C3Ro: An efficient mining algorithm of extende d-close d contiguous robust sequential patterns in noisy data

International audienceSequential pattern mining has been the focus of many works, but still faces a tough challenge in the mining of large databases for both efficiency and apprehensibility of its resulting set. To overcome these issues, the most promising direction taken by the literature relies on the use of constraints, including the well-known closedness constraint. However, such a mining is not resistant to noise in data, a characteristic of most real-world data. The main research question raised in this paper is thus: how to efficiently mine an apprehensible set of sequential patterns from noisy data? In order to address this research question, we introduce 1) two original constraints designed for the mining of noisy data: the robustness and the extended-closedness constraints, 2) a generic pattern mining algorithm, C3Ro, designed to mine a wide range of sequential patterns, going from closed or maximal contiguous sequential patterns to closed or maximal regular sequential patterns. C3Ro is dedicated to practitioners and is able to manage their multiple constraints. C3Ro also is the first sequential pattern mining algorithm to be as generic and parameterizable. Extensive experiments have been conducted and reveal the high efficiency of C3Ro, especially in large datasets, over well-known algorithms from the literature. Additional experiments have been conducted on a real-world job offers noisy dataset, with the goal to mine activities. This experiment offers a more thorough insight into C3Ro algorithm: job market experts confirm that the constraints we introduced actually have a significant positive impact on the apprehensibility of the set of mined activities

Human Machine Interaction

In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction

Investigating project management maturity in the ship repair industry of South Africa, a case study

Purpose Ship repair companies that employ a greater degree of the project management process functions enjoys greater business value and business success. Such certainty within a business' structure supports its longer-term sustainability and improves its growth potential. This research seeks to address the problem relating to the inability of ship repair companies to continually achieve targeted project estimates because of a lower levels of project management maturity. Research Design The research is exploratory in nature as the response in term of the selected maturity model used, seeks to understand the level of application of the ten PMI knowledge areas and how deeply engrained the function is adopted in the performance and within the organisation within the ship repair industry. The principle of communities of practise was adopted for this study which implies that the response and the data obtained will be based on the information shared by the respondents on their insights, experience, knowledge, and common interests within the industry. Findings - This study found an active, informal, and partially structured project management function present within the Western Cape's ship repair industry. The study further found the actual project maturity level at an average of 3.24, in line expectations for the industry and following the same direction, though at a lower level as similar research done on South Africa's IT, mining, engineering, and construction industries. Research Limitations - The study is limited to the Western Cape province's ship repair industry and based on the views of the industry's community of practise as indicator of its project management maturity

Advances in Reinforcement Learning

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic

An Evaluation of Structured Navigation for Subject Searching in Online Catalogues

