Algorithms and applications of preference based ranking for information retrieval

In this thesis, the author designed three sets of preference based ranking algorithms for information retrieval and provided the corresponsive applications for the algorithms. The main goal is to retrieve recommended, high similar and valuable ranking results to users.

An parallel information retrieval method for e-commerce

An online transaction always retrieves a large amount of information before making decisions. Currently, the parallel methods for retrieving such information can only provide a similar performance to serial methods. In this paper we first perform an analysis to determine the factors that affect the performance of exiting methods, i.e., HQR and EHQR, and show that the several of these factors are not considered by these methods. Motivated by this, we propose a new dispatch scheme called AEHQR, which takes into account the features of parallel dispatching. In addition, we provide cost models that determine the optimal performance achievable by any parallel dispatching method. Using experimental comparison, we illustrate that the AEHQR is significantly outperforms the HQR and EHQR under all conditions.

Information retrieval in documents using semantic criteria

The central problem of automatic retrieval from unformatted text is that computational devices are not adequately trained to look for associated information. However for complete understanding and information retrieval, a complete artificial intelligence would have to be built. This paper describes a method for achieving significant information retrieval by using a semantic search engine. The underlying semantic information is stored in a network of clarified words, linked by logical connections. We employ simple scoring techniques on collections of paths in this network to establish a degree of relevance between a document and a clarified search criterion. This technique has been applied with success to test examples and can be easily scaled up to search large documents.

Media-independent information representation and retrieval

In this paper we propose a media-independent knowledge indexing and retrieval system as a basis for an information retrieval system. The representation allows for sharing of low level information bearing objects and at the same time allows for maintaining of user-dependent views. The tools for maintenance and manipulation of concepts focus on the user and user's intentions. The aim of the system is to provide a set of flexible tools and let the user structure the knowledge in his or her own way, instead of attempting to build an all-encompassing common sense, or general knowledge representation.

Media-independent knowledge representation via UMART : unified mental annotation and retrieval tool

Multimedia information is now routinely available in the forms of text, pictures, animation and sound. Although text objects are relatively easy to deal with (in terms of information search and retrieval), other information bearing objects (such as sound, images, animation) are more difficult to index. Our research is aimed at developing better ways of representing multimedia objects by using a conceptual representation based on Schank's conceptual dependencies. Moreover, the representation allows for users' individual interpretations to be embedded in the system. This will alleviate the problems associated with traditional semantic networks by allowing for coexistence of multiple views of the same information. The viability of the approach is tested, and the preliminary results reported.

A distributed directory scheme for information access in mobile computers

In this paper, we discuss the design aspects of a dynamic distributed directory scheme (DDS) to facilitate efficient and transparent access to information files in mobile environments. The proposed directory interface enables users of mobile computers to view a distributed file system on a network of computers as a globally shared file system. In order to counter some of the limitations of wireless communications, we propose improvised invalidation schemes that avoid false sharing and ensure uninterrupted usage under disconnected and low bandwidth conditions.

Accessing database information using mobile agents

Many real-world applications on the Internet require accessing database information and typical technology employed is client/server plus Web (C/S + Web). Although past few years saw many success applications by using this technique, there are still some drawbacks that need to be overcome. One of the drawbacks is that the transaction often fails if the network connection is unstable. Another disadvantage is high bandwidth requirement and latency. This paper argues that mobile agent technology provide an easy way to overcome the shortcomings in CIS + Web in database access on the Internet. A success case study using mobile agents to admit new students to China's institutions is then presented. The mobile agent was created by using IBM's Aglets Software Development Kit (SDK). Based on the experimental results, it is evident that mobile agent technology is well suited for such applications.

Effectively finding relevant web pages from linkage information

This paper presents two hyperlink analysis-based algorithms to find relevant pages for a given Web page (URL). The first algorithm comes from the extended cocitation analysis of the Web pages. It is intuitive and easy to implement. The second one takes advantage of linear algebra theories to reveal deeper relationships among the Web pages and to identify relevant pages more precisely and effectively. The experimental results show the feasibility and effectiveness of the algorithms. These algorithms could be used for various Web applications, such as enhancing Web search. The ideas and techniques in this work would be helpful to other Web-related researches.

Reasoning with multimedia information using symbolic projection

In many multimedia application systems, it is not the final goal to retrieve the relevant multimedia information from different multimedia information sources. Rather, post-processing of the retrieved multimedia information is needed. For example, the retrieved information is used as “known facts”. The systems will do some reasoning to obtain further conclusions based on these multimedia form “known facts”. We call this reasoning with multimedia information. Most current research work in multimedia information processing is focused on multimedia information retrieval, but post-processing the retrieved information is more or less ignored. This paper explores the way to tackle this problem by using symbolic projection. A case study of reasoning with still image information is presented. Some extensions to symbolic projection- introducing auxiliary pictorial objects in symbolic pictures that need to be processed-are discussed. We expect this paper will stimulate further research on this important but ignored topic.

