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2010

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Articles 31 - 60 of 243

Full-Text Articles in Databases and Information Systems

Business Network-Based Value Creation In Electronic Commerce, Robert John Kauffman, Ting Li, Eric Van Heck Oct 2010

Business Network-Based Value Creation In Electronic Commerce, Robert John Kauffman, Ting Li, Eric Van Heck

Research Collection School Of Computing and Information Systems

Information technologies (IT) have affected economic activities within and beyond the boundaries of the firm, changing the face of e-commerce. This article explores the circumstances under which value is created in business networks made possible by IT. Business networks combine the capabilities of multiple firms to produce and deliver products and services that none of them could more economically produce on its own and for which there is demand in the market. We call this business network-based value creation. We apply economic theory to explain the conditions under which business networks will exist and are able to sustain their value-producing …

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Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng Oct 2010

Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng

Research Collection School Of Computing and Information Systems

Link structures are important patterns one looks out for when modeling and analyzing social networks. In this paper, we propose the task of mining interesting Link Formation rules (LF-rules) containing link structures known as Link Formation patterns (LF-patterns). LF-patterns capture various dyadic and/or triadic structures among groups of nodes, while LF-rules capture the formation of a new link from a focal node to another node as a postcondition of existing connections between the two nodes. We devise a novel LF-rule mining algorithm, known as LFR-Miner, based on frequent subgraph mining for our task. In addition to using a support-confidence framework …

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Jointly Modeling Aspects And Opinions With A Maxent-Lda Hybrid, Xin Zhao, Jing Jiang, Hongfei Yan, Xiaoming Li Oct 2010

Jointly Modeling Aspects And Opinions With A Maxent-Lda Hybrid, Xin Zhao, Jing Jiang, Hongfei Yan, Xiaoming Li

Research Collection School Of Computing and Information Systems

Discovering and summarizing opinions from online reviews is an important and challenging task. A commonly-adopted framework generates structured review summaries with aspects and opinions. Recently topic models have been used to identify meaningful review aspects, but existing topic models do not identify aspect-specific opinion words. In this paper, we propose a MaxEnt-LDA hybrid model to jointly discover both aspects and aspect-specific opinion words. We show that with a relatively small amount of training data, our model can effectively identify aspect and opinion words simultaneously. We also demonstrate the domain adaptability of our model.

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The Mississippi Digital Library’S Civil Rights Thesaurus: An Evolving Authority Control Tool For Civil Rights-Related Headings In Metadata Records, Kathleen L. Wells Oct 2010

The Mississippi Digital Library’S Civil Rights Thesaurus: An Evolving Authority Control Tool For Civil Rights-Related Headings In Metadata Records, Kathleen L. Wells

The Southeastern Librarian

The online Civil Rights Thesaurus (CRT) at the University of Southern Mississippi (USM) had its beginnings in the digitization of civil rights materials in the university’s McCain Library and Archives in the early 2000s. The materials included oral history interviews, letters, newspaper clippings, photographs, and other items from the rich history of the civil rights movement in Mississippi, including materials from the Freedom Summer of 1964. In addition to the creation of digitized images, making these materials available online as the Civil Rights in Mississippi Digital Archive included the formulation of descriptive records using Dublin Core metadata and the development …

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Online Multiple Kernel Learning: Algorithms And Mistake Bounds, Rong Jin, Steven C. H. Hoi, Tianbao Yang Oct 2010

Online Multiple Kernel Learning: Algorithms And Mistake Bounds, Rong Jin, Steven C. H. Hoi, Tianbao Yang

Research Collection School Of Computing and Information Systems

Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing the intersecting research. In this paper, we introduce a new research problem, termed Online Multiple Kernel Learning (OMKL), that aims to learn a kernel based prediction function from a pool of predefined kernels in an online learning fashion. OMKL is generally more challenging than typical online learning because both the kernel classifiers and their linear combination weights must be learned simultaneously. In this work, we consider two setups for OMKL, i.e. combining …

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Detecting Product Review Spammers Using Rating Behaviors, Ee Peng Lim, Viet-An Nguyen, Nitin Jindal, Bing Liu, Hady Wirawan Lauw Oct 2010

Detecting Product Review Spammers Using Rating Behaviors, Ee Peng Lim, Viet-An Nguyen, Nitin Jindal, Bing Liu, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

This paper aims to detect users generating spam reviews or review spammers. We identify several characteristic be- haviors of review spammers and model these behaviors so as to detect the spammers. In particular, we seek to model the following behaviors. First, spammers may target specific products or product groups in order to maximize their im- pact. Second, they tend to deviate from the other reviewers in their ratings of products. We propose scoring methods to measure the degree of spam for each reviewer and apply them on an Amazon review dataset. We then select a sub- set of highly suspicious …

