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Databases and Information Systems

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Articles 661 - 690 of 809

Full-Text Articles in Numerical Analysis and Scientific Computing

Authenticating Multi-Dimensional Query Results In Data Publishing, Weiwei Cheng, Hwee Hwa Pang, Kian-Lee Tan Jul 2006

Authenticating Multi-Dimensional Query Results In Data Publishing, Weiwei Cheng, Hwee Hwa Pang, 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. This paper introduces a mechanism for users to verify that their query answers on a multi-dimensional dataset are correct, in the sense of being complete (i.e., no qualifying data points are omitted) and authentic (i.e., all the result values originated from the owner). Our approach is to add authentication information into a spatial data structure, by constructing certified chains on the points within each partition, as well as …

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Interacting With Web Hierarchies, Saverio Perugini, Naren Ramakrishnan Jun 2006

Interacting With Web Hierarchies, Saverio Perugini, Naren Ramakrishnan

Computer Science Faculty Publications

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

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Exploiting Domain Structure For Named Entity Recognition, Jing Jiang, Chengxiang Zhai Jun 2006

Exploiting Domain Structure For Named Entity Recognition, Jing Jiang, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

Named Entity Recognition (NER) is a fundamental task in text mining and natural language understanding. Current approaches to NER (mostly based on supervised learning) perform well on domains similar to the training domain, but they tend to adapt poorly to slightly different domains. We present several strategies for exploiting the domain structure in the training data to learn a more robust named entity recognizer that can perform well on a new domain. First, we propose a simple yet effective way to automatically rank features based on their generalizabilities across domains. We then train a classifier with strong emphasis on the …

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On In-Network Synopsis Join Processing For Sensor Networks, Hai Yu, Ee Peng Lim, Jun Zhang May 2006

On In-Network Synopsis Join Processing For Sensor Networks, Hai Yu, Ee Peng Lim, Jun Zhang

Research Collection School Of Computing and Information Systems

The emergence of sensor networks enables applications that deploy sensors to collaboratively monitor environment and process data collected. In some scenarios, we are interested in using join queries to correlate data stored in different regions of a sensor network, where the data volume is large, making it prohibitive to transmit all data to a central server for joining. In this paper, we present an in-network synopsis join strategy for evaluating join queries in sensor networks with communication efficiency. In this strategy, we prune data that do not contribute to the join results in the early stage of the join processing, …

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Discovering Causal Dependencies In Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang May 2006

Discovering Causal Dependencies In Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Mobile context-aware recommender systems face unique challenges in acquiring context. Resource limitations make minimizing context acquisition a practical need, while the uncertainty inherent to the mobile environment makes missing context values a major concern. This paper introduces a scalable mechanism based on Bayesian network learning in a tiered context model to overcome both of these challenges. Extensive experiments on a restaurant recommender system showed that our mechanism can accurately discover causal dependencies among context, thereby enabling the effective identification of the minimal set of important context for a specific user and task, as well as providing highly accurate recommendations even …

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Searching Substructures With Superimposed Distance, Xifeng Yan, Feida Zhu, Jiawei Han, Philip S. Yu Apr 2006

Searching Substructures With Superimposed Distance, Xifeng Yan, Feida Zhu, Jiawei Han, Philip S. Yu

Research Collection School Of Computing and Information Systems

Efficient indexing techniques have been developed for the exact and approximate substructure search in large scale graph databases. Unfortunately, the retrieval problem of structures with categorical or geometric distance constraints is not solved yet. In this paper, we develop a method called PIS (Partition-based Graph Index and Search) to support similarity search on substructures with superimposed distance constraints. PIS selects discriminative fragments in a query graph and uses an index to prune the graphs that violate the distance constraints. We identify a criterion to distinguish the selectivity of fragments in multiple graphs and develop a partition method to obtain a …

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Fisa: Feature-Based Instance Selection For Imbalanced Text Classification, Aixin Sun, Ee Peng Lim, Boualem Benatallah, Mahbub Hassan Apr 2006

