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Articles 3151 - 3180 of 3560

Full-Text Articles in Databases and Information Systems

Hot Event Detection And Summarization By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo Jul 2005

Hot Event Detection And Summarization By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for hot event detection and summarization of news videos. The approach is mainly based on two graph algorithms: optimal matching (OM) and normalized cut (NC). Initially, OM is employed to measure the visual similarity between all pairs of events under the one-to-one mapping constraint among video shots. Then, news events are represented as a complete weighted graph and NC is carried out to globally and optimally partition the graph into event clusters. Finally, based on the cluster size and globality of events, hot events can be automatically detected and selected as the summaries of …

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Co-Clustering Of Time-Evolving News Story With Transcript And Keyframe, Xiao Wu, Chong-Wah Ngo, Qing Li Jul 2005

Co-Clustering Of Time-Evolving News Story With Transcript And Keyframe, Xiao Wu, Chong-Wah Ngo, Qing Li

Research Collection School Of Computing and Information Systems

This paper presents techniques in clustering the same-topic news stories according to event themes. We model the relationship of stories with textual and visual concepts under the representation of bipartite graph. The textual and visual concepts are extracted respectively from speech transcripts and keyframes. Co-clustering algorithm is employed to exploit the duality of stories and textual-visual concepts based on spectral graph partitioning. Experimental results on TRECVID-2004 corpus show that the co-clustering of news stories with textual-visual concepts is significantly better than the co-clustering with either textual or visual concept alone.

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Social Network Discovery By Mining Spatio-Temporal Events, Hady Lauw, Ee Peng Lim, Hwee Hwa Pang, Teck-Tim Tan Jul 2005

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

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 …

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An Informatization Of Society Approach To E-Government: Analyzing Singapore’S E-Government Efforts, Calvin M. L. Chan, Yi Meng Lau Jul 2005

An Informatization Of Society Approach To E-Government: Analyzing Singapore’S E-Government Efforts, Calvin M. L. Chan, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Despite the much publicized benefits of e-government, many countries are experiencing difficulty in yielding success in their e-government initiatives. Studies which adopt the national e-government initiatives as the unit of analysis remain largely rare. This paper aspires to provide an analysis of Singapore’s widely acclaimed success in the e-government effort at the national level to allow other countries to learn and gain from its experience. Using the ‘Conceptual Framework for the Informatization of Society’ in facilitating the data analysis, implications are drawn to offer insights for the considerations of e-government practitioners. Theoretical implications are also derived through positing that the …

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A Semi-Supervised Active Learning Framework For Image Retrieval, Steven Hoi, Michael R. Lyu Jun 2005

A Semi-Supervised Active Learning Framework For Image Retrieval, Steven Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Although recent studies have shown that unlabeled data are beneficial to boosting the image retrieval performance, very few approaches for image retrieval can learn with labeled and unlabeled data effectively. This paper proposes a novel semi-supervised active learning framework comprising a fusion of semi-supervised learning and support vector machines. We provide theoretical analysis of the active learning framework and present a simple yet effective active learning algorithm for image retrieval. Experiments are conducted on real-world color images to compare with traditional methods. The promising experimental results show that our proposed scheme significantly outperforms the previous approaches.

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Knowledge Management Mechanisms Of Financial Service Sites, Fiona Fui-Hoon Nah, Keng Siau, Y. Tian Jun 2005

Knowledge Management Mechanisms Of Financial Service Sites, Fiona Fui-Hoon Nah, Keng Siau, Y. Tian

Research Collection School Of Computing and Information Systems

How can we effectively acquire, use, and manage knowledge via the Web?

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Conceptual Partitioning: An Efficient Method For Continuous Nearest Neighbor Monitoring, Kyriakos Mouratidis, Marios Hadjieleftheriou, Dimitris Papadias Jun 2005

Conceptual Partitioning: An Efficient Method For Continuous Nearest Neighbor Monitoring, Kyriakos Mouratidis, Marios Hadjieleftheriou, Dimitris Papadias

Research Collection School Of Computing and Information Systems

Given a set of objects P and a query point q, a k nearest neighbor (k-NN) query retrieves the k objects in P that lie closest to q. Even though the problem is well-studied for static datasets, the traditional methods do not extend to highly dynamic environments where multiple continuous queries require real-time results, and both objects and queries receive frequent location updates. In this paper we propose conceptual partitioning (CPM), a comprehensive technique for the efficient monitoring of continuous NN queries. CPM achieves low running time by handling location updates only from objects that fall in the vicinity of …

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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 …

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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.

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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 …

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Aggregate Nearest Neighbor Queries In Spatial Databases, Dimitris Papadias, Yufei Tao, Kyriakos Mouratidis, Chun Kit Hui Jun 2005

Aggregate Nearest Neighbor Queries In Spatial Databases, Dimitris Papadias, Yufei Tao, Kyriakos Mouratidis, Chun Kit Hui

Research Collection School Of Computing and Information Systems

Given two spatial datasets P (e.g., facilities) and Q (queries), an aggregate nearest neighbor (ANN) query retrieves the point(s) of P with the smallest aggregate distance(s) to points in Q. Assuming, for example, n users at locations q1,...qn, an ANN query outputs the facility p belongs to P that minimizes the sum of distances |pqi| for 1 is less than or equal to i is less than or equal to n that the users have to travel in order to meet there. Similarly, another ANN query may report the point p belongs to P that minimizes the maximum distance that …

