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Articles 31 - 41 of 41
Full-Text Articles in OS and Networks
Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini
Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini
Computer Science Faculty Publications
We demonstrate the use of two user interfaces for interacting with web hierarchies. One uses the dependencies underlying a hierarchy to perform real-time query expansion and, in this way, acts as an in situ feedback mechanism. The other enables the user to cascade the output from one interaction to the input of another, and so on, and, in this way, supports procedural information-seeking tasks without disrupting the flow of interaction.
On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov
On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov
Computer Science Faculty Publications
In this paper, we analyze the problem of network disconnection in the context of large-scale P2P networks and understand how both static and dynamic patterns of node failure affect the resilience of such graphs. We start by applying classical results from random graph theory to show that a large variety of deterministic and random P2P graphs almost surely (i.e., with probability 1-o(1)) remain connected under random failure if and only if they have no isolated nodes. This simple, yet powerful, result subsequently allows us to derive in closed-form the probability that a P2P network develops isolated nodes, and therefore partitions, …
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Computer Science Faculty Publications
Clustering is well-suited for Web mining by automatically organizing Web pages into categories, each of which contains Web pages having similar contents. However, one problem in clustering is the lack of general methods to automatically determine the number of categories or clusters. For the Web domain in particular, currently there is no such method suitable for Web page clustering. In an attempt to address this problem, we discover a constant factor that characterizes the Web domain, based on which we propose a new method for automatically determining the number of clusters in Web page data sets. We discover that the …
The Good, Bad And The Indifferent: Explorations In Recommender System Health, Benjamin J. Keller, Sun-Mi Kim, N. Srinivas Vemuri, Naren Ramakrishnan, Saverio Perugini
The Good, Bad And The Indifferent: Explorations In Recommender System Health, Benjamin J. Keller, Sun-Mi Kim, N. Srinivas Vemuri, Naren Ramakrishnan, Saverio Perugini
Computer Science Faculty Publications
Our work is based on the premise that analysis of the connections exploited by a recommender algorithm can provide insight into the algorithm that could be useful to predict its performance in a fielded system. We use the jumping connections model defined by Mirza et al. [6], which describes the recommendation process in terms of graphs. Here we discuss our work that has come out of trying to understand algorithm behavior in terms of these graphs. We start by describing a natural extension of the jumping connections model of Mirza et al., and then discuss observations that have come from …
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 …
Staging Transformations For Multimodal Web Interaction Management, Michael Narayan, Christopher Williams, Saverio Perugini, Naren Ramakrishnan
Staging Transformations For Multimodal Web Interaction Management, Michael Narayan, Christopher Williams, Saverio Perugini, Naren Ramakrishnan
Computer Science Faculty Publications
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 – …
Program Transformations For Information Personalization, Saverio Perugini
Program Transformations For Information Personalization, Saverio Perugini
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. The central thesis of this dissertation is that modeling interaction explicitly in a representation, and studying how partial information can be harnessed in it by program transformations to direct the flow of the interaction, can provide insight into, reveal opportunities for, and define a model for personalized interaction. To evaluate this thesis, a formal modeling methodology is developed for personalizing interactions with information systems, especially hierarchical hypermedia, based on program transformations. The …
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 …
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, …