Fisa: Feature-Based Instance Selection For Imbalanced Text Classification, Aixin Sun, Ee Peng Lim, Boualem Benatallah, Mahbub Hassan

Research Collection School Of Computing and Information Systems

Support Vector Machines (SVM) classifiers are widely used in text classification tasks and these tasks often involve imbalanced training. In this paper, we specifically address the cases where negative training documents significantly outnumber the positive ones. A generic algorithm known as FISA (Feature-based Instance Selection Algorithm), is proposed to select only a subset of negative training documents for training a SVM classifier. With a smaller carefully selected training set, a SVM classifier can be more efficiently trained while delivering comparable or better classification accuracy. In our experiments on the 20-Newsgroups dataset, using only 35% negative training examples and 60% learning …

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In-Network Processing Of Nearest Neigbor Queries For Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim Apr 2006

In-Network Processing Of Nearest Neigbor Queries For Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Wireless sensor networks have been widely used for civilian and military applications, such as environmental monitoring and vehicle tracking. The sensor nodes in the network have the abilities to sense, store, compute and communicate. To enable object tracking applications, spatial queries such as nearest neighbor queries are to be supported in these networks. The queries can be injected by the user at any sensor node. Due to the limited power supply for sensor nodes, energy efficiency is the major concern in query processing. Centralized data storage and query processing schemes do not favor energy efficiency. In this paper, we propose …

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Sgpm: Static Group Pattern Mining Using Apriori-Like Sliding Window, John Goh, David Taniar, Ee Peng Lim Apr 2006

Sgpm: Static Group Pattern Mining Using Apriori-Like Sliding Window, John Goh, David Taniar, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Mobile user data mining is a field that focuses on extracting interesting pattern and knowledge out from data generated by mobile users. Group pattern is a type of mobile user data mining method. In group pattern mining, group patterns from a given user movement database is found based on spatio-temporal distances. In this paper, we propose an improvement of efficiency using area method for locating mobile users and using sliding window for static group pattern mining. This reduces the complexity of valid group pattern mining problem. We support the use of static method, which uses areas and sliding windows instead …

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Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini Jan 2006

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

Computer Science Faculty Publications

We demonstrate the use of two user interfaces for interacting with web hierarchies. One uses the dependencies underlying a hierarchy to perform real-time query expansion and, in this way, acts as an in situ feedback mechanism. The other enables the user to cascade the output from one interaction to the input of another, and so on, and, in this way, supports procedural information-seeking tasks without disrupting the flow of interaction.

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Information Assurance Through Binary Vulnerability Auditing, William B. Kimball, Saverio Perugini Jan 2006

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

Computer Science Faculty Publications

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 …

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Efficient Mining Of Group Patterns From User Movement Data, Yida Wang, Ee Peng Lim, San-Yih Hwang Jan 2006

Efficient Mining Of Group Patterns From User Movement Data, Yida Wang, Ee Peng Lim, San-Yih Hwang

Research Collection School Of Computing and Information Systems

In this paper, we present a new approach to derive groupings of mobile users based on their movement data. We assume that the user movement data are collected by logging location data emitted from mobile devices tracking users. We formally define group pattern as a group of users that are within a distance threshold from one another for at least a minimum duration. To mine group patterns, we first propose two algorithms, namely AGP and VG-growth. In our first set of experiments, it is shown when both the number of users and logging duration are large, AGP and VG-growth are …

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Grid-Partition Index: A Hybrid Approach To Nearest-Neighbor Queries In Wireless Location-Based Services, Baihua Zheng, Jianliang Xu, Wang-Chien Lee, Dik Lun Lee Jan 2006