The portal as information broker

The term information broker is widely used in the area of library and information science to describe a middle agent who deals in information as a commodity, enabling customers to gain more efficient access to quality data. The role of this middle agent is described as “information retrieval and information organisation” (Rugge & Glossbrenner, 1995). The role of the broker is to bring additional organisation to the market by lowering search costs (Palmer & Lindemann, 2003).

An agent-based intelligent system for information gathering from world wide web environment

To use the vast amount of information efficiently and effectively from Web sites is very important for making informed decisions. There are, however, still many problems that need to be overcome in the information gathering research arena to enable the delivery of relevant information required by users. In this paper, an information gathering system is develop by means of multiple agents to solve those problems. We employed some ideas of Gaia's methodology and an open agent architecture to analyze and design the system. The system consists of a query preprocessing agent, information retrieval agent, information filtering agent, and information management agent. The filtering agent is trained with categorized documents and can provide users with the necessary information. The experimental results show that all agents in the system can work cooperatively to retrieve relevant information from the World Wide Web environment.

Impact of image organizations on multimedia document retrieval

In this paper we compare ranking effectiveness of heterogeneous multimedia document retrieval when different image organizations are used for formulating queries. The quality of image queries depends on the organization of images used to make queries which in turn significantly impacts retrieval precision. CBIR (content based information retrieval) needs an effective and efficient organization of images including user interface which must be part of the configuration parameters of image retrieval research.

Building information modelling project decision support framework

Building Information Modelling (BIM) is an information technology [IT] enabled approach to managing design data in the AEC/FM (Architecture, Engineering and Construction/ Facilities Management) industry. BIM enables improved interdisciplinary collaboration across distributed teams, intelligent documentation and information retrieval, greater consistency in building data, better conflict detection and enhanced facilities management. Despite the apparent benefits the adoption of BIM in practice has been slow. Workshops with industry focus groups were conducted to identify the industry needs, concerns and expectations from participants who had implemented BIM or were BIM “ready”. Factors inhibiting BIM adoption include lack of training, low business incentives, perception of lack of rewards, technological concerns, industry fragmentation related to uneven ICT adoption practices, contractual matters and resistance to changing current work practice. Successful BIM usage depends on collective adoption of BIM across the different disciplines and support by the client. The relationship of current work practices to future BIM scenarios was identified as an important strategy as the participants believed that BIM cannot be efficiently used with traditional practices and methods. The key to successful implementation is to explore the extent to which current work practices must change. Currently there is a perception that all work practices and processes must adopt and change for effective usage of BIM. It is acknowledged that new roles and responsibilities are emerging and that different parties will lead BIM on different projects. A contingency based approach to the problem of implementation was taken which relies upon integration of BIM project champion, procurement strategy, team capability analysis, commercial software availability/applicability and phase decision making and event analysis. Organizations need to understand: (a) their own work processes and requirements; (b) the range of BIM applications available in the market and their capabilities (c) the potential benefits of different BIM applications and their roles in different phases of the project lifecycle, and (d) collective supply chain adoption capabilities. A framework is proposed to support organizations selection of BIM usage strategies that meet their project requirements. Case studies are being conducted to develop the framework. The results of the preliminary design management case study is presented for contractor led BIM specific to the design and construct procurement strategy.

