Identifying interests of web users for effective recommendations

Search log data is multi dimensional data consisting of number of searches of multiple users with many searched parameters. This data can be used to identify a user’s interest in an item or object being searched. Identifying highest interests of a Web user from his search log data is a complex process. Based on a user’s previous searches, most recommendation methods employ two-dimensional models to find relevant items. Such items are then recommended to a user. Two-dimensional data models, when used to mine knowledge from such multi dimensional data may not be able to give good mappings of user and his searches. The major problem with such models is that they are unable to find the latent relationships that exist between different searched dimensions. In this research work, we utilize tensors to model the various searches made by a user. Such high dimensional data model is then used to extract the relationship between various dimensions, and find the prominent searched components. To achieve this, we have used popular tensor decomposition methods like PARAFAC, Tucker and HOSVD. All experiments and evaluation is done on real datasets, which clearly show the effectiveness of tensor models in finding prominent searched components in comparison to other widely used two-dimensional data models. Such top rated searched components are then given as recommendation to users.

Understanding business process models : the costs and benefits of structuredness

Previous research has put forward a number of properties of business process models that have an impact on their understandability. Two such properties are compactness and(block-)structuredness. What has not been sufficiently appreciated at this point is that these desirable properties may be at odds with one another. This paper presents the results of a two-pronged study aimed at exploring the trade-off between compactness and structuredness of process models. The first prong of the study is a comparative analysis of the complexity of a set of unstructured process models from industrial practice and of their corresponding structured versions. The second prong is an experiment wherein a cohort of students was exposed to semantically equivalent unstructured and structured process models. The key finding is that structuredness is not an absolute desideratum vis-a-vis for process model understandability. Instead, subtle trade-offs between structuredness and other model properties are at play.

Ensuring Correctness During Process Configuration via Partner Synthesis

Variants of the same process can be encountered within one organization or across different organizations. For example, different municipalities, courts, and rental agencies all need to support highly similar processes. In fact, procurement and sales processes can be found in almost any organization. However, despite these similarities, there is also the need to allow for local variations in a controlled manner. Therefore, many academics and practitioners have advocated the use of configurable process models (sometimes referred to as reference models). A configurable process model describes a family of similar process models in a given domain. Such a model can be configured to obtain a specific process model that is subsequently used to handle individual cases, for instance, to process customer orders. Process configuration is notoriously difficult as there may be all kinds of interdependencies between configuration decisions. In fact, an incorrect configuration may lead to behavioral issues such as deadlocks and livelocks. To address this problem, we present a novel verification approach inspired by the “operating guidelines” used for partner synthesis. We view the configuration process as an external service, and compute a characterization of all such services which meet particular requirements via the notion of configuration guideline. As a result, we can characterize all feasible configurations (i. e., configurations without behavioral problems) at design time, instead of repeatedly checking each individual configuration while configuring a process model.

Process mining manifesto

Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.

Impact of a data warehouse model for improved decision-making process in healthcare

The health system is one sector dealing with a deluge of complex data. Many healthcare organisations struggle to utilise these volumes of health data effectively and efficiently. Also, there are many healthcare organisations, which still have stand-alone systems, not integrated for management of information and decision-making. This shows, there is a need for an effective system to capture, collate and distribute this health data. Therefore, implementing the data warehouse concept in healthcare is potentially one of the solutions to integrate health data. Data warehousing has been used to support business intelligence and decision-making in many other sectors such as the engineering, defence and retail sectors. The research problem that is going to be addressed is, "how can data warehousing assist the decision-making process in healthcare". To address this problem the researcher has narrowed an investigation focusing on a cardiac surgery unit. This research used the cardiac surgery unit at the Prince Charles Hospital (TPCH) as the case study. The cardiac surgery unit at TPCH uses a stand-alone database of patient clinical data, which supports clinical audit, service management and research functions. However, much of the time, the interaction between the cardiac surgery unit information system with other units is minimal. There is a limited and basic two-way interaction with other clinical and administrative databases at TPCH which support decision-making processes. The aims of this research are to investigate what decision-making issues are faced by the healthcare professionals with the current information systems and how decision-making might be improved within this healthcare setting by implementing an aligned data warehouse model or models. As a part of the research the researcher will propose and develop a suitable data warehouse prototype based on the cardiac surgery unit needs and integrating the Intensive Care Unit database, Clinical Costing unit database (Transition II) and Quality and Safety unit database [electronic discharge summary (e-DS)]. The goal is to improve the current decision-making processes. The main objectives of this research are to improve access to integrated clinical and financial data, providing potentially better information for decision-making for both improved from the questionnaire and by referring to the literature, the results indicate a centralised data warehouse model for the cardiac surgery unit at this stage. A centralised data warehouse model addresses current needs and can also be upgraded to an enterprise wide warehouse model or federated data warehouse model as discussed in the many consulted publications. The data warehouse prototype was able to be developed using SAS enterprise data integration studio 4.2 and the data was analysed using SAS enterprise edition 4.3. In the final stage, the data warehouse prototype was evaluated by collecting feedback from the end users. This was achieved by using output created from the data warehouse prototype as examples of the data desired and possible in a data warehouse environment. According to the feedback collected from the end users, implementation of a data warehouse was seen to be a useful tool to inform management options, provide a more complete representation of factors related to a decision scenario and potentially reduce information product development time. However, there are many constraints exist in this research. For example the technical issues such as data incompatibilities, integration of the cardiac surgery database and e-DS database servers and also, Queensland Health information restrictions (Queensland Health information related policies, patient data confidentiality and ethics requirements), limited availability of support from IT technical staff and time restrictions. These factors have influenced the process for the warehouse model development, necessitating an incremental approach. This highlights the presence of many practical barriers to data warehousing and integration at the clinical service level. Limitations included the use of a small convenience sample of survey respondents, and a single site case report study design. As mentioned previously, the proposed data warehouse is a prototype and was developed using only four database repositories. Despite this constraint, the research demonstrates that by implementing a data warehouse at the service level, decision-making is supported and data quality issues related to access and availability can be reduced, providing many benefits. Output reports produced from the data warehouse prototype demonstrated usefulness for the improvement of decision-making in the management of clinical services, and quality and safety monitoring for better clinical care. However, in the future, the centralised model selected can be upgraded to an enterprise wide architecture by integrating with additional hospital units’ databases.

