Computer Sciences Commons^™

Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox

Saverio Perugini

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

Saverio Perugini

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.

Symbolic Links In The Open Directory Project, Saverio Perugini

Saverio Perugini

We present a study to develop an improved understanding of symbolic links in web directories. A symbolic link is a hyperlink that makes a directed connection from a web page along one path through a directory to a page along another path. While symbolic links are ubiquitous in web directories such as Yahoo!, they are under-studied, and as a result, their uses are poorly understood. A cursory analysis of symbolic links reveals multiple uses: to provide navigational shortcuts deeper into a directory, backlinks to more general categories, and multiclassification. We investigated these uses in the Open Directory Project (ODP), the …

Interacting With Web Hierarchies, Saverio Perugini, Naren Ramakrishnan

Saverio Perugini

Web site interfaces are a particularly good fit for hierarchies in the broadest sense of that idea, i.e. a classification with multiple attributes, not necessarily a tree structure. Several adaptive interface designs are emerging that support flexible navigation orders, exposing and exploring dependencies, and procedural information-seeking tasks. This paper provides a context and vocabulary for thinking about hierarchical Web sites and their design. The paper identifies three features that interface to information hierarchies. These are flexible navigation orders, the ability to expose and explore dependencies, and support for procedural tasks. A few examples of these features are also provided

The Partial Evaluation Approach To Information Personalization, Naren Ramakrishnan, Saverio Perugini

Saverio Perugini

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 …

The Staging Transformation Approach To Mixing Initiative, Robert Capra, Michael Narayan, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones

Saverio Perugini

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 …

A Study Of Out-Of-Turn Interaction In Menu-Based, Ivr, Voicemail Systems, Saverio Perugini, Taylor J. Anderson, William F. Moroney

Saverio Perugini

We present the first user study of out-of-turn interaction in menu-based, interactive voice-response systems. Out-ofturn interaction is a technique which empowers the user (unable to respond to the current prompt) to take the conversational initiative by supplying information that is currently unsolicited, but expected later in the dialog. The technique permits the user to circumvent any flows of navigation hardwired into the design and navigate the menus in a manner which reflects their model of the task. We conducted a laboratory experiment to measure the effect of the use of outof- turn interaction on user performance and preference in a …

Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan

Saverio Perugini

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, …

Information Assurance Through Binary Vulnerability Auditing, William B. Kimball, Saverio Perugini

Saverio Perugini

The goal of this research is to develop improved methods of discovering vulnerabilities in software. A large volume of software, from the most frequently used programs on a desktop computer, such as web browsers, e-mail programs, and word processing applications, to mission-critical services for the space shuttle, is unintentionally vulnerable to attacks and thus insecure. By seeking to improve the identification of vulnerabilities in software, the security community can save the time and money necessary to restore compromised computer systems. In addition, this research is imperative to activities of national security such as counterterrorism. The current approach involves a systematic …

Personalizing Interactions With Information Systems, Saverio Perugini, Naren Ramakrishnan

Saverio Perugini

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 …

Mining Web-Functional Dependencies For Flexible Information Access, Saverio Perugini, Naren Ramakrishnan

Saverio Perugini

We present an approach to enhancing information access through Web structure mining in contrast to traditional approaches involving usage mining. Specifically, we mine the hardwired hierarchical hyperlink structure of Web sites to identify patterns of term-term co-occurrences we call Web functional dependencies (FDs). Intuitively, a Web FD ‘x y’ declares that all paths through a site involving a hyperlink labeled x also contain a hyperlink labeled y. The complete set of FDs satisfied by a site help characterize (flexible and expressive) interaction paradigms supported by a site, where a paradigm is the set of explorable sequences therein. …

Supporting Multiple Paths To Objects In Information Hierarchies: Faceted Classification, Faceted Search, And Symbolic Links, Saverio Perugini

Saverio Perugini

We present three fundamental, interrelated approaches to support multiple access paths to each terminal object in information hierarchies: faceted classification, faceted search, and web directories with embedded symbolic links. This survey aims to demonstrate how each approach supports users who seek information from multiple perspectives. We achieve this by exploring each approach, the relationships between these approaches, including tradeoffs, and how they can be used in concert, while focusing on a core set of hypermedia elements common to all. This approach provides a foundation from which to study, understand, and synthesize applications which employ these techniques. This survey does not …

Recommender Systems Research, Saverio Perugini

Saverio Perugini

We outline the history of recommender systems from their roots in information retrieval and filtering to their role in today’s Internet economy. Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. Research in recommender systems lies at the intersection of several areas of computer science, such as artificial intelligence and human-computer interaction, and has progressed to an important research area of its own. It is important to note that recommendations are not delivered within a vacuum, but rather cast within an informal community of users …

Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini

Saverio Perugini

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.

