38524318
Making Sense of Search Results by Automatic Web-page Classifications
This paper reports the development of a system for automatically organizing Internet web pages into meaningful categories. The aim of the system is to allow Internet users to find useful information in less time. The current problem with using the Internet is how to find the information that we need. With the explosive growth in the Internet, the information overload situation is getting worse. The proposed system automatically classifies web pages based on three types of information: (1) The system analyzes organizational information among web pages (inter-web-page relationship), such as an URL and links within a web page. (2) It analyzes the meta-web-page information such as data contained in META tags and formatting data of a web page. And (3), it analyzes web-page-content information such as keywords and phrases in the content of a web page. Our results show that combining all three types of information provides better accuracy.
10179927
Automatic web page classification in a dynamic and hierarchical way
Automatic classification of web pages is an effective way to deal with the difficulty of retrieving information from the Internet. Although there are many automatic classification algorithms and systems that have been proposed, most of them ignore the conflict between the fixed number of categories and the growing number of web pages going into the system. They also require searching through all existing categories to make any classification. We propose a dynamic and hierarchical classification system that is capable of adding new categories as required, organizing the web pages into a tree structure, and classifying web pages by searching through only one path of the tree structure. Our test results show that our proposed single-path search technique reduces the search complexity and increases the accuracy by 6% comparing to related algorithms. Our dynamic-category expansion technique also achieves satisfying results on adding new categories into our system as required.
11850990
Network Traffic Reduction by Hypertext Compression
This paper proposes a three-step process to reduce the size of hypertext documents for reducing the network traffic on the Internet. With the explosive growth in the number of users on the Internet, the bandwidth demand has grown tremendously. Before the improvement of network infrastructures can meet the demand, this paper addresses the problem by reducing the size of HTML documents that currently occupies majority of the network traffic on the Internet. The proposed process consists of three steps: (1) shrinking HTML documents by removing data that will not alter the appearance and the function, (2) encoding HTML documents by representing most frequent used tags and words with single bytes, and (3) compressing HTML documents by using standard compression utilities. Our test results show that the proposed process achieves a reduction ratio of 81% on average. We also developed a browser plug-in program that provides transparent access for the users when viewing the reduced-size HTML documents. With the plug-in program, the users will not see any differences when viewing the reduced-sized HTML documents comparing to the original ones. They will, however, experience a reduction in retrieval latency on average of 15%.
8998832
Document Classifications based on Word Semantic Hierarchies
In this paper we proposed to automatically classify documents based on the meanings of words and the relationships between groups of meanings or concepts. Our proposed classification algorithm builds on the word structures provided by WordNet, which not only arranges words into groups of synonyms, called Synsets, but also arranges the Synsets into hierarchies representing the relationships between concepts. Most existing methods classify text documents based on the number of occurrences of words and some based on Synsets. Our approach goes one step further by using not only word occurrences and Synsets but also the relationships between Synsets. We also proposed a sense-based document representation based on the semantic hierarchies provided by WordNet. To classify a document, our approach extracts words occurred in the document and uses them to increase the weight of the Synsets corresponding to the words. Words with same meanings will increase the weight of their corresponding Synsets. As a result, we count the occurrences of senses. We also propagate the weight of a Synset upward to its related Synsets in the hierarchies and thus capture the relationships between concepts. In comparing to previous research, our approach increases the classification accuracy by 14%.
7584097
An Adaptive Web Cache Access Predictor Using Neural Network
This paper presents a novel approach to successfully predict Web pages that are most likely to be re-accessed in a given period of time. We present the design of an intelligent predictor that can be implemented on a Web server to guide caching strategies. Our approach is adaptive and learns the changing access patterns of pages in a Web site. The core of our predictor is a neural network that uses a backpropagation learning rule. We present results of the application of this predictor on static data using log files; it can be extended to learn the distribution of live Web page access patterns. Our simulations show fast learning, uniformly good prediction, and up to 82% correct prediction for the following six months based on a one-day training data. This long-range prediction accuracy is attributed to the static structure of the test Web site.
