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Articles 31 - 36 of 36
Full-Text Articles in Numerical Analysis and Scientific Computing
Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox
Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox
Computer Science Faculty Publications
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 …
Automatically Generating Interfaces For Personalized Interaction With Digital Libraries, Saverio Perugini, Naren Ramakrishnan, Edward A. Fox
Automatically Generating Interfaces For Personalized Interaction With Digital Libraries, Saverio Perugini, Naren Ramakrishnan, Edward A. Fox
Computer Science Faculty Publications
We present an approach to automatically generate interfaces supporting personalized interaction with digital libraries; these interfaces augment the user-DL dialog by empowering the user to (optionally) supply out-of-turn information during an interaction, flatten or restructure the dialog, and inquire about dialog options. Interfaces generated using this approach for CITIDEL are described.
The Staging Transformation Approach To Mixing Initiative, Robert Capra, Michael Narayan, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones
The Staging Transformation Approach To Mixing Initiative, Robert Capra, Michael Narayan, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones
Computer Science Faculty Publications
Mixed-initiative interaction is an important facet of many conversational interfaces, flexible planning architectures, intelligent tutoring systems, and interactive information retrieval systems. Software systems for mixed-initiative interaction must enable us to both operationalize the mixing of initiative (i.e., support the creation of practical dialogs) and to reason in real-time about how a flexible mode of interaction can be supported (e.g., from a meta-dialog standpoint). In this paper, we present the staging transformation approach to mixing initiative, where a dialog script captures the structure of the dialog and dialog control processes are realized through generous use of program transformation techniques (e.g., partial …
Personalizing Interactions With Information Systems, Saverio Perugini, Naren Ramakrishnan
Personalizing Interactions With Information Systems, Saverio Perugini, Naren Ramakrishnan
Computer Science Faculty Publications
Personalization constitutes the mechanisms and technologies necessary to customize information access to the end-user. It can be defined as the automatic adjustment of information content, structure, and presentation tailored to the individual. In this chapter, we study personalization from the viewpoint of personalizing interaction. The survey covers mechanisms for information-finding on the web, advanced information retrieval systems, dialog-based applications, and mobile access paradigms. Specific emphasis is placed on studying how users interact with an information system and how the system can encourage and foster interaction. This helps bring out the role of the personalization system as a facilitator which reconciles …
The Partial Evaluation Approach To Information Personalization, Naren Ramakrishnan, Saverio Perugini
The Partial Evaluation Approach To Information Personalization, Naren Ramakrishnan, Saverio Perugini
Computer Science Faculty Publications
Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. By reducing information overload and customizing information access, personalization systems have emerged as an important segment of the Internet economy. This paper presents a systematic modeling methodology— PIPE (‘Personalization is Partial Evaluation’) — for personalization. Personalization systems are designed and implemented in PIPE by modeling an information-seeking interaction in a programmatic representation. The representation supports the description of information-seeking activities as partial information and their subsequent realization by partial evaluation, a technique for specializing programs. We describe the modeling methodology at a …
Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan
Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan
Computer Science Faculty Publications
The NIST Guide to Available Mathematical Software (GAMS) system at http://gams.nist .gov serves as the gateway to thousands of scientific codes and modules for numerical computation. We describe the PIPE personalization facility for GAMS, whereby content from the cross-index is specialized for a user desiring software recommendations for a specific problem instance. The key idea is to (i) mine structure, and (ii) exploit it in a programmatic manner to generate personalized web pages. Our approach supports both content-based and collaborative personalization and enables information integration from multiple (and complementary) web resources. We present case studies for the domain of linear, …