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Articles 5911 - 5940 of 6720

Full-Text Articles in Physical Sciences and Mathematics

On Assigning Place Names To Geography Related Web Pages, Wenbo Zong, Dan Wu, Aixin Sun, Ee Peng Lim, Dion Hoe-Lian Goh Jun 2005

On Assigning Place Names To Geography Related Web Pages, Wenbo Zong, Dan Wu, Aixin Sun, Ee Peng Lim, Dion Hoe-Lian Goh

Research Collection School Of Computing and Information Systems

In this paper, we attempt to give spatial semantics to web pages by assigning them place names. The entire assignment task is divided into three sub-problems, namely place name extraction, place name disambiguation and place name assignment. We propose our approaches to address these sub-problems. In particular, we have modified GATE, a well-known named entity extraction software, to perform place name extraction using a US Census gazetteer. A rule-based place name disambiguation method and a place name assignment method capable of assigning place names to web page segments have also been proposed. We have evaluated our proposed disambiguation and assignment …


Evaluating G-Portal For Geography Learning And Teaching, Chew-Hung Chang, John G. Hedberg, Yin-Leng Theng, Ee Peng Lim, Tiong-Sa Teh, Dion Hoe-Lian Goh Jun 2005

Evaluating G-Portal For Geography Learning And Teaching, Chew-Hung Chang, John G. Hedberg, Yin-Leng Theng, Ee Peng Lim, Tiong-Sa Teh, Dion Hoe-Lian Goh

Research Collection School Of Computing and Information Systems

This paper describes G-Portal, a geospatial digital library of geographical assets, providing an interactive platform to engage students in active manipulation and analysis of information resources and collaborative learning activities. Using a G-Portal application in which students conducted a field study of an environmental problem of beach erosion and sea level rise, we describe a pilot study to evaluate usefulness and usability issues to support the learning of geographical concepts, and in turn teaching.


Verifying Completeness Of Relational Query Results In Data Publishing, Hwee Hwa Pang, Arpit Jain, Krithi Ramamritham, Kian-Lee Tan Jun 2005

Verifying Completeness Of Relational Query Results In Data Publishing, Hwee Hwa Pang, Arpit Jain, Krithi Ramamritham, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

In data publishing, the owner delegates the role of satisfying user queries to a third-party publisher. As the publisher may be untrusted or susceptible to attacks, it could produce incorrect query results. In this paper, we introduce a scheme for users to verify that their query results are complete (i.e., no qualifying tuples are omitted) and authentic (i.e., all the result values originated from the owner). The scheme supports range selection on key and non-key attributes, project as well as join queries on relational databases. Moreover, the proposed scheme complies with access control policies, is computationally secure, and can be …


The Effects Of Digital Audio On Social Presence, Motivation And Perceived Learning In Asynchronous Learning Networks, Eunhee Kim May 2005

The Effects Of Digital Audio On Social Presence, Motivation And Perceived Learning In Asynchronous Learning Networks, Eunhee Kim

Dissertations

This study explores the possibilities of applying digital audio to the ALN environment, so that students can speak and listen rather than type and read. Two sets of 1x2 field experiments (text vs. digital audio) were conducted with two formats of digital audio -recorded voice messages and narrated Microsoft PowerPoint presentation - used in several NJIT courses conducted via ALN. The perceptions of communication media were measured from two different user perspectives: active use when the subjects created their assignments using prescribed communication media (audio or text) and passive use when the subjects viewed/listened to other students' work.

The perceptions …


Collaborative Examinations In Asyncronous Learning Networks : Field Experiments On Collaborative Learning Through Online Assessments, Jia Shen May 2005

Collaborative Examinations In Asyncronous Learning Networks : Field Experiments On Collaborative Learning Through Online Assessments, Jia Shen

Dissertations

With the proliferation of computer networks and the emergence of virtual teams, learning and knowledge sharing in the online environment has become an increasingly important topic. Applying constructivism and collaborative learning theories to assessment, the collaborative online exam is designed featuring students' active participation in various phases of the exam process through small group activities online. A participatory online exam process is designed featuring similar procedures except that students' involvement in each phase of the exam is individual. The collaborative online exam and the participatory online exam are investigated regarding student exam study strategies, group process, exam outcomes, faculty satisfaction, …


Improving Document Representation By Accumulating Relevance Feedback : The Relevance Feedback Accumulation (Rfa) Algorithm, Razvan Stefan Bot May 2005