AskNow Instant Messaging: innovation in virtual reference

In late 2006, the National Library of Australia implemented a trial Instant Messaging service that ran in parallel with the AskNow chat reference service for a six month period. The trial was a resounding success, proving both a demand for an IM service and the suitability of the medium for reference service provision in a collaborative environment. The trial also allowed the collection of a significant body of data on user expectations, librarian experience and the nature of enquiries. This article begins by introducing the concept of IM and discusses the impetus for its use as a channel for reference service provision. It presents and analyses data collected from user surveys, session transcripts, usage statistics, staff surveys and other staff feedback mechanisms, and explores the issues arising from the data analysis. The article concludes by discussing the IM system architecture that the NLA is currently developing, which will allow the Library to move forward with an ongoing IM service.

Acoustic component detection for automatic species recognition in environmental monitoring

Automatic species recognition plays an important role in assisting ecologists to monitor the environment. One critical issue in this research area is that software developers need prior knowledge of specific targets people are interested in to build templates for these targets. This paper proposes a novel approach for automatic species recognition based on generic knowledge about acoustic events to detect species. Acoustic component detection is the most critical and fundamental part of this proposed approach. This paper gives clear definitions of acoustic components and presents three clustering algorithms for detecting four acoustic components in sound recordings; whistles, clicks, slurs, and blocks. The experiment result demonstrates that these acoustic component recognisers have achieved high precision and recall rate.

Developing a framework for Six Sigma in financial service institutions : empirical evidence from expert interviews

Six Sigma is considered to be an important management philosophy to obtain satisfied customers. But financial service organisations have been slow to adopt Six Sigma issues so far. Despite the extensive effort that has been invested and benefits that can be obtained, the systematic implementation of Six Sigma in financial service organisations is limited. As a company wide implementation framework is missing so far, this paper tries to fill this gap. Based on theory, a conceptual framework is developed and evaluated by experts from financial institutions. The results show that it is very important to link Six Sigma with the strategic as well as the operations level. Furthermore, although Six Sigma is a very important method for improving quality of processes others such as Lean Management are also used This requires a superior project portfolio management to coordinate resources and projects of Six Sigma with the other methods used. Beside the theoretical contribution, the framework can be used by financial service companies to evaluate their Six Sigma activities. Thus, the framework grounded through literature and empirical data will be a useful guide for sustainable and successful implementation of a Six Sigma initiative in financial service organisations.

Using Web Search Logs to Identify Query Classification Terms

Purpose – The work presented in this paper aims to provide an approach to classifying web logs by personal properties of users. Design/methodology/approach – The authors describe an iterative system that begins with a small set of manually labeled terms, which are used to label queries from the log. A set of background knowledge related to these labeled queries is acquired by combining web search results on these queries. This background set is used to obtain many terms that are related to the classification task. The system then ranks each of the related terms, choosing those that most fit the personal properties of the users. These terms are then used to begin the next iteration. Findings – The authors identify the difficulties of classifying web logs, by approaching this problem from a machine learning perspective. By applying the approach developed, the authors are able to show that many queries in a large query log can be classified. Research limitations/implications – Testing results in this type of classification work is difficult, as the true personal properties of web users are unknown. Evaluation of the classification results in terms of the comparison of classified queries to well known age-related sites is a direction that is currently being exploring. Practical implications – This research is background work that can be incorporated in search engines or other web-based applications, to help marketing companies and advertisers. Originality/value – This research enhances the current state of knowledge in short-text classification and query log learning. Classification schemes, Computer networks, Information retrieval, Man-machine systems, User interfaces

An exploration of the role of web and mobile social media in the implementation of e-Government in Malaysia

This paper reports on an exploratory study of the role of web and social media in e-governments, especially in the context of Malaysia, with some comparisons and contrasts from other countries where such governmental efforts have been underway for awhile. It describes the current e-government efforts in Malaysia, and proposes that applying a theoretical framework would help understand the context and streamline these ongoing efforts. Specifically, it lays out a theoretical and cultural framework based on Mary Douglas’ (1996) Grid-Group Theory, Mircea Georgescu’s (2005) Three Pillars of E-Government, and Gerald Grant’s and Derek Chau’s (2006) Generic Framework for E-Government. Although this study is in its early stages, it has relevance to everyone who is interested in e-government efforts across the world, and especially relevant to developing countries.

“Modeling with tools is easier, believe me” : the effects of tool functionality on modeling grammar usage beliefs

Increasingly, studies are reported that examine how conceptual modeling is conducted in practice. Yet, typically the studies to date have examined in isolation how modeling grammars can be, or are, used to develop models of information systems or organizational processes, without considering that such modeling is typically done by means of a modeling tool that extends the modeling functionality offered by a grammar through complementary features. This paper extends the literature by examining how the use of seven different features of modeling tools affects usage beliefs users develop when using modeling grammars for process modeling. We show that five distinct tool features positively affect usefulness, ease of use and satisfaction beliefs of users. We offer a number of interpretations about the findings. We also describe how the results inform decisions of relevance to developers of modeling tools as well as managers in charge for making modeling-related investment decisions.