1825969
Agent space architecture for search engines
The future of computing is moving from individual processing units to communities of self organizing agents. In This work we propose an agent and network based architecture for parallel and distributed computing called agent space architecture. Our architecture builds upon the notions of agent and object space and utilizes multicast networks. The building blocks for our proposed architecture consist of an active processing unit called agent, a shared place for communication called space, and a communication medium called multicast network. One unique feature of our architecture is that we extend the concept of object space to become an active space. Our active space functions as a rendezvous, a repository, a cache, a responder, a notifier, and a manager of its own resources. The organization of our architecture is as general as network topology. Any number of agents, spaces, or networks can be added to achieve high performance. It is as scalable as Ethernet and adding agents or spaces is as easy as plug and play. High availability and fault tolerance is achieved through multiple agents, spaces, and networks. All these features are particularly beneficial for challenging applications such as search engine, which is used as a test case to implement and to test our proposed architecture.
9581771
Scalable QoS guaranteed communication services for real-time applications
We propose an approach to flow-unaware admission control which is a combination with an aggregate packet forwarding scheme, improving scalability of networks while guaranteeing end-to-end deadlines for real-time applications. We achieve this by using an off-line delay computation and verification step, which allows to reduce the overhead at admission control while keeping admission probability and resource utilization high. Our evaluation data show that our system's admission probabilities are very close to those of significantly more expensive flow-aware approaches. At the same time, the admission control overhead during flow establishment is very low. Our results therefore support the claim from the DS architecture literature that scalability can be achieved through flow aggregation without sacrificing resource utilization and with significant reduction in run time overhead.
10441527
Efficient Support for Ordered XPath Processing in Tree-Unaware Commercial Relational Databases
In this paper, we present a novel ordered XPATH evaluation in treeunaware RDBMS. The novelties of our approach lies in the followings. (a) We propose a novel XML storage scheme which comprises only leaf nodes, their corresponding data values, order encodings and their root-to-leaf paths. (b) We propose an algorithm for mapping ordered XPATH queries into SQL queries over the storage scheme. (c) We propose an optimization technique that enforces all mapped SQL queries to be evaluated in a "left-to-right" join order. By employing these techniques, we show, through a comprehensive experiment, that our approach not only scales well but also performs better than some representative tree-unaware approaches on more than 65% of our benchmark queries with the highest observed gain factor being 1939. In addition, our approach reduces significantly the performance gap between tree-aware and tree-unaware approaches and even outperforms a state-of-the-art tree-aware approach for certain benchmark queries.
16011778
A Uniform System for Publishing and Maintaining XML Data
XML has become the prime standard for data exchange on the Web. To exchange data residing in Databases, one needs to publish it in XML. Data publishing is often done with a predefined “schema.” The chapter proposes a new approach for schema-directed publishing of relational data in XML, based on the novel notion of attribute transformation grammars (ATGs). ATGs provide guidance on how to define views conforming to target schemas (DTDs), and automatically ensure schema conformance. The chapter also develops an incremental algorithm for maintaining XML views produced by ATGs, based on new incremental computation techniques that capitalize on the hierarchical structure of XML data and unique features of the ATGs. Taking real-life data from Gene Ontology (GO), this chapter also demonstrates how this system can efficiently publish the GO data in XML with respect to a predefined recursive DTD, and how it incrementally updates the target XML data in response to changes to the underlying GO database.
11364385
An organizational memory for facilitating knowledge: an application to e-business architecture
Abstract Our economy is increasingly dependent on knowledge. Organizational memory (OM) contains knowledge that companies need to manage. This paper proposes a knowledge facilitating organizational memory (KFOM) to decipher a harmony mechanism of OM from the Oriental Yin and Yang perspective. KFOM clarifies an architecture to catapult the OM to organizational effectiveness. This architecture is made up of two layers: storage layer and facilitation layer. Storage layer represents task and domain knowledge. Facilitation layer identifies the harmony mechanism for utilizing knowledge. This harmony mechanism leverages the knowledge chain with agent, collaborator, transactor, object and registry facilitators. In order to demonstrate its practical usefulness, we explore how KFOM can sharpen an international e-business technical standard. Furthermore, an extension to a real-life B2B collaboration project for Korean steel and automotive companies confirms that KFOM can lead to business practices which most knowledge-oriented companies can adopt.
32334665
An Empirical Study of Standards Development for E-Businesses: A Social Network Perspective
Research on the nature of e-business standards and the organizational context in which they are developed has received little attention in the literature of IT standards and standardization. This study investigates communication patterns in online standards groups to provide insights into the nature of group dynamics among standards decision makers and its relation to the standards context. Email data is used from the ebXML standards initiative. Findings suggest that standards groups operating on the Internet appear to form a cohesive structure, despite the fact that they tend to consist of large group of participants coming from various backgrounds and industries, while their communication patterns are influenced by standards orientation. Policy implications for managers in online standards groups are presented.