to make buying decisions.

PICASSO: Pervasive Information Chronicling, Access, Search, and Sharing for Organizations

Several researchers have pointed out and begun to demonstrate that it is now possible to digitize an entire lifetime of experiences into a pocket-sized storage device, and thus to create a rich and portable electronic chronicle of an individuals life and activities. This possibility has brought with it a host of significant challenges: How can the creation of these electronic chronicles be natural and effortless? How should these chronicles be organized? What kinds of navigation and search tools unleash the potential of the chronicled data allowing the user to receive and retrieve the information most relevant to their context at any time? How can such chronicles impact business organizations? How can people in organizations share chronicles and effectively combine chronicled data from different individuals in collaborative settings? Our research is beginning to address these issues with a focus on the business organizational setting. In this paper we introduce PICASSO, our work on pervasive chronicle creation and exploitation in enterprise applications. PICASSO enables the capture of rich user context (including PC/PDA interactions, audio, video, images, and location) and provides tools that enable users to search, navigate, share, and merge personal events, both from desktop computers and from mobile devices

Interaction Techniques for Exploring Historic Sites through Situated Media

We present a set of augmented reality and virtual reality interaction techniques that enable mobile users to visualize and interact virtually with representations of past events. These approaches use historic photographic imagery registered with real and virtual 3D objects to depict events in situ, and to provide interactive timelines. We demonstrate our techniques through examples developed for an important landmark, the Cathedral of St. John the Divine.

A hypermedia authoring tool for augmented and virtual reality

Most existing hypermedia authoring systems are intended for use on desktop computers. These systems are typically designed for the creation of 2D documents and therefore employ 2D authoring mechanisms. In contrast, authoring systems for nontraditional multimedia/hypermedia experiences for 3D virtual or augmented worlds focus mainly on creating separate media objects and embedding them within the users surroundings. As a result, linking these media objects to create 3D hypermedia is a tedious manual task. To address this issue, we present an authoring tool for creating and editing linked 3D hypermedia narratives that are interwoven with a wearable computer users surrounding environment. Our system is designed for use by authors who are not programmers, and allows them to preview their results on a desktop workstation, as well as with an augmented or virtual reality system.

Towards establishing causality between change and incident

It is common knowledge in the IT service domain that changes to the system configuration are responsible for a major portion of incidents that result in client outages. However, it is typically very difficult to establish a relationship between changes and incidents as proper documentation takes lower priority at change creation time, as well as during incident management, in order to deal with the tremendous time pressure to quickly implement changes and resolve incidents. As a result, it is often not possible to leverage historical data to perform retrospective analysis to identify any emerging trends linking changes to incidents, or to build predictive models for proactive incident prevention at change creation time. In this paper, we present an approach for establishing causality between changes and incidents through an ensemble of statistics, data classification, and natural language processing techniques. We demonstrate our approach with a real world example.

Exploring Co-presence for Next Generation Technical Support

In many technical support systems, live support agents help end-users resolve issues with computer software/hardware and appliances/gadgets in the real world. The dominant mode of communication in such systems is still the telephone, while instant messaging, video communication, and remote take-over have emerged as additional modalities in recent years. In contrast to these, 3D avatar based visual co-presence offers a unique combination of gestural interaction, shared reality, agent multitasking, and anonymity. Our paper argues that such 3D co-presence is viable in computer chat/remote help sessions, as well as real world support over camera equipped devices, offering an attractive alternative and enhancement to todays support modalities.

COACH: Cognitive analytics for change

This paper presents our initial efforts towards building a cognitive analytics framework for change management. We propose a novel predictive algorithm for change risk calculation based on historical change failures, server failures, change triggered incidents as well as expert user input. Our predictive algorithm provides significant improvement over traditional risk assessments in proactively capturing problematic changes when tested with real client account data.

Latent trait analysis for risk management of complex information technology projects

Recent years have seen a major increase in the application of predictive analytics to the service delivery domain as more and more service providers rely on such analytics for proactive risk management. At the pre-contract stage, identifying potential project risks accurately is of vital importance since it allows service providers to avoid profit erosion through proactive risk management. This paper describes a data-driven approach to project failure prediction of complex information technology (IT) projects. We introduce a novel theoretical framework of Latent Trait Analysis (LTA), whose original form was first developed in psychometrics. We take as the input questionnaire data of risk assessment reviews in the quality assurance (QA) process of IT projects before contract signing, and attempt to predict the project health in the delivery phase after contract signing. The idea is to explicitly capture the human cognitive process through LTA, and estimate the latent project failure tendency hidden behind the questionnaire answers collected by QA experts. Using real QA data of an IT service provider, we demonstrate that our approach outperforms existing approaches in project failure prediction while providing practical information on the usefulness of individual question items.

Understanding the role of sentiment analysis in contract risk classification

This paper describes a novel approach for identifying IT outsourcing contract renewal risk ahead of contract expiration by taking into account not only client satisfaction survey results (in the form of numeric scores), but also client interview transcripts (in the form of unstructured text). By using machine learning techniques, the interview transcripts are automatically processed to identify important topics of interest along with an associated sentiment for each topic. The output of the sentiment analysis is then used as an input (in addition to client satisfaction survey scores) to classify contract renewal risk. We show that, by using sentiment analysis to transform unstructured textual information into structured input, the classification accuracy of non-renewing contracts, in particular, is substantially enhanced. Moreover, the topics with negative sentiments can shed light on the root causes of problems leading to contract non-renewal.