Peer to peer English/Chinese cross-language information retrieval

Peer to peer systems have been widely used in the internet. However, most of the peer to peer information systems are still missing some of the important features, for example cross-language IR (Information Retrieval) and collection selection / fusion features. Cross-language IR is the state-of-art research area in IR research community. It has not been used in any real world IR systems yet. Cross-language IR has the ability to issue a query in one language and receive documents in other languages. In typical peer to peer environment, users are from multiple countries. Their collections are definitely in multiple languages. Cross-language IR can help users to find documents more easily. E.g. many Chinese researchers will search research papers in both Chinese and English. With Cross-language IR, they can do one query in Chinese and get documents in two languages. The Out Of Vocabulary (OOV) problem is one of the key research areas in crosslanguage information retrieval. In recent years, web mining was shown to be one of the effective approaches to solving this problem. However, how to extract Multiword Lexical Units (MLUs) from the web content and how to select the correct translations from the extracted candidate MLUs are still two difficult problems in web mining based automated translation approaches. Discovering resource descriptions and merging results obtained from remote search engines are two key issues in distributed information retrieval studies. In uncooperative environments, query-based sampling and normalized-score based merging strategies are well-known approaches to solve such problems. However, such approaches only consider the content of the remote database but do not consider the retrieval performance of the remote search engine. This thesis presents research on building a peer to peer IR system with crosslanguage IR and advance collection profiling technique for fusion features. Particularly, this thesis first presents a new Chinese term measurement and new Chinese MLU extraction process that works well on small corpora. An approach to selection of MLUs in a more accurate manner is also presented. After that, this thesis proposes a collection profiling strategy which can discover not only collection content but also retrieval performance of the remote search engine. Based on collection profiling, a web-based query classification method and two collection fusion approaches are developed and presented in this thesis. Our experiments show that the proposed strategies are effective in merging results in uncooperative peer to peer environments. Here, an uncooperative environment is defined as each peer in the system is autonomous. Peer like to share documents but they do not share collection statistics. This environment is a typical peer to peer IR environment. Finally, all those approaches are grouped together to build up a secure peer to peer multilingual IR system that cooperates through X.509 and email system.

Final report : task 4 : waste minimisation in construction

The Regenerating Construction Project for the CRC for Construction Innovation aims to assist in the delivery of demonstrably superior ‘green’ buildings. Components of the project address eco-efficient redesign, achieving a smaller ecological footprint, enhancing indoor environment and minimising waste in design and construction. The refurbishment of Council House 1 for Melbourne City Council provides an opportunity to develop and demonstrate tools that will be of use for commercial building refurbishment generally. It is hoped that the refurbishment will act as an exemplar project to demonstrate environmentally friendly possibilities for office building refurbishment.

Waste minimisation in office refurbishment projects : an Australian perspective

The refurbishment of commercial buildings is growing as a percentage of overall construction activity in Australia and this trend is likely to continue. Refurbishment generates a significant waste stream much of which is potentially reusable or recyclable. Despite this potential, several factors are known to unnecessarily inhibit the amount of recycling that actually occurs on renovation projects. In order to identify the reasons causing this reluctance, a process of project monitoring and expert consultation was carried out. Twenty three experts experienced in commercial refurbishment projects and three waste contractors with specific knowledge of construction waste were interviewed. Records of receipts for waste from a case study project reveal three principal factors inhibiting recycling rates: the presence of asbestos in the building; the continued occupation of the building during construction; and the breaking up of a large project into small separate contracts thereby reducing economies of scale. To ascertain the potential for improvement, current rates for reuse and recycling of materials were collected from the experts. The results revealed a considerable variation in practice between companies and indicated key areas which should be targeted to improve performance.

The efficacy of waste management plans in Australian commercial construction refurbishment projects

Renovation and refurbishment of the existing commercial building stock is a growing area of total construction activity and a significant generator of waste sent to landfill in Australia. A written waste management plan (WMP) is a widespread regulatory requirement for commercial office redevelopment projects. There is little evidence, however, that WMPs actually increase the quantity of waste that is ultimately diverted from landfill. Some reports indicate an absence of any formal verification or monitoring process by regulators to assess the efficacy of the plans. In order to gauge the extent of the problem a survey was conducted of twenty four consultants and practitioners involved in commercial office building refurbishment projects to determine the state of current practice with regard to WMPs and to elicit suggestions with regard to ways of making the process more effective. Considerable variation in commitment to recycling policies was encountered indicating a need to revisit waste minimisation practices if the environmental performance of refurbishment projects is to be improved.

The innovation deficit in public services : the curious problem of too much efficiency and not enough waste and failure

It has long been recognised that government and public sector services suffer an innovation deficit compared to private or market-based services. This paper argues that this can be explained as an unintended consequence of the concerted public sector drive toward the elimination of waste through efficiency, accountability and transparency. Yet in an evolving economy this can be a false efficiency, as it also eliminates the 'good waste' that is a necessary cost of experimentation. This results in a systematic trade0off in the public sector between the static efficiency of minimizing the misuse of public resources and the dynamic efficiency of experimentation. this is inherently biased against risk and uncertainty and therein, explains why governments find service innovation so difficult. In the drive to eliminate static inefficiencies, many political systems have susequently overshot and stifled policy innovation. I propose the 'Red Queen' solution of adaptive economic policy.