Improving Document Representation By Accumulating Relevance Feedback : The Relevance Feedback Accumulation (Rfa) Algorithm, Razvan Stefan Bot

Dissertations

Document representation (indexing) techniques are dominated by variants of the term-frequency analysis approach, based on the assumption that the more occurrences a term has throughout a document the more important the term is in that document. Inherent drawbacks associated with this approach include: poor index quality, high document representation size and the word mismatch problem. To tackle these drawbacks, a document representation improvement method called the Relevance Feedback Accumulation (RFA) algorithm is presented. The algorithm provides a mechanism to continuously accumulate relevance assessments over time and across users. It also provides a document representation modification function, or document representation learning …


Sharing The Big Apple : A Survey Study Of People, Place And Locatability, Samer Nadim Karam May 2005

Sharing The Big Apple : A Survey Study Of People, Place And Locatability, Samer Nadim Karam

Theses

Over the past half century social trends and new technologies have weakened local social ties and thus, the fabric of civil society itself. Mobile location-aware community systems offer one path to redress these problems by enhancing community cohesion and the formation of social capital by helping people to meet each other and coordinate their actions. However, little is known about the general population's desire and attitude towards these systems.

The design space described by the People-to-People-to-Geographical-Places Framework (P3-Framework), was used to guide a survey study of the impact of 'place' on people's social information needs and their willingness to share …


Tosa: A Near-Optimal Scheduling Algorithm For Multi-Channel Data Broadcast, Baihua Zheng, Xia Xu, Xing Jin, Dik Lun Lee May 2005

Tosa: A Near-Optimal Scheduling Algorithm For Multi-Channel Data Broadcast, Baihua Zheng, Xia Xu, Xing Jin, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Wireless broadcast is very suitable for delivering information to a large user population. In this paper, we concentrate on data allocation methods for multiple broadcast channels. To the best of our knowledge, this is the first allocation model that takes into the consideration of items' access frequencies, items' lengths. and bandwidth of different channels. We first derive the optimal average expected delay for multiple channels for the general case where data access frequencies, data sizes, and channel bandwidths can all be non-uniform. Second, we develop TOSA, a multi-channel allocation method that does not assume a uniform broadcast schedule for data …


An Ontological Approach To The Document Access Problem Of Insider Threat, Boanerges Aleman-Meza, Phillip Burns, Matthew Eavenson, Devanand Palanswami, Amit P. Sheth May 2005

An Ontological Approach To The Document Access Problem Of Insider Threat, Boanerges Aleman-Meza, Phillip Burns, Matthew Eavenson, Devanand Palanswami, Amit P. Sheth

Kno.e.sis Publications

Verification of legitimate access of documents, which is one aspect of the umbrella of problems in the Insider Threat category, is a challenging problem. This paper describes the research and prototyping of a system that takes an ontological approach, and is primarily targeted for use by theintelligence community. Our approach utilizes the notion of semantic associations and their discovery among a collection of heterogeneous documents. We highlight our contributions in (graphically) capturing the scope of the investigation assignment of an intelligence analyst by referring to classes and relationships of an ontology; in computing a measure of the relevance …


Semantic Web Services For N-Glycosylation Process, Satya S. Sahoo, Amit P. Sheth, William S. York, John A. Miller May 2005

Semantic Web Services For N-Glycosylation Process, Satya S. Sahoo, Amit P. Sheth, William S. York, John A. Miller

Kno.e.sis Publications

Glycomics is one of the many research efforts currently underway in the biosciences domain, which is characterized by high throughput data generated at multiple experimental stages. For example, analysis of N-glycosylation encompasses stages from cell-culture to peptide identification and quantification. Research groups across the world use diverse cell cultures, separation and spectroscopic techniques, and data identification, correlation and integration methodologies. Thus, data generated at different phases of the process by multiple groups are both structurally and functionally heterogeneous.