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Dsi: A Fully Distributed Spatial Index For Wireless Data Broadcast, Wang-Chien Lee, Baihua Zheng Jun 2005

Dsi: A Fully Distributed Spatial Index For Wireless Data Broadcast, Wang-Chien Lee, Baihua Zheng

Research Collection School Of Computing and Information Systems

Recent announcement of the MSN Direct Service has demonstrated the feasibility and industrial interest in utilizing wireless broadcast for pervasive information services. To support location-based services in wireless data broadcast systems, a distributed spatial index (called DSI) is proposed in this paper. DSI is highly efficient because it has a linear yet fully distributed structure that facilitates multiple search paths to be naturally mixed together by sharing links. Moreover, DSI is very resilient in error-prone wireless communication environments. Search algorithms for two classical location-based queries, window queries and kNN queries, based on DSI are presented. Performance evaluation of DSI shows …

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Synthesizing E-Government Stage Models – A Meta-Synthesis Based On Meta-Ethnography Approach, Keng Siau, Y. Long May 2005

Synthesizing E-Government Stage Models – A Meta-Synthesis Based On Meta-Ethnography Approach, Keng Siau, Y. Long

Research Collection School Of Computing and Information Systems

The growing interest in e-government raises the question of stages in e-government development. A few stage models for e-government have been proposed. Without a common e-government stage model, different research in e-government may be based on different stage models. This presents a difficulty in comparing and understanding different research results. In this research, we synthesize the existing e-government stage models so that there is a common frame of reference for researchers and practitioners in the area.

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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 …

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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.

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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 …

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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 …

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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.

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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 …

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Synthesizing E-Government Stage Models – A Meta-Synthesis Based On Meta-Ethnography Approach, Keng Siau, Y. Long May 2005

Synthesizing E-Government Stage Models – A Meta-Synthesis Based On Meta-Ethnography Approach, Keng Siau, Y. Long

Research Collection School Of Computing and Information Systems

The growing interest in e-government raises the question of stages in e-government development. A few stage models for e-government have been proposed. Without a common e-government stage model, different research in e-government may be based on different stage models. This presents a difficulty in comparing and understanding different research results. In this research, we synthesize the existing e-government stage models so that there is a common frame of reference for researchers and practitioners in the area.

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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 …

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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 …

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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 …

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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 …

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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 …

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Ais Sighci Position Paper, Dennis Galletta, Ping Zhang, Fiona Fui-Hoon Nah Apr 2005

Ais Sighci Position Paper, Dennis Galletta, Ping Zhang, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The upcoming ACM SIGCHI Development Consortium is aimed at meeting the needs of multidisciplinary professionals that must choose among a variety of professional associations and their events. The position of AIS' (Association for Information Systems) SIGHCI is that the main problem lies in the deep chasms that separate the literatures of the related disciplines, and the solution is to provide an umbrella organization that enables a more organized federation of disciplines, groups, and associations. Problems identified include differences in terminology, competition for scarce resources, differences in how publications in various outlets are valued, and confusion about where should be the …

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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 …

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Evaluation Of Mpeg-4 Ipmp Extension, Hwee Hwa Pang, Yongdong Wu Mar 2005

Evaluation Of Mpeg-4 Ipmp Extension, Hwee Hwa Pang, Yongdong Wu

Research Collection School Of Computing and Information Systems

MPEG-4 IPMPX (intellectual property management and protection extension) is the latest ISO standard which provides a flexible framework for protecting MPEG streams. The message mechanism of IPMPX enables interoperability among IPMPX-compliant devices no matter which protection methods are embedded. This paper highlights several problems in the message syntax of IPMPX: the tool delivery message IPMP_ToolES_AU is vulnerable to network attack, the authentication message IMP_Mutual_Authentication is incapable of defending against forgery attack, and the configuration message IPMP_SelectiveDecrptionInit is ambiguous and redundant. We propose a number of remedies to those problems, which can be incorporated into a corrigenda to improve the present …

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The Value Of Mobile Applications: A Utility Company Study, Fiona Fui-Hoon Nah, Keng Siau, Hong Sheng Feb 2005

The Value Of Mobile Applications: A Utility Company Study, Fiona Fui-Hoon Nah, Keng Siau, Hong Sheng

Research Collection School Of Computing and Information Systems

The value proposition of mobile applications i.e. the net value of the benefits and costs associated with the adoption and adaptation of mobile applications is discussed. A means-ends network that depicts the fundamental relationships among the objectives such as efficiency, effectiveness, customer satisfaction, security, cost, and employee acceptance, was developed. The network is useful to researchers as it highlights the issues, concerns, and values of mobile applications. The network help the managers and practitioners to achieve their companies' objectives of implementing mobile and wireless applications.

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Systems Analysis And Design: Should We Be Researching What We Teach?, A. Bajaj, D. Batra, A. Hevner, J. Parsons, Keng Siau Jan 2005

Systems Analysis And Design: Should We Be Researching What We Teach?, A. Bajaj, D. Batra, A. Hevner, J. Parsons, Keng Siau

Research Collection School Of Computing and Information Systems

A guiding premise of academic scholarship is that knowledge gained from first-hand research experience is disseminated to students via the classroom. However, that valuable connection is lost when professors are not researching what they teach. In this paper, we explore issues of mismatch between teaching and research in the Information Systems (IS) discipline. Specifically, while systems analysis and design (SA&D) is an integral topic in IS curricula, this topic is the research specialty of few IS professors. This situation is reflected by the low number of research publications in this area; particularly in the leading mainstream IS journals. We characterize …

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