Grid-Partition Index: A Hybrid Approach To Nearest-Neighbor Queries In Wireless Location-Based Services, Baihua Zheng, Jianliang Xu, Wang-Chien Lee, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Traditional nearest-neighbor (NN) search is based on two basic indexing approaches: object-based indexing and solution-based indexing. The former is constructed based on the locations of data objects: using some distance heuristics on object locations. The latter is built on a precomputed solution space. Thus, NN queries can be reduced to and processed as simple point queries in this solution space. Both approaches exhibit some disadvantages, especially when employed for wireless data broadcast in mobile computing environments. In this paper, we introduce a new index method, called the grid-partition index, to support NN search in both ondemand access and periodic broadcast …

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In-Network Join Processing For Sensor Networks, Hai Yu, Ee Peng Lim, Jun Zhang Jan 2006

In-Network Join Processing For Sensor Networks, Hai Yu, Ee Peng Lim, Jun Zhang

Research Collection School Of Computing and Information Systems

Recent advances in hardware and wireless technologies have led to sensor networks consisting of large number of sensors capable of gathering and processing data collectively. Query processing on these sensor networks has to consider various inherent constraints. While simple queries such as select and aggregate queries in wireless sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. In this paper, we present a synopsis join strategy for evaluating join queries in sensor networks with communication efficiency. In this strategy, instead of directly joining two relations distributed in a sensor …

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Webarc: Website Archival Using A Structured Approach, Ee Peng Lim, Maria Marissa Dec 2005

Webarc: Website Archival Using A Structured Approach, Ee Peng Lim, Maria Marissa

Research Collection School Of Computing and Information Systems

Website archival refers to the task of monitoring and storing snapshots of website(s) for future retrieval and analysis. This task is particularly important for websites that have content changing over time with older information constantly overwritten by newer one. In this paper, we propose WEBARC as a set of software tools to allow users to construct a logical structure for a website to be archived. Classifiers are trained to. determine relevant web pages and their categories, and subsequently used in website downloading. The archival schedule can be specified and executed by a scheduler. A website viewer is also developed to …

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A Threshold-Based Algorithm For Continuous Monitoring Of K Nearest Neighbors, Kyriakos Mouratidis, Dimitris Papadias, Spiridon Bakiras, Yufei Tao Nov 2005

A Threshold-Based Algorithm For Continuous Monitoring Of K Nearest Neighbors, Kyriakos Mouratidis, Dimitris Papadias, Spiridon Bakiras, Yufei Tao

Research Collection School Of Computing and Information Systems

Assume a set of moving objects and a central server that monitors their positions over time, while processing continuous nearest neighbor queries from geographically distributed clients. In order to always report up-to-date results, the server could constantly obtain the most recent position of all objects. However, this naïve solution requires the transmission of a large number of rapid data streams corresponding to location updates. Intuitively, current information is necessary only for objects that may influence some query result (i.e., they may be included in the nearest neighbor set of some client). Motivated by this observation, we present a threshold-based algorithm …

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Query Processing In Spatial Databases Containing Obstacles, Jun Zhang, Dimitris Papadias, Kyriakos Mouratidis, Manli Zhu Nov 2005

Query Processing In Spatial Databases Containing Obstacles, Jun Zhang, Dimitris Papadias, Kyriakos Mouratidis, Manli Zhu

Research Collection School Of Computing and Information Systems

Despite the existence of obstacles in many database applications, traditional spatial query processing assumes that points in space are directly reachable and utilizes the Euclidean distance metric. In this paper, we study spatial queries in the presence of obstacles, where the obstructed distance between two points is defined as the length of the shortest path that connects them without crossing any obstacles. We propose efficient algorithms for the most important query types, namely, range search, nearest neighbours, e-distance joins, closest pairs and distance semi-joins, assuming that both data objects and obstacles are indexed by R-trees. The effectiveness of the proposed …

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Accurately Extracting Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai Nov 2005

Accurately Extracting Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

In this paper, we present a principled method for accurately extracting coherent relevant passages of variable lengths using HMMs. We show that with appropriate parameter estimation, the HMM method outperforms a number of strong baseline methods on two data sets.