Dynamically Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang May 2005

Dynamically Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the results. This paper advocates context-awareness as a promising approach to enhance the performance of recommenders, and introduces a mechanism to realize this approach. We present a framework that separates the contextual concerns from the actual recommendation module, so that contexts can be readily shared across applications. More importantly, we devise a learning algorithm to dynamically identify the optimal set of contexts for a specific recommendation task and user. An extensive series of experiments has validated that our …


Secure Human Communications Based On Biometrics Signals, Yongdong Wu, Feng Bao, Robert H. Deng May 2005

Secure Human Communications Based On Biometrics Signals, Yongdong Wu, Feng Bao, Robert H. Deng

Research Collection School Of Computing and Information Systems

User authentication is the first and probably the most challenging step in achieving secure person-to-person communications. Most of the existing authentication schemes require communicating parties either share a secret/password or know each other's public key. In this paper we suggest a novel user authentication scheme that is easy to use and overcomes the requirements of sharing password or public keys. Our scheme allows two human users to perform mutual authentication and have secure communications over an open channel by exchanging biometrics signals (e. g., voice or video signals). In addition to user authentication, our scheme establishes a secret session key …


Event-Driven Document Selection For Terrorism, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Teng-Kwee Ong, Rohan Kumar Gunaratna May 2005

Event-Driven Document Selection For Terrorism, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Teng-Kwee Ong, Rohan Kumar Gunaratna

Research Collection School Of Computing and Information Systems

In this paper, we examine the task of extracting information about terrorism related events hidden in a large document collection. The task assumes that a terrorism related event can be described by a set of entity and relation instances. To reduce the amount of time and efforts in extracting these event related instances, one should ideally perform the task on the relevant documents only. We have therefore proposed some document selection strategies based on information extraction (IE) patterns. Each strategy attempts to select one document at a time such that the gain of event related instance information is maximized. Our …


Information Dissemination Via Wireless Broadcast, Baihua Zheng, Dik Lun Lee May 2005

Information Dissemination Via Wireless Broadcast, Baihua Zheng, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Unrestricted mobility adds a new dimension to data access methodology--- one that must be addressed before true ubiquity can be realized.


Dynamically-Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee-Hwa Pang May 2005

Dynamically-Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee-Hwa Pang

Research Collection School Of Computing and Information Systems

Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the results. This paper advocates context-awareness as a promising approach to enhance the performance of recommenders, and introduces a mechanism to realize this approach. We present a framework that separates the contextual concerns from the actual recommendation module, so that contexts can be readily shared across applications. More importantly, we devise a learning algorithm to dynamically identify the optimal set of contexts for a specific recommendation task and user. An extensive series of experiments has validated that our …


Mining Mobile Group Patterns: A Trajectory-Based Approach, San-Yih Hwang, Ying-Han Liu, Jeng-Kuen Chiu, Ee Peng Lim May 2005

Mining Mobile Group Patterns: A Trajectory-Based Approach, San-Yih Hwang, Ying-Han Liu, Jeng-Kuen Chiu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we present a group pattern mining approach to derive the grouping information of mobile device users based on a trajectory model. Group patterns of users are determined by distance threshold and minimum time duration. A trajectory model of user movement is adopted to save storage space and to cope with untracked or disconnected location data. To discover group patterns, we propose ATGP algorithm and TVG-growth that are derived from the Apriori and VG-growth algorithms respectively.


Web Services To Semantic Web Processes: Investigating Synergy Between Practice And Research, Amit P. Sheth Apr 2005

Web Services To Semantic Web Processes: Investigating Synergy Between Practice And Research, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.


Real-Time Business Intelligence In Multi-Agent Adaptive Supply Networks, Gavin Finnie, Jeffrey Barker Apr 2005

Real-Time Business Intelligence In Multi-Agent Adaptive Supply Networks, Gavin Finnie, Jeffrey Barker

Jeffrey Barker

The increasing speed and complexity of inter-organisational communication in supply networks requires effective automation. Multi-agent systems have been proposed as a possible solution. However, the information needs of the agent, particularly in responding to any variation from the norm, are similar to a human in the same position.

This paper reviews the concepts of Business Intelligence (BI) and Real-Time Enterprises (RTE) and looks at the need for BI in dynamic information management. A multi-agent framework is described and case-based reasoning investigated as a reasoning paradigm capable of responding to the need for business intelligence. A CBR approach is proposed with …


Bridging The Paradigm Gap With Rules For Owl, Jurgen Angele, Boris Motik, Rudi Studer, Pascal Hitzler Apr 2005

Bridging The Paradigm Gap With Rules For Owl, Jurgen Angele, Boris Motik, Rudi Studer, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Accelerated by the vision of the semantic web, semantic technologies have recently made significant advances. The underlying methods and paradigms are already being transferred to adjacent areas of research in artificial intelligence, knowledge management, and elsewhere. Textbooks explaining the foundations have appeared. Large national and international projects on the topic are under way.