The Good, Bad And The Indifferent: Explorations In Recommender System Health, Benjamin J. Keller, Sun-Mi Kim, N. Srinivas Vemuri, Naren Ramakrishnan, Saverio Perugini

Saverio Perugini

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 …

Staging Transformations For Multimodal Web Interaction Management, Michael Narayan, Christopher Williams, Saverio Perugini, Naren Ramakrishnan

Saverio Perugini

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 – …

Ocena Wpływu Rozdzielczości Siatki Obliczeniowej Na Wyniki Modelowania Rozprzestrzeniania Się Zanieczyszczeń W Powietrzu, Mateusz Rzeszutek, Robert Oleniacz, Marian Mazur

Robert Oleniacz

In this study are presented the results of the assessment of the impact of grid resolution on the results of computational modeling of the dispersion of air pollutants. Calculations were performed using Gaussian, non-stationary puff model CALPUFF. Four different grids resolution were analyzed. Networks were established on the basis of SRTM3 terrain and land cover classes of CLC, 2006. Analysis of results of spatial distribution of concentrations of air pollutants obtained in a regular computing grid was performed using statistical indicators recommended by the U.S. EPA. The study shows the applicability of particular computational grids in the system modeling transport …

These Are Not The K-Mers You Are Looking For: Efficient Online K-Mer Counting Using A Probabilistic Data Structure, Qingpeng Zhang, Jason Pell, Rosangela Canino-Koning, Adina Chuang Howe, C. Titus Brown

Adina Howe

K-mer abundance analysis is widely used for many purposes in nucleotide sequence analysis, including data preprocessing for de novo assembly, repeat detection, and sequencing coverage estimation. We present the khmer software package for fast and memory efficient online counting of k-mers in sequencing data sets. Unlike previous methods based on data structures such as hash tables, suffix arrays, and trie structures, khmer relies entirely on a simple probabilistic data structure, a Count-Min Sketch. The Count-Min Sketch permits online updating and retrieval of k-mer counts in memory which is necessary to support online k-mer analysis algorithms. On sparse data sets this …

A General Framework For Uncertainty Propagation Based On Point Estimate Methods, René Schenkendorf

René Schenkendorf

A general framework to approach the challenge of uncertainty propagation in model based prognostics is presented in this work. It is shown how the so-called Point Estimate Meth- ods (PEMs) are ideally suited for this purpose because of the following reasons: 1) A credible propagation and represen- tation of Gaussian (normally distributed) uncertainty can be done with a minimum of computational effort for non-linear applications. 2) Also non-Gaussian uncertainties can be prop- agated by evaluating suitable transfer functions inherently. 3) Confidence intervals of simulation results can be derived which do not have to be symmetrically distributed around the mean value …

Link Spamming Wikipedia For Profit, Andrew West, Jian Chang, Krishna Venkatasubramanian, Oleg Sokolsky, Insup Lee

Oleg Sokolsky

Collaborative functionality is an increasingly prevalent web technology. To encourage participation, these systems usually have low barriers-to-entry and permissive privileges. Unsurprisingly, ill-intentioned users try to leverage these characteristics for nefarious purposes. In this work, a particular abuse is examined -- link spamming -- the addition of promotional or otherwise inappropriate hyperlinks.

Our analysis focuses on the "wiki" model and the collaborative encyclopedia, Wikipedia, in particular. A principal goal of spammers is to maximize *exposure*, the quantity of people who view a link. Creating and analyzing the first Wikipedia link spam corpus, we find that existing spam strategies perform quite poorly …

Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang

Kyriakos MOURATIDIS

In this paper we study a novel query type, called direct neighbor query. Two objects in a dataset are direct neighbors (DNs) if a window selection may exclusively retrieve these two objects. Given a source object, a DN search computes all of its direct neighbors in the dataset. The DNs define a new type of affinity that differs from existing formulations (e.g., nearest neighbors, nearest surrounders, reverse nearest neighbors, etc.) and finds application in domains where user interests are expressed in the form of windows, i.e., multi-attribute range selections. Drawing on key properties of the DN relationship, we develop an …

Predicting Response In Mobile Advertising With Hierarchical Importance-Aware Factorization Machine, Richard Jayadi Oentaryo, Ee Peng Lim, Jia Wei Low, David Lo, Michael Finegold

David LO

Mobile advertising has recently seen dramatic growth, fueled by the global proliferation of mobile phones and devices. The task of predicting ad response is thus crucial for maximizing business revenue. However, ad response data change dynamically over time, and are subject to cold-start situations in which limited history hinders reliable prediction. There is also a need for a robust regression estimation for high prediction accuracy, and good ranking to distinguish the impacts of different ads. To this end, we develop a Hierarchical Importance-aware Factorization Machine (HIFM), which provides an effective generic latent factor framework that incorporates importance weights and hierarchical …