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Cast2face: Character Identification In Movie With Actor-Character Correspondence, Mengdi Xu, Xiaotong Yuan, Jialie Shen, Shuicheng Yan Oct 2010

Cast2face: Character Identification In Movie With Actor-Character Correspondence, Mengdi Xu, Xiaotong Yuan, Jialie Shen, Shuicheng Yan

Research Collection School Of Computing and Information Systems

We investigate the problem of automatically identifying characters in a movie with the supervision of actor-character name correspondence provided by the movie cast. Our proposed framework, namely Cast2Face, is featured by: (i) we restrict the names to assign within the set of character names in the cast; (ii) for each character, by using the corresponding actor's name as a key word, we retrieve from Google image search a group of face images to form the gallery set; and (iii) the probe face tracks in the movie are then identified as one of the actors by robust multi-task joint sparse representation …

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Trajectory-Based Visualization Of Web Video Topics, Juan Cao, Chong-Wah Ngo, Yong-Dong Zhang, Dong-Ming Zhang, Liang Ma Oct 2010

Trajectory-Based Visualization Of Web Video Topics, Juan Cao, Chong-Wah Ngo, Yong-Dong Zhang, Dong-Ming Zhang, Liang Ma

Research Collection School Of Computing and Information Systems

While there have been research efforts in organizing largescale web videos into topics, efficient browsing of web video topics remains a challenging problem not yet addressed. The related issues include how to efficiently browse and track the evolution of topics and eventually locate the videos of interest. In this paper, we introduce a novel interface for visualizing video topics as evolution trajectories. The trajectory visualization is capable of highlighting milestone events and depicting the topical hotness over time. The interface also allows multi-level browsing from topics to events and to videos, resulting in search exploration could be more efficiently conducted …

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Co-Creation And Collaboration In A Virtual World: A 3d Visualization Design Project In Second Life, Keng Siau, Fiona Fui-Hoon Nah, B. Mennecke, S. Schiller Oct 2010

Co-Creation And Collaboration In A Virtual World: A 3d Visualization Design Project In Second Life, Keng Siau, Fiona Fui-Hoon Nah, B. Mennecke, S. Schiller

Research Collection School Of Computing and Information Systems

One of the most successful and useful implementations of 3D virtual worlds is in the area of education and training. This paper discusses the use of virtual worlds in education and describes an innovative 3D visualization design project using one of the most popular virtual worlds, Second Life. This ongoing project is a partnership between IBM and three universities in the United States: the University of Nebraska-Lincoln, Iowa State University, and Wright State University. More than 400 MBA students have participated in this project by completing a creative design project that involves co-creation and collaboration in Second Life. The MBA …

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Context Modeling For Ranking And Tagging Bursty Features In Text Streams, Xin Zhao, Jing Jiang, Jing He, Xiaoming Li, Hongfei Yan, Dongdong Shan Oct 2010

Context Modeling For Ranking And Tagging Bursty Features In Text Streams, Xin Zhao, Jing Jiang, Jing He, Xiaoming Li, Hongfei Yan, Dongdong Shan

Research Collection School Of Computing and Information Systems

Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without taking into account the semantic contexts of terms, and as a result the detected bursty features may not always be interesting or easy to interpret. In this paper we propose to model the contexts of bursty features using a language modeling approach. We then propose a novel topic diversity-based metric using the context models to find newsworthy bursty features. We also propose to use the context models to automatically assign meaningful tags to bursty …

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Mining Collaboration Patterns From A Large Developer Network, Didi Surian, David Lo, Ee Peng Lim Oct 2010

Mining Collaboration Patterns From A Large Developer Network, Didi Surian, David Lo, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this study, we extract patterns from a large developer collaborations network extracted from Source Forge. Net at high and low level of details. At the high level of details, we extract various network-level statistics from the network. At the low level of details, we extract topological sub-graph patterns that are frequently seen among collaborating developers. Extracting sub graph patterns from large graphs is a hard NP-complete problem. To address this challenge, we employ a novel combination of graph mining and graph matching by leveraging network-level properties of a developer network. With the approach, we successfully analyze a snapshot of …

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Rich Internet Geoweb For Spatial Data Infrastructure, Tin Seong Kam Oct 2010