Web Service Semantics - Wsdl-S, Rama Akkiraju, Joel Farrell, John A. Miller, Meenakshi Nagarajan, Amit P. Sheth, Kunal Verma Apr 2005

Web Service Semantics - Wsdl-S, Rama Akkiraju, Joel Farrell, John A. Miller, Meenakshi Nagarajan, Amit P. Sheth, Kunal Verma

Kno.e.sis Publications

The current WSDL standard operates at the syntactic level and lacks the semantic expressivity needed to represent the requirements and capabilities of Web Services. Semantics can improve software reuse and discovery, significantly facilitate composition of Web services and enable integrating legacy applications as part of business process integration. The Web Service Semantic s technical note defines a mechanism to associate semantic annotations with Web services that are described using Web Service Description Language (WSDL). It is conceptually based on, but a significant refinement in details of, the original WSDL-S proposal [WSDL-S] from the LSDIS laboratory at the University of Georgia. …


Information Technology (It) Appropriateness: The Contingency Theory Of “Fit” And It Implementation In Small And Medium Enterprises, Deepak Khazanchi Apr 2005

Information Technology (It) Appropriateness: The Contingency Theory Of “Fit” And It Implementation In Small And Medium Enterprises, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Publications

There is little doubt that advanced information and communication technologies (IT) arc changing the way businesses operate and conduct commerce. As the advent of a more secure Internet and new transmission standards makes it easier and cheaper for businesses to conduct inter-organizational commerce, it is incumbent upon SME managers to assess whether implementing new technologies such as Electronic Data Interchange (EDI) over the Internet, XML or web-based e-commerce is the "right thing to do" for their organizations. The key question implicit in this decision is addressed in this paper: "Under what conditions should businesses consider themselves likely candidates for (new) …


Personalization By Program Slicing, Saverio Perugini, Naren Ramakrishnan Apr 2005

Personalization By Program Slicing, Saverio Perugini, Naren Ramakrishnan

Computer Science Faculty Publications

Personalization involves customizing information access to the end-user. As any new area of computer science research it lacks formal models to guide the design of systems. In this paper, we present a modeling methodology, based on generative programming, for personalizing interactions with hierarchical websites. The methodology entails modeling a user’s interaction with a site in a program and applying program slicing to personalize the interaction. While preserving interactivity, this approach does not require the designer to anticipate all possible user interactions a priori and provide interfaces for each. Moreover, it provides a theoretical, systematic, and implementation-neutral way to design systems …


Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan Apr 2005

Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan

Research Collection School Of Computing and Information Systems

Gene expression data generated by DNA microarray experiments have provided a vast resource for medical diagnosis and disease understanding. Most prior work in analyzing gene expression data, however, focuses on predictive performance but not so much on deriving human understandable knowledge. This paper presents a systematic approach for learning and extracting rule-based knowledge from gene expression data. A class of predictive self-organizing networks known as Adaptive Resonance Associative Map (ARAM) is used for modelling gene expression data, whose learned knowledge can be transformed into a set of symbolic IF-THEN rules for interpretation. For dimensionality reduction, we illustrate how the system …


Mining Social Network From Spatio-Temporal Events, Hady Wirawan Lauw, Ee Peng Lim, Teck Tim Tan, Hwee Hwa Pang Apr 2005

Mining Social Network From Spatio-Temporal Events, Hady Wirawan Lauw, Ee Peng Lim, Teck Tim Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Knowing patterns of relationship in a social network is very useful for law enforcement agencies to investigate collaborations among criminals, for businesses to exploit relationships to sell products, or for individuals who wish to network with others. After all, it is not just what you know, but also whom you know, that matters. However, finding out who is related to whom on a large scale is a complex problem. Asking every single individual would be impractical, given the huge number of individuals and the changing dynamics of relationships. Recent advancement in technology has allowed more data about activities of individuals …


Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin Apr 2005

Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin

Research Collection School Of Computing and Information Systems

Relevance feedback has been shown as an important tool to boost the retrieval performance in content-based image retrieval. In the past decade, various algorithms have been proposed to formulate relevance feedback in contentbased image retrieval. Traditional relevance feedback techniques mainly carry out the learning tasks by focusing lowlevel visual features of image content with little consideration on log information of user feedback. However, from a long-term learning perspective, the user feedback log is one of the most important resources to bridge the semantic gap problem in image retrieval. In this paper we propose a novel technique to integrate the log …