Modeling intelligent agents for web-based information gathering

The recent emergence of intelligent agent technology and advances in information gathering have been the important steps forward in efficiently managing and using the vast amount of information now available on the Web to make informed decisions. There are, however, still many problems that need to be overcome in the information gathering research arena to enable the delivery of relevant information required by end users. Good decisions cannot be made without sufficient, timely, and correct information. Traditionally it is said that knowledge is power, however, nowadays sufficient, timely, and correct information is power. So gathering relevant information to meet user information needs is the crucial step for making good decisions. The ideal goal of information gathering is to obtain only the information that users need (no more and no less). However, the volume of information available, diversity formats of information, uncertainties of information, and distributed locations of information (e.g. World Wide Web) hinder the process of gathering the right information to meet the user needs. Specifically, two fundamental issues in regard to efficiency of information gathering are mismatch and overload. The mismatch means some information that meets user needs has not been gathered (or missed out), whereas, the overload means some gathered information is not what users need. Traditional information retrieval has been developed well in the past twenty years. The introduction of the Web has changed people's perceptions of information retrieval. Usually, the task of information retrieval is considered to have the function of leading the user to those documents that are relevant to his/her information needs. The similar function in information retrieval is to filter out the irrelevant documents (or called information filtering). Research into traditional information retrieval has provided many retrieval models and techniques to represent documents and queries. Nowadays, information is becoming highly distributed, and increasingly difficult to gather. On the other hand, people have found a lot of uncertainties that are contained in the user information needs. These motivate the need for research in agent-based information gathering. Agent-based information systems arise at this moment. In these kinds of systems, intelligent agents will get commitments from their users and act on the users behalf to gather the required information. They can easily retrieve the relevant information from highly distributed uncertain environments because of their merits of intelligent, autonomy and distribution. The current research for agent-based information gathering systems is divided into single agent gathering systems, and multi-agent gathering systems. In both research areas, there are still open problems to be solved so that agent-based information gathering systems can retrieve the uncertain information more effectively from the highly distributed environments. The aim of this thesis is to research the theoretical framework for intelligent agents to gather information from the Web. This research integrates the areas of information retrieval and intelligent agents. The specific research areas in this thesis are the development of an information filtering model for single agent systems, and the development of a dynamic belief model for information fusion for multi-agent systems. The research results are also supported by the construction of real information gathering agents (e.g., Job Agent) for the Internet to help users to gather useful information stored in Web sites. In such a framework, information gathering agents have abilities to describe (or learn) the user information needs, and act like users to retrieve, filter, and/or fuse the information. A rough set based information filtering model is developed to address the problem of overload. The new approach allows users to describe their information needs on user concept spaces rather than on document spaces, and it views a user information need as a rough set over the document space. The rough set decision theory is used to classify new documents into three regions: positive region, boundary region, and negative region. Two experiments are presented to verify this model, and it shows that the rough set based model provides an efficient approach to the overload problem. In this research, a dynamic belief model for information fusion in multi-agent environments is also developed. This model has a polynomial time complexity, and it has been proven that the fusion results are belief (mass) functions. By using this model, a collection fusion algorithm for information gathering agents is presented. The difficult problem for this research is the case where collections may be used by more than one agent. This algorithm, however, uses the technique of cooperation between agents, and provides a solution for this difficult problem in distributed information retrieval systems. This thesis presents the solutions to the theoretical problems in agent-based information gathering systems, including information filtering models, agent belief modeling, and collection fusions. It also presents solutions to some of the technical problems in agent-based information systems, such as document classification, the architecture for agent-based information gathering systems, and the decision in multiple agent environments. Such kinds of information gathering agents will gather relevant information from highly distributed uncertain environments.

Doctoral research and scholarly communication : candidates, supervisors and information literacy

This study investigates information literacy and scholarly communication within the processes of doctoral research and supervision at a distance. Both doctoral candidates and supervisors acknowledge information literacy deficiencies and it is suggested that disintermediation and the proliferation of information may contribute to those deficiencies. Further to this, the influence of pedagogic continuity—particularly in relation to the information seeking behaviour of candidates—is investigated, as is the concomitant aspect of how doctoral researchers practise scholarly communication. The well-documented and enduring problem for candidates of isolation from the research cultures of their universities is also scrutinised. The contentious issue of more formally involving librarians in the doctoral process is also considered, from the perspective of candidates and supervisors. Superimposed upon these topical and timely issues is the theoretical framework of adult learning theory, in particular the tenets of andragogy. The pedagogical-andragogical orientation of candidates and supervisors is established, demonstrating both the differences and similarities between candidates and supervisors, as are a number of independent variables, including a comparison of on-campus and off-campus candidates. Other independent variables include age, gender, DETYA (Department of Education, Training & Youth Affairs) category, enrolment type, stage of candidature, employment and status, type of doctorate, and English/non-English speaking background. The research methodology uses qualitative and quantitative techniques encompassing both data and methodological triangulation. The study uses two sets of questionnaires and a series of in-depth interviews with a sample of on-campus and off-campus doctoral candidates and supervisors from four Australian universities. Major findings include NESB candidates being more pedagogical than their ESB counterparts, and candidates and supervisors from the Sciences are more pedagogical than those from Arts, Humanities and Social Sciences, or Education. Candidates make a transition from a more dependent and pedagogically oriented approach to learning towards more of an independent and andragogical orientation over the duration of their candidature. However, over tune both on-campus and off-campus candidates become more isolated from the research cultures of their universities, and less happy with support received from their supervisors in relation to their literature reviews. Ill The study found large discrepancies in perception between the support supervisors believed they gave to candidates in relation to the literature review, and the support candidates believed they received. Information seeking becomes easier over time, but candidates face a dilemma with the proliferation of information, suggesting that disintermediation has exacerbated the challenges of evaluation and organisation of information. The concept of pedagogic continuity was recognised by supervisors and especially candidates, both negative and positive influences. The findings are critically analysed and synthesised using the metaphor of a scholarly 'Club' of which obtaining a doctorate is a rite of passage. Recommendations are made for changes in professional practice, and topics that may warrant further research are suggested.