Rich Internet Geoweb For Spatial Data Infrastructure, Tin Seong Kam

Research Collection School Of Computing and Information Systems

In this information age, more and more public statistical data such as population census, household living, local economy and business establishment are distributed over the internet within the framework of spatial data infrastructure. By and large, these data are organized geographically such as region, province as well as district. Usually, they are published in the form of digital maps over the internet as simple points, lines and polygons markers limited or no analytical function available to transform these data into useful information. To meet the analytical needs of casual public data users, we contribute RIGVAT, a rich internet geospatial visual …

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Improving Information Products For System 2 Decision Support, Neal Gibson Sep 2010

Improving Information Products For System 2 Decision Support, Neal Gibson

Theses and Dissertations

The creation, maintenance, and management of Information Product (IP) systems that are used by organizations for complex decisions represent a unique set of challenges. These challenges are compounded when the purpose of such a systems is also for knowledge creation and dissemination. Information quality research to date has focused mainly upon treating IP independent from the actual users, despite the obvious interdependency between the two. Research in cognitive psychology has established a dual-process model for human cognition. Designing IP systems in recognition of these differing methods of human cognition represents a new approach to improving their quality. Education data and …

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Knowledge-Driven Identity Resolution For Longitudinal Education Data, Greg Holland Sep 2010

Knowledge-Driven Identity Resolution For Longitudinal Education Data, Greg Holland

Theses and Dissertations

Data sets containing information for an overlapping group of real-world identities present a very high likelihood that the identifying attributes and attribute values for these identities may be inconsistent between the data sets. Differences in the types of identifying attributes or attribute values inhibit proper record linkage and identity resolution. Traditional approaches to record linkage are commonly utilized however the results from these approaches do not demonstrate the highest possible levels of confidence and utility. Syntax, semantics, and temporal aspects of data sets should be understood and incorporated into the methodology of heterogeneous data set integration. Domain-specific expertise is a …

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A Taxonomy-Based Model For Expertise Extrapolation, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar, Sheron L. Decker, Amit P. Sheth Sep 2010

A Taxonomy-Based Model For Expertise Extrapolation, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar, Sheron L. Decker, Amit P. Sheth

Kno.e.sis Publications

While many ExpertFinder applications succeed in finding experts, their techniques are not always designed to capture the various levels at which expertise can be expressed. Indeed, expertise can be inferred from relationships between topics and subtopics in a taxonomy. The conventional wisdom is that expertise in subtopics is also indicative of expertise in higher level topics as well. The enrichment of Expertise Profiles for finding experts can therefore be facilitated by taking domain hierarchies into account. We present a novel semantics-based model for finding experts, expertise levels and collaboration levels in a peer review context, such as composing a Program …

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Investigating Ultrasonic Positioning On Mobile Phones, Viacheslav Filonenko, Charlie Cullen, James Carswell Sep 2010

Investigating Ultrasonic Positioning On Mobile Phones, Viacheslav Filonenko, Charlie Cullen, James Carswell

Conference papers

In this paper we evaluate the innate ability of mobile phone speakers to produce ultrasound and the possible uses of this ability for accurate indoor positioning. The frequencies in question are a range between 20 and 22 KHz, which is high enough to be inaudible but low enough to be generated by standard sound hardware. A range of tones is generated at different volume settings on several popular modern mobile phones with the aim of finding points of failure. Our results indicate that it is possible to generate the given range of frequencies without significant distortions, provided the signal volume …

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Ranking Documents Semantically Using Ontological Relationships, Boanerges Aleman-Meza, I. Budak Arpinar, Mustafa V. Nural, Amit P. Sheth Sep 2010

Ranking Documents Semantically Using Ontological Relationships, Boanerges Aleman-Meza, I. Budak Arpinar, Mustafa V. Nural, Amit P. Sheth

Kno.e.sis Publications

Although arguable success of today’s keyword based search engines in certain information retrieval tasks, ranking search results in a meaningful way remains an open problem. In this work, the goal is to use of semantic relationships for ranking documents without relying on the existence of any specific structure in a document or links between documents. Instead, real-world entities are identified and the relevance of documents is determined using relationships that are known to exist between the entities in a populated ontology. We introduce a measure of relevance that is based on traversal and the semantics of relationships that link entities …

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Diract: Agent-Based Interactive Storytelling, Yundong Cai, Zhiqi Shen, Chunyan Miao, Ah-Hwee Tan Sep 2010

Diract: Agent-Based Interactive Storytelling, Yundong Cai, Zhiqi Shen, Chunyan Miao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

A lot of researches haven been done on the interactive storytelling authoring , e.g. by a director agent, or by interactions among a number of character agents. However, it is still difficult to construct the interactive storytelling for novice users, due to a need of various agents development and complex communication among the agents. We propose an agent-based interactive storytelling architecture, namely DIRACT (short of “Direct and Act”). It is composed of numerous atomic DIRACT agents, which are goal oriented and use an unified communication protocol. By removing the difference between the director and character, each DIRACT agent can either …