Proactive Caching For Spatial Queries In Mobile Environments, Haibo Hu, Jianliang Xu, Wing Sing Wong, Baihua Zheng, Dik Lun Lee, Wang-Chien Lee Apr 2005

Proactive Caching For Spatial Queries In Mobile Environments, Haibo Hu, Jianliang Xu, Wing Sing Wong, Baihua Zheng, Dik Lun Lee, Wang-Chien Lee

Research Collection School Of Computing and Information Systems

Semantic caching enables mobile clients to answer spatial queries locally by storing the query descriptions together with the results. However, it supports only a limited number of query types, and sharing results among these types is difficult. To address these issues, we propose a proactive caching model which caches the result objects as well as the index that supports these objects as the results. The cached index enables the objects to be reused for all common types of queries. We also propose an adaptive scheme to cache such an index, which further optimizes the query response time for the best …


A Statistical Performance Model Of Homogeneous Raidb Clusters, Brandon Lamar Rogers Mar 2005

A Statistical Performance Model Of Homogeneous Raidb Clusters, Brandon Lamar Rogers

Theses and Dissertations

The continual growth of the Internet and e-commerce is driving demand for speed, reliability and processing power. With the rapid development and maturation of e-commerce, the need for a quick access to large amounts of information is steadily rising. Traditionally, database systems have been used for information storage and retrieval. However, with online auctions, rapid Internet searches, and data archival, the need for more powerful database systems is also growing. One type of distributed database is called Redundant Arrays of Inexpensive Databases (RAIDb). RAIDb clusters are middleware-driven to promote interoperability and portability. RAIDb clusters allow for multiple levels of data …


An Information Extraction Approach To Reorganizing And Summarizing Specifications, Krishnaprasad Thirunarayan, Aaron Berkovich, Dan Z. Sokol Mar 2005

An Information Extraction Approach To Reorganizing And Summarizing Specifications, Krishnaprasad Thirunarayan, Aaron Berkovich, Dan Z. Sokol

Kno.e.sis Publications

Materials and Process Specifications are complex semi-structured documents containing numeric data, text, and images. This article describes a coarse-grain extraction technique to automatically reorganize and summarize spec content. Specifically, a strategy for semantic-markup, to capture content within a semantic ontology, relevant to semi-automatic extraction, has been developed and experimented with. The working prototypes were built in the context of Cohesia's existing software infrastructure, and use techniques from Information Extraction, XML technology, etc.


Divide-And-Approximate: A Novel Constraint Push Strategy For Iceberg Cube Mining, Ke Wang, Yuelong Jiang, Jeffrey Xu Yu, Guozhu Dong, Jiawei Han Mar 2005

Divide-And-Approximate: A Novel Constraint Push Strategy For Iceberg Cube Mining, Ke Wang, Yuelong Jiang, Jeffrey Xu Yu, Guozhu Dong, Jiawei Han

Kno.e.sis Publications

The iceberg cube mining computes all cells v, corresponding to GROUP BY partitions, that satisfy a given constraint on aggregated behaviors of the tuples in a GROUP BY partition. The number of cells often is so large that the result cannot be realistically searched without pushing the constraint into the search. Previous works have pushed antimonotone and monotone constraints. However, many useful constraints are neither antimonotone nor monotone. We consider a general class of aggregate constraints of the form f(v)θσ, where f is an arithmetic function of SQL-like aggregates and θ is one of <, ≤, ≥, > . We propose a …


Scheduling Queries To Improve The Freshness Of A Website, Haifeng Liu, Wee-Keong Ng, Ee Peng Lim Mar 2005

Scheduling Queries To Improve The Freshness Of A Website, Haifeng Liu, Wee-Keong Ng, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The World Wide Web is a new advertising medium that corporations use to increase their exposure to consumers. Very large websites whose content is derived from a source database need to maintain a freshness that reflects changes that are made to the base data. This issue is particularly significant for websites that present fast-changing information such as stock-exchange information and product information. In this article, we formally define and study the freshness of a website that is refreshed by a scheduled set of queries that fetch fresh data from the databases. We propose several online-scheduling algorithms and compare the performance …