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Dsim: A Distance-Based Indexing Method For Genomic Sequences, Xia Cao, Beng-Chin Ooi, Hwee Hwa Pang, Kian-Lee Tan, Anthony K. H. Tung Oct 2005

Dsim: A Distance-Based Indexing Method For Genomic Sequences, Xia Cao, Beng-Chin Ooi, Hwee Hwa Pang, Kian-Lee Tan, Anthony K. H. Tung

Research Collection School Of Computing and Information Systems

In this paper, we propose a Distance-based Sequence Indexing Method (DSIM) for indexing and searching genome databases. Borrowing the idea of video compression, we compress the genomic sequence database around a set of automatically selected reference words, formed from high-frequency data substrings and substrings in past queries. The compression captures the distance of each non-reference word in the database to some reference word. At runtime, a query is processed by comparing its substrings with the compressed data strings, through their distances to the reference words. We also propose an efficient scheme to incrementally update the reference words and the compressed …

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On Organizing And Accessing Geospatial And Georeferenced Web Resources Using The G-Portal System, Zehua Liu, Ee Peng Lim, Yin-Leng Theng, Dion Hoe-Lian Goh, Wee-Keong Ng Sep 2005

On Organizing And Accessing Geospatial And Georeferenced Web Resources Using The G-Portal System, Zehua Liu, Ee Peng Lim, Yin-Leng Theng, Dion Hoe-Lian Goh, Wee-Keong Ng

Research Collection School Of Computing and Information Systems

In order to organise and manage geospatial and georeferenced information on the Web making them convenient for searching and browsing, a digital portal known as G-Portal has been designed and implemented. Compared to other digital libraries, G-Portal is unique for several of its features. It maintains metadata resources in XML with flexible resource schemas. Logical groupings of metadata resources as projects and layers are possible to allow the entire metadata collection to be partitioned differently for users with different information needs. These metadata resources can be displayed in both the classification-based and map-based interfaces provided by G-Portal. G-Portal further incorporates …

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Managing Geography Learning Objects Using Personalized Project Spaces In G-Portal, Dion Hoe-Lian Goh, Aixin Sun, Wenbo Zong, Dan Wu, Ee Peng Lim, Yin-Leng Theng, John Hedberg, Chew-Hung Chang Sep 2005

Managing Geography Learning Objects Using Personalized Project Spaces In G-Portal, Dion Hoe-Lian Goh, Aixin Sun, Wenbo Zong, Dan Wu, Ee Peng Lim, Yin-Leng Theng, John Hedberg, Chew-Hung Chang

Research Collection School Of Computing and Information Systems

The personalized project space is an important feature in G-Portal that supports individual and group learning activities. Within such a space, its owner can create, delete, and organize metadata referencing learning objects on the Web. Browsing and querying are among the functions provided to access the metadata. In addition, new schemas can be added to accommodate metadata of diverse attribute sets. Users can also easily share metadata across different projects using a “copy-and-paste” approach. Finally, a viewer to support offline viewing of personalized project content is also provided.

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Constrained Shortest Path Computation, Manolis Terrovitis, Spiridon Bakiras, Dimitris Papadias, Kyriakos Mouratidis Aug 2005

Constrained Shortest Path Computation, Manolis Terrovitis, Spiridon Bakiras, Dimitris Papadias, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

This paper proposes and solves a-autonomy and k-stops shortest path problems in large spatial databases. Given a source s and a destination d, an aautonomy query retrieves a sequence of data points connecting s and d, such that the distance between any two consecutive points in the path is not greater than a. A k-stops query retrieves a sequence that contains exactly k intermediate data points. In both cases our aim is to compute the shortest path subject to these constraints. Assuming that the dataset is indexed by a data-partitioning method, the proposed techniques initially compute a sub-optimal path by …

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Evaluation Criteria For Information Systems Development Methodologies, Keng Siau, Xin Tan Aug 2005

Evaluation Criteria For Information Systems Development Methodologies, Keng Siau, Xin Tan

Research Collection School Of Computing and Information Systems

The evaluation of information systems development methodologies is becoming increasingly important. The lack of a commonly acceptable set of criteria for evaluation, however, hinders aggregating knowledge from field studies. Our study attempts to fill the gap. To reduce the effects of subjectivity, we surveyed the opinions of a group (28) of experienced IS researchers. Fifty-one criteria were generated from the research participants. A systematic content analysis technique will be applied for grouping the unique criteria into general categories. Upon completion, our study can make both academic and practical contributions in evaluating ISD methodologies.

