Personalised ontology learning and mining for web information gathering

Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.

Understanding users’ information behaviors through information journals

Information behavior studies in the field of Library and Information Science (LIS) generally focus on one of many aspects of information behavior: information finding, information organizing, and information using. Information seeking is further specialized into information searching, information seeking, information foraging or information sense making. Spink and Cole (2006) highlighted the lack of integration across these various approaches and models of information behavior within LIS. Often, each approach provides a different language for similar processes (Spink & Cole, 2004), and it is sometimes hard for practicing information professionals to parse the various theories and models to see how they shape and affect the provision of information resources, services, and products. An integrated model of information behaviors that explains the key dimensions of how peoples’ contextual and situational dimensions affect their information needs and behavior will help information providers and LIS researchers alike with a framework that can help “depict and explain a sequence of behaviors by referring to relevant variables, rather than merely indicating a sequence of events… while indicating something about information needs and sources” (Case, 2002). This presentation presents an integrated model of peoples’ information behaviors based on research that studied participants’ information behaviors through a detailed daily information journal maintained for two weeks.

Conceptualising use for information systems (IS) success

This thesis conceptualises Use for IS (Information Systems) success. While Use in this study describes the extent to which an IS is incorporated into the user’s processes or tasks, success of an IS is the measure of the degree to which the person using the system is better off. For IS success, the conceptualisation of Use offers new perspectives on describing and measuring Use. We test the philosophies of the conceptualisation using empirical evidence in an Enterprise Systems (ES) context. Results from the empirical analysis contribute insights to the existing body of knowledge on the role of Use and demonstrate Use as an important factor and measure of IS success. System Use is a central theme in IS research. For instance, Use is regarded as an important dimension of IS success. Despite its recognition, the Use dimension of IS success reportedly suffers from an all too simplistic definition, misconception, poor specification of its complex nature, and an inadequacy of measurement approaches (Bokhari 2005; DeLone and McLean 2003; Zigurs 1993). Given the above, Burton-Jones and Straub (2006) urge scholars to revisit the concept of system Use, consider a stronger theoretical treatment, and submit the construct to further validation in its intended nomological net. On those considerations, this study re-conceptualises Use for IS success. The new conceptualisation adopts a work-process system-centric lens and draws upon the characteristics of modern system types, key user groups and their information needs, and the incorporation of IS in work processes. With these characteristics, the definition of Use and how it may be measured is systematically established. Use is conceptualised as a second-order measurement construct determined by three sub-dimensions: attitude of its users, depth, and amount of Use. The construct is positioned in a modified IS success research model, in an attempt to demonstrate its central role in determining IS success in an ES setting. A two-stage mixed-methods research design—incorporating a sequential explanatory strategy—was adopted to collect empirical data and to test the research model. The first empirical investigation involved an experiment and a survey of ES end users at a leading tertiary education institute in Australia. The second, a qualitative investigation, involved a series of interviews with real-world operational managers in large Indian private-sector companies to canvass their day-to-day experiences with ES. The research strategy adopted has a stronger quantitative leaning. The survey analysis results demonstrate the aptness of Use as an antecedent and a consequence of IS success, and furthermore, as a mediator between the quality of IS and the impacts of IS on individuals. Qualitative data analysis on the other hand, is used to derive a framework for classifying the diversity of ES Use behaviour. The qualitative results establish that workers Use IS in their context to orientate, negotiate, or innovate. The implications are twofold. For research, this study contributes to cumulative IS success knowledge an approach for defining, contextualising, measuring, and validating Use. For practice, research findings not only provide insights for educators when incorporating ES for higher education, but also demonstrate how operational managers incorporate ES into their work practices. Research findings leave the way open for future, larger-scale research into how industry practitioners interact with an ES to complete their work in varied organisational environments.

Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

Information interventions for orienting patients and their carers to cancer care facilities