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Context-Aware Query Recommendations, Alexandros Ntoulas, Heasoo Hwang, Lise Getoor, Stelios Paparizos, Hady Wirawan Lauw Sep 2010

Context-Aware Query Recommendations, Alexandros Ntoulas, Heasoo Hwang, Lise Getoor, Stelios Paparizos, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Described is a search-related technology in which context information regarding a user's prior search actions is used in making query recommendations for a current user action, such as a query or click. To determine whether each set or subset of context information is relevant to the user action, data obtained from a query log is evaluated. More particularly, a query transition (query-query) graph and a query click (query-URL) graph are extracted from the query log; vectors are computed for the current action and each context/sub-context and evaluated against vectors in the graphs to determine current action-to-context similarity. Also described is …

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Embellishing Text Search Queries To Protect User Privacy, Hwee Hwa Pang, Xuhua Ding, Xiaokui Xiao Sep 2010

Embellishing Text Search Queries To Protect User Privacy, Hwee Hwa Pang, Xuhua Ding, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Users of text search engines are increasingly wary that their activities may disclose confidential information about their business or personal profiles. It would be desirable for a search engine to perform document retrieval for users while protecting their intent. In this paper, we identify the privacy risks arising from semantically related search terms within a query, and from recurring highspecificity query terms in a search session. To counter the risks, we propose a solution for a similarity text retrieval system to offer anonymity and plausible deniability for the query terms, and hence the user intent, without degrading the system’s precision-recall …

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P2pdoctagger: Content Management Through Automated P2p Collaborative Tagging, Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Steven C. H. Hoi Sep 2010

P2pdoctagger: Content Management Through Automated P2p Collaborative Tagging, Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

As the amount of user generated content grows, personal information management has become a challenging problem. Several information management approaches, such as desktop search, document organization and (collaborative) document tagging have been proposed to address this, however they are either inappropriate or inefficient. Automated collaborative document tagging approaches mitigate the problems of manual tagging, but they are usually based on centralized settings which are plagued by problems such as scalability, privacy, etc. To resolve these issues, we present P2PDocTagger, an automated and distributed document tagging system based on classification in P2P networks. P2P-DocTagger minimizes the efforts of individual peers and …

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Shortest Path Computation On Air Indexes, Georgios Kellaris, Kyriakos Mouratidis Sep 2010

Shortest Path Computation On Air Indexes, Georgios Kellaris, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Shortest path computation is one of the most common queries in location-based services that involve transportation net- works. Motivated by scalability challenges faced in the mo- bile network industry, we propose adopting the wireless broad- cast model for such location-dependent applications. In this model the data are continuously transmitted on the air, while clients listen to the broadcast and process their queries locally. Although spatial problems have been considered in this environment, there exists no study on shortest path queries in road networks. We develop the rst framework to compute shortest paths on the air, and demonstrate the practicality and …

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3dq: Threat Dome Visibility Querying On Mobile Devices, James Carswell, Keith Gardiner, Junjun Yin Aug 2010

3dq: Threat Dome Visibility Querying On Mobile Devices, James Carswell, Keith Gardiner, Junjun Yin

Articles

3DQ (Three Dimensional Query) is our mobile spatial interaction (MSI) prototype for location and orientation aware mobile devices (i.e. today's sensor enabled smartphones). The prototype tailors a military style threat dome query calculation using MSI with hidden query removal functionality for reducing “information overload” on these off-the-shelf devices. The effect gives a more accurate and expected query result for Location-Based Services (LBS) applications by returning information on only those objects visible within a user’s 3D field-of-view. Our standardised XML based request/response design enables any mobile device, regardless of operating system and/or programming language, to access the 3DQ web-service interfaces.

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Penetration Testing And Vulnerability Assessments: A Professional Approach, Konstantinos Xynos, Iain Sutherland, Huw Read, Emlyn Everitt, Andrew J C Blyth Aug 2010

Penetration Testing And Vulnerability Assessments: A Professional Approach, Konstantinos Xynos, Iain Sutherland, Huw Read, Emlyn Everitt, Andrew J C Blyth

International Cyber Resilience conference

Attacks against computer systems and the data contained within these systems are becoming increasingly frequent and evermore sophisticated. So-called “zero-day” exploits can be purchased on black markets and Advanced Persistent Threats (APTs) can lead to exfiltration of data over extended periods. Organisations wishing to ensure security of their systems may look towards adopting appropriate measures to protect themselves against potential security breaches. One such measure is to hire the services of penetration testers (or “pen-tester”) to find vulnerabilities present in the organisation’s network, and provide recommendations as to how best to mitigate such risks. This paper discusses the definition and …