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Geogdl: A Web-Based Approach To Geography Examination, Ee Peng Lim, Dion Hoe-Lian Goh, Yin-Leng Theng Aug 2005

Geogdl: A Web-Based Approach To Geography Examination, Ee Peng Lim, Dion Hoe-Lian Goh, Yin-Leng Theng

Research Collection School Of Computing and Information Systems

The traditional educational approach with students as passive recipients has been the subject of criticism. A constructivist learner-centered approach towards education has been argued to produce greater internalization and application of knowledge compared to the traditional teacher-centered, transmission-oriented approach. Nevertheless, contemporary instructional design models argue for the use and integration of both approaches especially in complex learning tasks. This paper describes GeogDL, a Web-based application developed above a digital library of geographical resources for Singapore students preparing to take a national examination in geography. GeogDL is unique in that it not only provides an environment for active learning, it also …

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Medoid Queries In Large Spatial Databases, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou Aug 2005

Medoid Queries In Large Spatial Databases, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou

Research Collection School Of Computing and Information Systems

Assume that a franchise plans to open k branches in a city, so that the average distance from each residential block to the closest branch is minimized. This is an instance of the k-medoids problem, where residential blocks constitute the input dataset and the k branch locations correspond to the medoids. Since the problem is NP-hard, research has focused on approximate solutions. Despite an avalanche of methods for small and moderate size datasets, currently there exists no technique applicable to very large databases. In this paper, we provide efficient algorithms that utilize an existing data-partition index to achieve low CPU …

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Web Mining - The Ontology Approach, Ee Peng Lim, Aixin Sun Aug 2005

Web Mining - The Ontology Approach, Ee Peng Lim, Aixin Sun

Research Collection School Of Computing and Information Systems

The World Wide Web today provides users access to extremely large number of Web sites many of which contain information of education and commercial values. Due to the unstructured and semi-structured nature of Web pages and the design idiosyncrasy of Web sites, it is a challenging task to develop digital libraries for organizing and managing digital content from the Web. Web mining research, in its last 10 years, has on the other hand made significant progress in categorizing and extracting content from the Web. In this paper, we represent ontology as a set of concepts and their inter-relationships relevant to …

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Wmxml: A System For Watermarking Xml Data, Xuan Zhou, Hwee Hwa Pang, Kian-Lee Tan, Dhruv Mangla Aug 2005

Wmxml: A System For Watermarking Xml Data, Xuan Zhou, Hwee Hwa Pang, Kian-Lee Tan, Dhruv Mangla

Research Collection School Of Computing and Information Systems

As increasing amount of data is published in the form of XML, copyright protection of XML data is becoming an important requirement for many applications. While digital watermarking is a widely used measure to protect digital data from copyright offences, the complex and flexible construction of XML data poses a number of challenges to digital watermarking, such as re-organization and alteration attacks. To overcome these challenges, the watermarking scheme has to be based on the usability of data and the underlying semantics like key attributes and functional dependencies. In this paper, we describe WmXML, a system for watermarking XML documents. …

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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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Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao Jun 2005

Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao

Computer Science Faculty Publications

Clustering is well-suited for Web mining by automatically organizing Web pages into categories, each of which contains Web pages having similar contents. However, one problem in clustering is the lack of general methods to automatically determine the number of categories or clusters. For the Web domain in particular, currently there is no such method suitable for Web page clustering. In an attempt to address this problem, we discover a constant factor that characterizes the Web domain, based on which we propose a new method for automatically determining the number of clusters in Web page data sets. We discover that the …

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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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