Background: Cancer patients experience distress and anxiety related to their diagnosis, treatment and the unfamiliar cancer centre. Strategies with the aim of orienting patients to a cancer care facility may improve patient outcomes. Although meeting patients' information needs at different stages is important, there is little agreement about the type of information and the timing for information to be given. Orientation interventions aim to address information needs at the start of a person's experience with a cancer care facility. The extent of any benefit of these interventions is unknown. Objectives: To assess the effects of information interventions which orient patients and their carers/family to a cancer care facility, and to the services available in the facility. Search Methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2011, Issue 2); MEDLINE (OvidSP) (1966 to Jun 2011), EMBASE (Ovid SP) (1966 to Jun 2011), CINAHL (EBSCO) (1982 to Jun 2011), PsycINFO (OvidSP) (1966 to Jun 2011), review articles and reference lists of relevant articles. We contacted principal investigators and experts in the field. Selection Criteria: Randomised controlled trials (RCTs), cluster RCTs and quasi-RCTs evaluating the effects of information interventions that orient patients and their carers/family to a cancer care facility. Data collection and analysis: Results of searches were reviewed against the pre-determined criteria for inclusion by two review authors. The primary outcomes were knowledge and understanding; health status and wellbeing, evaluation of care, and harms. Secondary outcomes were communication, skills acquisition, behavioural outcomes, service delivery, and health professional outcomes. We pooled results of RCTs using mean differences (MD) and 95% confidence intervals (CI). Main results: We included four RCTs involving 610 participants. All four trials aimed to investigate the effects of orientation programs for cancer patients to a cancer facility. There was high risk of bias across studies. Findings from two of the RCTs demonstrated significant benefits of the orientation intervention in relation to levels of distress (mean difference (MD) -8.96 (95% confidence interval (CI) -11.79 to -6.13), but non-significant benefits in relation to state anxiety levels (MD -9.77 (95% CI -24.96 to 5.41). Other outcomes for participants were generally positive (e.g. more knowledgeable about the cancer centre and cancer therapy, better coping abilities). No harms or adverse effects were measured or reported by any of the included studies. There were insufficient data on the other outcomes of interest. Authors conclusion: This review has demonstrated the feasibility and some potential benefits of orientation interventions. There was a low level of evidence suggesting that orientation interventions can reduce distress in patients. However, most of the other outcomes remain inconclusive (patient knowledge recall/ satisfaction). The majority of studies were subject to high risk of bias, and were likely to be insufficiently powered. Further well conducted and powered RCTs are required to provide evidence for determining the most appropriate intensity, nature, mode and resources for such interventions. Patient and carer-focused outcomes should be included.

Health professionals’ perspectives on information provision for patients with brain tumours and their families

A significant number of patients diagnosed with primary brain tumours report unmet information needs. Using concept mapping methodology, this study aimed to identify strategies for improving information provision, and to describe factors that health professionals understood to influence their provision of information to patients with brain tumours and their families. Concept mapping is a mixed methods approach that uses statistical methods to represent participants’ perceived relationships between elements as conceptual maps. These maps, and results of associated data collection and analyses, are used to extract concepts involved in information provision to these patients. Thirty health professionals working across a range of neuro-oncology roles and settings participated in the concept mapping process. Participants rated a care coordinator as the most important strategy for improving brain tumour care, with psychological support as a whole rated as the most important element of care. Five major themes were identified as facilitating information provision: health professionals’ communication skills, style and attitudes; patients’ needs and preferences; perceptions of patients’ need for protection and initiative; rapport and continuity between patients and health professionals; and the nature of the health care system. Overall, health professionals conceptualised information provision as ‘individualised’, dependent on these interconnected personal and environmental factors.

Exploring the information practices of people with end stage kidney disease

This small exploratory study sought to understand how people with End Stage Kidney Disease (ESKD) experience the information environment and what information practices they employ in order to inform the decisions they make in relation to treatment and care. Using a constructivist methodology, in-depth interviews were conducted with five people who were receiving haemodialysis in two small satellite dialysis units located in regional and rural communities in New South Wales, Australia. Thematic analysis revealed two types of patients. The first type appears to adopt a received view of information, who do not question their condition; and passively accept information. In the other type, patients were found to be engaged; they actively identified their information needs and quickly learned what that they needed to ask and who to ask. Knowing the information practices of people with ESKD is useful for nephrology nurses when providing patient education.

Workplace experiences of information literacy

The idea of information literacy, broadly deÞned as the ability to recognise information needs and identify, evaluate and use information e¤ectively, has been of growing concern in the education sectors for a number of years; whilst in the workplace, employers and managers have perhaps attended more to the need for computer and information technology skill. New descriptions of information literacy, that may be of value to the business sector, are now beginning to appear as a result of qualitative research into how professional employees experience the e¤ective use of information. This paper summarises the outcomes of an investigation into the experience of information literacy amongst various types of professionals; and explores the possible di¤erences and interrelations between individual and organisational information literacy suggested by these outcomes. Seven di¤erent ways of experiencing information literacy were identiÞed. These experiences are closely related to important workplace processes such as environmental scanning, information management, corporate memory, and research and development; conÞrming that information literacy should be considered a signiÞcant part of the character of learning organisations as well as being a key characteristic of the organisationÕs employees. Implications of individual and organisational information literacy for beginning and continuing professional education are explored.

