Abstract. Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from such a perspective. This viewpoint is under-emphasized in the recommender systems literature. We therefore take a connection-oriented perspective toward recommender systems research. We posit that recommendation has an inherently social element and is ultimately intended to connect people either directly as a result of explicit user modeling or indirectly through the discovery of relationships implicit in extant data. Thus, recommender systems are characterized by how they model users to bring people together: explicitly or implicitly. Finally, user modeling and the connection-centric viewpoint raise broadening and social issues—such as evaluation, targeting, and privacy and trust—which we also briefly address. Keywords: recommendation, recommender systems, small-worlds, social networks, user modeling “What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”

Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations -- a theory for representing and reasoning about dialogs based on partial input. It supports multiple interaction interfaces, and offers sessioning, caching, and co-ordination functions through the use of an interaction manager. Two case studies are presented to illustrate the promise of this approach.

We describe four usability-enhancing interfaces to CITIDEL aimed at improving the user experience and supporting personalized information access by targeted communities. These comprise: a multimodal interaction facility with capability for out-of-turn input, interactive visualizations for exploratory analysis, a translation center exposing multilingual interfaces, as well as traditional usability enhancements. Pilot studies demonstrate the resulting improvements in quality, as measured across a number of metrics. Categories and Subject Descriptors H.5.2 [Information Interfaces and Presentation]: User

Personalization constitutes the mechanisms necessary to automatically customize information content, structure, and presentation to the end-user to reduce information overload. Unlike traditional approaches to personalization, the central theme of our approach is to model a website as a program and conduct website transformation for personalization by program transformation (e.g., partial evaluation, program slicing). The goal of this paper is study personalization through a program transformation lens, and develop a formal model, based on program transformations, for personalized interaction with hierarchical hypermedia. The specific research issues addressed involve identifying and developing program representations and transformations suitable for classes of hierarchical hypermedia, and providing supplemental interactions for improving the personalized experience. The primary form of personalization discussed is out-of-turn interaction – a technique which empowers a user navigating a hierarchical website to postpone clicking on any of the hyperlinks presented on the current page and, instead, communicate the

The rise of ubiquitous computing devices has provided the catalyst for the next generation World Wide Web, one that shifts the focus from the desktop computer to mobile devices such as cell phones and PDAs, in an ever increasing range of modalities. Web interaction management in this setting must contend with a plethora of interaction interfaces and a diverse range of content types in addition to helping realize the full potential of multimodality (i.e., supporting flexible and personalized interactions between humans and sites). This thesis presents WS://IM, a new software framework for web interaction management that is capable of supporting multimodal interactions. In addition to presenting a loosely bundled, factorized architecture that supports hyperlink interaction, WS://IM has the unique facilitation for out-of-turn interaction. Out-of-turn interaction is a novel technique that helps realize mixed-initiative interactions between humans and Web sites. Design methodology, implementation details, and exposition through three implemented case studies are provided. For My parents and grandparents. Your guidance, support, and encouragement have made all the difference in the world.

Multimodal interfaces are becoming increasingly important with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. This thesis investigates systems support for web browsing in a multimodal interface. Specifically, we outline the design and implementation of a software framework that integrates hyperlink and voice interaction. This enables the user to engage in out-of-turn interactions to personalize access at an information site. For the developer, the framework enables the creation of sites that adapt to the needs of users, yet permits fine-grained control over what interactions to support. Design methodology, implementation details, and two case studies are presented.

Abstract. Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from such a perspective. This viewpoint is underemphasized in the recommender systems literature. We therefore take a connection-oriented viewpoint toward recommender systems research. We posit that recommendation has an inherently social element and is ultimately intended to connect people either directly as a result of explicit user modeling or indirectly through the discovery of relationships implicit in extant data. Thus, recommender systems are characterized by how they model users to bring people together: explicitly or implicitly. Finally, user modeling and the connection-centric viewpoint raise broadening and social issues—such as evaluation, targeting, and privacy and trust—which we also briefly address.

My primary area of research interest is information personalization. Personalization involves the mechanisms and technologies necessary to customize information access to the end-user. My view of personalization is oriented toward personalizing interaction. The thesis of my research is that modeling information-seeking dialogs explicitly in a representation of interaction, and studying how partial information can be harnessed in the representation to direct the flow of the dialog, provides insight into and reveals opportunities for personalization. The central theme of my research is to model interactions with information systems programmatically, and use program transformation techniques for personalization. My approach to research involves a combination of modeling, implementation, and user studies. My specific research activities in this area involve: 1. investigating representations suitable for modeling interaction with different classes of hypermedia, 2. mining structural and semantic characteristics of targeted domains, 3. developing new interaction paradigms for personalized information access, and 4. identifying new program transformation techniques capable of realizing the paradigm from the modeled interaction. Once a (representation, transformation) pair is developed, I 5. compute evaluation metrics to assess representational adequacy, 6. conduct user studies to evaluate the personalized interaction enabled, and 7. provide supplemental operators to improve the personalized experience. To the best of my knowledge, I am the first to approach personalized interaction from a program transformation perspective. My use of program transformations casts personalization in a formal setting, and provides both a systematic approach to designing systems and an implementation-neutral way to study software frameworks for personalization. The following is a summary of my prior work in this area categorized by the class of stakeholder to which it contributed.