Understanding and improving subject searching in online library catalogues is the focus of this study. Against the backdrop of current research and developments in online catalogues an analysis of the problems and prospects for subject access in the expanding online catalogue is presented. Developments in recent information retrieval theory and practice are reviewed, and a case is made for a new model of information seeking and retrieval that more closely describes much of the subject searching and browsing activity actually conducted by library users. The center piece of this study is the experiment that was conducted using an experimental online catalogue developed to investigate and evaluate the effect of alternative browse and navigate search methods on overall retrieval effectiveness and subject searching performance. The objectives, methodology, and findings of this online catalogue search experiment are discussed. The primary aim of the experimental study was to evaluate the usability and retrieval performance of a pre-structured "navigation" approach to subject searching and browsing in library catalogues. The main hypothesis tested was that the provision and use of a navigation search and browse function would significantly improve overall OPAC retrieval effectiveness and the subject searching performance of OPAC users. The OPAC used in the study was designed and implemented by this author using the database management and retrieval software known as "TiNMAN", provided by Information Management & Engineering, Ltd. TINMAN employs an entity-relational database structure which permits the linking of any field in the stored bibliographic record to any other field. These linkages establish browse and navigation pathways among data fields ("entities") and citations to support guided but flexible searching and browsing through the collection by users. Thus, a rudimentary form of hypertext is provided for the users of the OPAC. The test database consisted of 30,000 Library of Congress MARC bibliographic records selected at random from all LC catalog records for publications through 1988 in the English language in the LC classes HB-HJ (Economics, Business, etc.). For each record, the verbal description of the assigned LC class number found in the printed schedules was added as a subject descriptor to augment the subject cataloging provided by the Library of Congress. Three different OPACs were tested for comparison purposes. The control OPAC lacked the navigation feature. The other two OPACs supported related-record navigation, one on title words only, the other on subject headings only. Searchers were encouraged to use the OPAC's features and search options in whatever manner they wished. Subjects in Group-I were permitted to navigate only on the subject headings from the controlled subject vocabulary assigned to the work cited (augmented by the verbal meanings of the Library of Congress class number). Subjects in Group-2 were permitted to navigate, but only from title words of the work cited and displayed. Navigating from one of these title words would result in the retrieval of all works whose titles had at least one occurrence of the selected word. Subjects in the control group were not permitted to navigate; that is, it was not possible for them to point to a selected data element in a displayed citation to move on to related terms or citations associated with that data element. The positive value of related-record navigation in improving subject searching in OPACs was not clearly determined. The navigation groups performed significantly better than the control groupon the first search task, but all three groups performed nearly equally well on the second search task. Navigation on subject headings or title keywords resulted in higher recall scores, especially among first time, novice users of the system, but precision suffered significantly in title-word navigation. In fact, the control group achieved higher precision scores on both search tasks. Navigation did not seem to aid subject searching performance after greater familiarity with the system was achieved, except perhaps to increase recall in persistent searches without much decrease in precision. Online bookshelf browsing seems to improve recall without a significant decrease in precision, and may be a more positive factor than navigation on either subject headings or title words

Online Simulation in Semiconductor Manufacturing

In semiconductor manufacturing discrete event simulation systems are quite established to support multiple planning decisions. During the recent years, the productivity is increasing by using simulation methods. The motivation for this thesis is to use online simulation not only for planning decisions, but also for a wide range of operational decisions. Therefore an integrated online simulation system for short term forecasting has been developed. The production environment is a mature high mix logic wafer fab. It has been selected because of its vast potential for performance improvement. In this thesis several aspects of online simulation will be addressed: The first aspect is the implementation of an online simulation system in semiconductor manufacturing. The general problem is to achieve a high speed, a high level of detail, and a high forecast accuracy. To resolve these problems, an online simulation system has been created. The simulation model has a high level of detail. It is created automatically from underling fab data. To create such a simulation model from fab data, additional problems related to the underlying data arise. The major parts are the data access, the data integration, and the data quality. These problems have been solved by using an integrated data model with several data extraction, data transformation, and data cleaning steps. The second aspect is related to the accuracy of online simulation. The overall problem is to increase the forecast horizon, increase the level of detail of the forecast and reduce the forecast error. To provide useful forecast results, the simulation model contains a high level of modeling details and a proper initialization. The influences on the forecast quality will be analyzed. The results show that the simulation forecast accuracy achieves good quality to predict future fab performance. The last aspect is to find ways to use simulation forecast results to improve the fab performance. Numerous applications have been identified. For each application a description is available. It contains the requirements of such a forecast, the decision variables, and background information. An application example shows, where a performance problem exists and how online simulation is able to resolve it. To further enhance the real time capability of online simulation, a major part is to investigate new ways to connect the simulation model with the wafer fab. For fab driven simulation, the simulation model and the real wafer fab run concurrently. The wafer fab provides several events to update the simulation during runtime. So the model is always synchronized with the real fab. It becomes possible to start a simulation run in real time. There is no further delay for data extraction, data transformation and model creation. A prototype for a single work center has been implemented to show the feasibility

Proceedings of the ECMLPKDD 2015 Doctoral Consortium

ECMLPKDD 2015 Doctoral Consortium was organized for the second time as part of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), organised in Porto during September 7-11, 2015. The objective of the doctoral consortium is to provide an environment for students to exchange their ideas and experiences with peers in an interactive atmosphere and to get constructive feedback from senior researchers in machine learning, data mining, and related areas. These proceedings collect together and document all the contributions of the ECMLPKDD 2015 Doctoral Consortium