On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo

David LO

Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome property which can be combined with pattern mining so as to automatically extract TPRs from any given game datasets. We specifically extend the well-known PrefixSpan sequence mining algorithm by incorporating the irreversible outcome property. To show the usefulness of TPRs, we apply them to Tetris, a popular game. We mine …

R-Energy For Evaluating Robustness Of Dynamic Networks, Ming Gao, Ee Peng Lim, David Lo

David LO

The robustness of a network is determined by how well its vertices are connected to one another so as to keep the network strong and sustainable. As the network evolves its robustness changes and may reveal events as well as periodic trend patterns that affect the interactions among users in the network. In this paper, we develop R-energy as a new measure of network robustness based on the spectral analysis of normalized Laplacian matrix. R-energy can cope with disconnected networks, and is efficient to compute with a time complexity of O (jV j + jEj) where V and E are …

Ocena Wpływu Nowo Budowanej Spalarni Odpadów Komunalnych W Krakowie Na Jakość Powietrza Z Wykorzystaniem Modelu Calmet/Calpuff, Mateusz Rzeszutek, Robert Oleniacz

Robert Oleniacz

The chapter presents the results of the evaluation the impact on air quality for the newly built Municipal Solid Waste Thermal Treatment Plant in Krakow (Poland) whose construction started in autumn 2013. Air pollution impact assessment was performed for air emissions adopted at the levels of emission limit values applicable for waste incineration. Modeling of air pollutant dispersion was carried out using the system of CALMET/CALPUFF models. For this purpose, the terrain elevation data from Shuttle Radar Topography Mission (SRTM3) and data of land use from Corine Land Cover 2006 (CLC 2006) were adopted with a resolution of about 100 …

Revealing The Bacterial Butyrate Synthesis Pathways By Analyzing (Meta)Genomic Data, Marius Vital, Adina Chuang Howe, James M. Tiedje

Adina Howe

Butyrate-producing bacteria have recently gained attention, since they are important for a healthy colon and when altered contribute to emerging diseases, such as ulcerative colitis and type II diabetes. This guild is polyphyletic and cannot be accurately detected by 16S rRNA gene sequencing. Consequently, approaches targeting the terminal genes of the main butyrate-producing pathway have been developed. However, since additional pathways exist and alternative, newly recognized enzymes catalyzing the terminal reaction have been described, previous investigations are often incomplete. We undertook a broad analysis of butyrate-producing pathways and individual genes by screening 3,184 sequenced bacterial genomes from the Integrated Microbial …

Social Sensing For Urban Crisis Management: The Case Of Singapore Haze, Philips Kokoh Prasetyo, Ming Gao, Ee Peng Lim, Christie N. Scollon

Ming Gao

Sensing social media for trends and events has become possible as increasing number of users rely on social media to share information. In the event of a major disaster or social event, one can therefore study the event quickly by gathering and analyzing social media data. One can also design appropriate responses such as allocating resources to the affected areas, sharing event related information, and managing public anxiety. Past research on social event studies using social media often focused on one type of data analysis (e.g., hashtag clusters, diffusion of events, influential users, etc.) on a single social media data …

R-Energy For Evaluating Robustness Of Dynamic Networks, Ming Gao, Ee Peng Lim, David Lo

Ming Gao

The robustness of a network is determined by how well its vertices are connected to one another so as to keep the network strong and sustainable. As the network evolves its robustness changes and may reveal events as well as periodic trend patterns that affect the interactions among users in the network. In this paper, we develop R-energy as a new measure of network robustness based on the spectral analysis of normalized Laplacian matrix. R-energy can cope with disconnected networks, and is efficient to compute with a time complexity of O (jV j + jEj) where V and E are …

Fc Product：Discrete Fractional Chaotic Signal Software, Guo-Cheng Wu, Dumitru Baleanu

G.C. Wu

No abstract provided.

A New Class Of Scalable Parallel Pseudorandom Number Generators Based On Pohlig-Hellman Exponentiation Ciphers, Paul Beale

Paul Beale

Parallel supercomputer-based Monte Carlo applications depend on pseudorandom number generators that produce independent pseudorandom streams across many separate processes. We propose a new scalable class of parallel pseudorandom number generators based on Pohlig--Hellman exponentiation ciphers. The method generates uniformly distributed floating point pseudorandom streams by encrypting simple sequences of integer \textit{messages} into \textit{ciphertexts} by exponentiation modulo prime numbers. The advantages of the method are: the method is trivially parallelizable by parameterization with each pseudorandom number generator derived from an independent prime modulus, the method is fully scalable on massively parallel computing clusters due to the large number of primes available …