Sense-making across space and time : implications for the organization and findability of information

This paper presents the results from a study of information behaviors, with specific focus on information organisation-related behaviours conducted as part of a larger daily diary study with 34 participants. The findings indicate that organization of information in everyday life is a problematic area due to various factors. The self-evident one is the inter-subjectivity between the person who may have organized the information and the person looking for that same information (Berlin et. al., 1993). Increasingly though, we are not just looking for information within collections that have been designed by someone else, but within our own personal collections of information, which frequently include books, electronic files, photos, records, documents, desktops, web bookmarks, and portable devices. The passage of time between when we categorized or classified the information, and the time when we look for the same information, poses several problems of intra-subjectivity, or the difference between our own past and present perceptions of the same information. Information searching, and hence the retrieval of information from one's own collection of information in everyday life involved a spatial and temporal coordination with one's own past selves in a sort of cognitive and affective time travel, just as organizing information is a form of anticipatory coordination with one's future information needs. This has implications for finding information and also on personal information management.

Personalized ontology learning for enhancing text mining effectiveness

Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

Pattern-based topics for document modelling in information filtering

Many mature term-based or pattern-based approaches have been used in the field of information filtering to generate users’ information needs from a collection of documents. A fundamental assumption for these approaches is that the documents in the collection are all about one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, and this has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering has not been so well explored. Patterns are always thought to be more discriminative than single terms for describing documents. However, the enormous amount of discovered patterns hinder them from being effectively and efficiently used in real applications, therefore, selection of the most discriminative and representative patterns from the huge amount of discovered patterns becomes crucial. To deal with the above mentioned limitations and problems, in this paper, a novel information filtering model, Maximum matched Pattern-based Topic Model (MPBTM), is proposed. The main distinctive features of the proposed model include: (1) user information needs are generated in terms of multiple topics; (2) each topic is represented by patterns; (3) patterns are generated from topic models and are organized in terms of their statistical and taxonomic features, and; (4) the most discriminative and representative patterns, called Maximum Matched Patterns, are proposed to estimate the document relevance to the user’s information needs in order to filter out irrelevant documents. Extensive experiments are conducted to evaluate the effectiveness of the proposed model by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models

What information is necessary to assess the environmental impacts of deconstruction?

4D modeling - the simulation and visualisation of the construction process - is now a common method used during the building construction process with reasonable support from existing software. The goal of this paper is to examine the information needs required to model the deconstruction/demolition process of a building. The motivation is the need to reduce the impacts on the local environment during the deconstruction process. The focus is on the definition and description of the activities to remove building components and on the assessment of the noise, dust and vibration implications of these activities on the surrounding environment. The outcomes of the research are: i. requirements specification for BIM models to support operational deconstruction process planning, ii. algorithms for augmenting the BIM with the derived information necessary to automate planning of the deconstruction process with respect to impacts on the surrounding environment, iii. algorithms to build naive deconstruction activity schedules.

The effectiveness of information-sharing interventions as a means to reduce anxiety in families waiting for surgical patients undergoing an elective surgical procedure : a systematic review protocol

Review question/objective What are the most effective information sharing strategies used to reduce anxiety in families of patients undergoing elective surgery? This review seeks to synthesize the best available evidence in relation to the most effective information-sharing intervention to reduce anxiety for families waiting for patients undergoing an elective surgical procedure. The specific objectives are to review the effectiveness of evidence of interventions designed to reduce the anxiety of families waiting whilst their loved one undergoes a surgical intervention. A variety of interventions exist and include surgical nurse liaison services, intraoperative reporting either by face-to-face or telephone delivery, informational cards, visual information screens, and intraoperative paging devices for families. Inclusion criteria Types of participants All studies of family members over 18 years of age waiting for patients undergoing an elective surgical procedure will be included, including those waiting for both adult and paediatric patients. Studies of families waiting for other patient populations, eg emergency surgery, chemotherapy or intensive care patients will be excluded. Types of intervention(s)/phenomena of interest All information-sharing Interventions for families of patients undergoing an elective surgical procedure will be included, including but not limited to: surgical nurse liaison services, in-person intraoperative reporting, visual information screens, paging devices, informational cards and telephone delivery of intraoperative progress reports. Interventions that take place during the intraoperative phase of care only will be included in the review. Preadmission information sharing interventions will be excluded. Types of outcomes The outcomes of interest include: Primary outcome: the level of anxiety amongst family members or close relatives whilst waiting for patients undergoing surgery, as measured by a validated instrument (such as the S-Anxiety portion of the State-Trait Anxiety Inventory).4 Secondary outcomes: family satisfaction and other measurements that may be considered indicators of stress and anxiety, such as mean arterial pressure (MAP) and heart rate.