Semantic and context-based retrieval of digital cultural objects [Published in Chinese]

Cultural objects are increasingly generated and stored in digital form, yet effective methods for their indexing and retrieval still remain an important area of research. The main problem arises from the disconnection between the content-based indexing approach used by computer scientists and the description-based approach used by information scientists. There is also a lack of representational schemes that allow the alignment of the semantics and context with keywords and low-level features that can be automatically extracted from the content of these cultural objects. This paper presents an integrated approach to address these problems, taking advantage of both computer science and information science approaches. We firstly discuss the requirements from a number of perspectives: users, content providers, content managers and technical systems. We then present an overview of our system architecture and describe various techniques which underlie the major components of the system. These include: automatic object category detection; user-driven tagging; metadata transform and augmentation, and an expression language for digital cultural objects. In addition, we discuss our experience on testing and evaluating some existing collections, analyse the difficulties encountered and propose ways to address these problems.

Retention and degradation of organics in Rundle waste shale/retort water mixtures

Batch, column and field lysimeter studies have been conducted to evaluate the concept of codisposal of retort water with Rundle (Queensland, Australia) waste shales. The batch studies indicated that degradation of a significant proportion of the total organic load occurs if the mixture is seeded with soil or compost. These results are compared with those from laboratory column studies and from the field lysimeter at the Rundle site. G.c.-m.s. analysis of some of the eluants indicated that significant degradation of the base-neutral fraction occurs even if no soil seed is added, and that degradation of this fraction was higher under anaerobic conditions.

Improvement to Chinese information retrieval by incorporating word segmentation and query expansion

The increasing diversity of the Internet has created a vast number of multilingual resources on the Web. A huge number of these documents are written in various languages other than English. Consequently, the demand for searching in non-English languages is growing exponentially. It is desirable that a search engine can search for information over collections of documents in other languages. This research investigates the techniques for developing high-quality Chinese information retrieval systems. A distinctive feature of Chinese text is that a Chinese document is a sequence of Chinese characters with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose two approaches to deal with the problems. In the first approach, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach. In the second approach, we propose a novel query expansion method which applies text mining techniques in order to find the most relevant words to extend the query. Unlike most existing query expansion methods, which generally select the highly frequent indexing terms from the retrieved documents to expand the query. In our approach, we utilize text mining techniques to find patterns from the retrieved documents that highly correlate with the query term and then use the relevant words in the patterns to expand the original query. This research project develops and implements a Chinese information retrieval system for evaluating the proposed approaches. There are two stages in the experiments. The first stage is to investigate if high accuracy segmentation can make an improvement to Chinese information retrieval. In the second stage, a text mining based query expansion approach is implemented and a further experiment has been done to compare its performance with the standard Rocchio approach with the proposed text mining based query expansion method. The NTCIR5 Chinese collections are used in the experiments. The experiment results show that by incorporating the text mining based query expansion with the hybrid model, significant improvement has been achieved in both precision and recall assessments.

Adaptive dual control of topic-based information retrieval

Information Retrieval is an important albeit imperfect component of information technologies. A problem of insufficient diversity of retrieved documents is one of the primary issues studied in this research. This study shows that this problem leads to a decrease of precision and recall, traditional measures of information retrieval effectiveness. This thesis presents an adaptive IR system based on the theory of adaptive dual control. The aim of the approach is the optimization of retrieval precision after all feedback has been issued. This is done by increasing the diversity of retrieved documents. This study shows that the value of recall reflects this diversity. The Probability Ranking Principle is viewed in the literature as the “bedrock” of current probabilistic Information Retrieval theory. Neither the proposed approach nor other methods of diversification of retrieved documents from the literature conform to this principle. This study shows by counterexample that the Probability Ranking Principle does not in general lead to optimal precision in a search session with feedback (for which it may not have been designed but is actively used). Retrieval precision of the search session should be optimized with a multistage stochastic programming model to accomplish the aim. However, such models are computationally intractable. Therefore, approximate linear multistage stochastic programming models are derived in this study, where the multistage improvement of the probability distribution is modelled using the proposed feedback correctness method. The proposed optimization models are based on several assumptions, starting with the assumption that Information Retrieval is conducted in units of topics. The use of clusters is the primary reasons why a new method of probability estimation is proposed. The adaptive dual control of topic-based IR system was evaluated in a series of experiments conducted on the Reuters, Wikipedia and TREC collections of documents. The Wikipedia experiment revealed that the dual control feedback mechanism improves precision and S-recall when all the underlying assumptions are satisfied. In the TREC experiment, this feedback mechanism was compared to a state-of-the-art adaptive IR system based on BM-25 term weighting and the Rocchio relevance feedback algorithm. The baseline system exhibited better effectiveness than the cluster-based optimization model of ADTIR. The main reason for this was insufficient quality of the generated clusters in the TREC collection that violated the underlying assumption.

Efficient and accurate retrieval of business process models through indexing

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective than developing them from scratch. As process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. Experiments are conducted to demonstrate that our proposal achieves a significant reduction in query evaluation time.