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Choosing Management Information Systems As A Major: Understanding The Smifactors For Mis, Thomas W. Ferratt, Stephen R. Hall, Jayesh Prasad, Donald E. Wynn Aug 2010

Choosing Management Information Systems As A Major: Understanding The Smifactors For Mis, Thomas W. Ferratt, Stephen R. Hall, Jayesh Prasad, Donald E. Wynn

MIS/OM/DS Faculty Publications

Given declining management information systems (MIS) enrollments at our university, we seek to understand our students‘ selection of a major. Prior studies have found that students choose a major based on a number of factors, with subject matter interest consistently being most important. We contribute to the literature by developing a deeper understanding of what is meant by subject matter interest, which we refer to as smiFactors, for MIS as a major and career. Based on a qualitative analysis of open-ended survey questions completed by undergraduate business students, we confirm a number of smiFactors for MIS gleaned from recent studies …

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A Comparative Study Of Filter-Based Feature Ranking Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao Aug 2010

A Comparative Study Of Filter-Based Feature Ranking Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao

Computer Science Faculty Publications

One factor that affects the success of machine learning is the presence of irrelevant or redundant information in the training data set. Filter-based feature ranking techniques (rankers) rank the features according to their relevance to the target attribute and we choose the most relevant features to build classification models subsequently. In order to evaluate the effectiveness of different feature ranking techniques, a commonly used method is to assess the classification performance of models built with the respective selected feature subsets in terms of a given performance metric (e.g., classification accuracy or misclassification rate). Since a given performance metric usually can …

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A Comparative Study Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse Aug 2010

A Comparative Study Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse

Computer Science Faculty Publications

Abstract Given high-dimensional software measurement data, researchers and practitioners often use feature (metric) selection techniques to improve the performance of software quality classification models. This paper presents our newly proposed threshold-based feature selection techniques, comparing the performance of these techniques by building classification models using five commonly used classifiers. In order to evaluate the effectiveness of different feature selection techniques, the models are evaluated using eight different performance metrics separately since a given performance metric usually captures only one aspect of the classification performance. All experiments are conducted on three Eclipse data sets with different levels of class imbalance. The …

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Investigating Capabilities Associated With Ict Access And Use In Latino Micro-Enterprises, Travis Good, Luis Flores Morales, Sajda Qureshi Aug 2010

Investigating Capabilities Associated With Ict Access And Use In Latino Micro-Enterprises, Travis Good, Luis Flores Morales, Sajda Qureshi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

While the process by which Information Technology enables growth in medium and large enterprises has been wellresearched, the corresponding processes in micro-enterprises are poorly understood. In fact, such micro-enterprises lie at the heart of many economies. This insight is important as information technology enables businesses to connect with each other through knowledge networking to carry out their basic business operations. There is thus a need to build our understanding of how micro-enterprises access and use technology in order to be able to assess the benefits they derive from ICT adoption. Following an analysis of two case studies of Latino micro-enterprises …

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Pattern Space Maintenance For Data Updates And Interactive Mining, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong Aug 2010

Pattern Space Maintenance For Data Updates And Interactive Mining, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong

Kno.e.sis Publications

This article addresses the incremental and decremental maintenance of the frequent pattern space. We conduct an in-depth investigation on how the frequent pattern space evolves under both incremental and decremental updates. Based on the evolution analysis, a new data structure, Generator-Enumeration Tree (GE-tree), is developed to facilitate the maintenance of the frequent pattern space. With the concept of GE-tree, we propose two novel algorithms, Pattern Space Maintainer+ (PSM+) and Pattern Space Maintainer− (PSM−), for the incremental and decremental maintenance of frequent patterns. Experimental results demonstrate that the proposed algorithms, on average, outperform the representative state-of-the-art …

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Cross-Market Model Adaptation With Pairwise Preference Data For Web Search Ranking, Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen Aug 2010

Cross-Market Model Adaptation With Pairwise Preference Data For Web Search Ranking, Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen

Kno.e.sis Publications

Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibility required of a commercial web search. However, manually labeled training data (with multiple absolute grades) has become the bottleneck for training a quality ranking function, particularly for a new domain. In this paper, we explore the adaptation of machine-learned ranking models across a set of geographically diverse markets with the market-specific pairwise preference data, which can be easily obtained from clickthrough logs. We propose a novel adaptation algorithm, Pairwise-Trada, which is able to adapt ranking models that are trained …

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