Time Series Data Mining: A Retail Application Using SAS Enterprise Miner

Modern technologies have allowed for the amassment of data at a rate never encountered before. Organizations are now able to routinely collect and process massive volumes of data. A plethora of regularly collected information can be ordered using an appropriate time interval. The data would thus be developed into a time series. With such data, analytical techniques can be employed to collect information pertaining to historical trends and seasonality. Time series data mining methodology allows users to identify commonalities between sets of time-ordered data. This technique is supported by a variety of algorithms, notably dynamic time warping (DTW). This mathematical technique supports the identification of similarities between numerous time series. The following research aims to provide a practical application of this methodology using SAS Enterprise Miner, an industry-leading software platform for business analytics. Due to the prevalence of time series data in retail settings, a realistic product sales transaction data set was analyzed. This information was provided by dunnhumbyUSA. Interpretations were drawn from output that was generated using “TS nodes” in SAS Enterprise Miner

Internal Migration and Regional Population Dynamics in Europe: United Kingdom Case Study

This case study examines recent population change patterns and internal migration activity in the United Kingdom. A wealth of knowledge about population dynamics in Britain is revealed. The spatial patterns of population change and net migration are intricate mosaics of gains and losses. Gains and losses in population were principally determined by net internal migration. The decade long population change patterns and one year long migration patterns were in close agreement. This was surprising in view of temporal instability in population change and migration patterns. The dominant spatial pattern was one of deconcentration from the cores of city regions to hinterlands for both the largest metropolises and also their subsidiary partner cities. There were also signs of loss in population and migrants in declining resource regions(former mining areas, fishing ports) and gains in new resource frontiers - particularly in northeast Scotland reflecting the vigorous development of onshore facilities for the offshore oil and gas fields of the North Sea. The pattern of overall population and migrant redistribution was predominantly that of the middle labour force/family ages reinforced at much lower mobility levels but with sharper patterns of redistribution by the pre-retirement and retirement ages. People in the young adult ages in contrast redistributed to different destinations, showing a unique shift to the dense neighbourhoods of big cities. With respect to the urban system, there was significant redistribution both downward and outward. Downward redistribution meant shifts from large metropolitan cities to medium and small sized freestanding cities. Outward redistribution meant shifts to the outer commuting rings around cities, often deep into the countryside, This was not a return to the rural idyll, merely the expansion of the daily urban systems to cover most of lowland Britain. Strong preferences for low density living were revealed by shifts towards districts in Rural Areas and by net flows to low density wards and sectors. Similar strong shifts out of areas of above average into below average unemployment were detected, though both relationships with density and unemployment were either not present or weak for young adults. Some ambiguity was revealed in the fortunes of Inner London areas. Migration data from the 1991 Census showed intense outward movement. Downward population shifts were on a lesser scale because of the compensating effects of higher than average natural increase and high immigration. However, a re-analysis of 1991 population by ONS led to a substantial upward revision of London borough populations, and so places doubt on the size of outward shift of population through internal migration

Modelling the Impact of Transport Planning Policy Upon Land Use

In this paper the results from the validation of an integrated land use and transport model are described. The goodness-of-fit for the forecasts are considered not only for the time horizon, but also in terms of the change over time, which is a much more sensitive test. The sensitivity of the land use and transport forecasts to changes in the monetary cost of travel are examined to see to what extent the location of housing, population, employment and jobs, and the journey to work respond to such changes. The spatial effects of these changes are demonstrated by finding the land use distribution for three concentric rings. The influence of land use changes upon time and money expenditure are examined by using the relevant elements of the generalised cost functions with the trip matrices computed under three different assumptions when the monetary cost of travel is varied: keeping modal split and land use constant, keeping only land use constant, and allowing both to respond. The paper is concluded with discussion of further model improvements and applications of the model

Applying knowledge management in education : teaching database normalization : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Information Science at Massey University

In tertiary education, Information Science has been attracting more attention in both teaching and learning. However, along the course on the database design theory, learners always find it hard to grasp the knowledge on database normalisation and hard to apply different levels of the normal forms while designing a database. This results poor database construction and difficulties in database maintenance. In regard to this teaching and learning dilemma, academic teaching staff should, on the one hand, pay more attention to organising different teaching resources on database normalisation concepts and making the best use of the existing and newly developed resources so as to make the teaching environment more adaptive and more sharable. and on the other hand, apply different teaching methods to different students according to their knowledge levels by understanding the nature of each learner's behaviour, interests and preferences concerning the existing learning resources. However, at present there is no effective Information Technology tool to use in considering the dynamic nature of knowledge discovery, creation, transfer utilisation and reuse in this area. This provides an opportunity to examine the potentiality of applying knowledge management in education with the focus on teaching database normalisation, in terms of knowledge discovering, sharing, utilisation and reuse. This thesis contains a review of knowledge management and web mining technologies in the education environment, presents a dynamic knowledge management framework for better utilising teaching resource in the area of database normalisation and diagnoses the students' learning patterns and behaviours to assist effective teaching and learning. It is argued that knowledge management-supported education can work as a value-added process which supports the different needs of teachers and learners

Identifying Agile Requirements Engineering Patterns in Industry

Agile Software Development (ASD) is gaining in popularity in today´s business world. Industry is adopting agile methodologies both to accelerate value delivery and to enhance the ability to deal with changing requirements. However, ASD has a great impact on how Requirements Engineering (RE) is carried out in agile environments. The integration of Human-Centered Design (HCD) plays an important role due to the focus on user and stakeholder involvement. To this end, we aim to introduce agile RE patterns as main objective of this paper. On the one hand, we will describe our pattern mining process based on empirical research in literature and industry. On the other hand, we will discuss our results and provide two examples of agile RE patterns. In sum, the pattern mining process identifies 41 agile RE patterns. The accumulated knowledge will be shared by means of a web application.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71938-RED

An introduction to Graph Data Management

A graph database is a database where the data structures for the schema and/or instances are modeled as a (labeled)(directed) graph or generalizations of it, and where querying is expressed by graph-oriented operations and type constructors. In this article we present the basic notions of graph databases, give an historical overview of its main development, and study the main current systems that implement them

Mining Knowledge in Astrophysical Massive Data Sets

Modern scientific data mainly consist of huge datasets gathered by a very large number of techniques and stored in very diversified and often incompatible data repositories. More in general, in the e-science environment, it is considered as a critical and urgent requirement to integrate services across distributed, heterogeneous, dynamic "virtual organizations" formed by different resources within a single enterprise. In the last decade, Astronomy has become an immensely data rich field due to the evolution of detectors (plates to digital to mosaics), telescopes and space instruments. The Virtual Observatory approach consists into the federation under common standards of all astronomical archives available worldwide, as well as data analysis, data mining and data exploration applications. The main drive behind such effort being that once the infrastructure will be completed, it will allow a new type of multi-wavelength, multi-epoch science which can only be barely imagined. Data Mining, or Knowledge Discovery in Databases, while being the main methodology to extract the scientific information contained in such MDS (Massive Data Sets), poses crucial problems since it has to orchestrate complex problems posed by transparent access to different computing environments, scalability of algorithms, reusability of resources, etc. In the present paper we summarize the present status of the MDS in the Virtual Observatory and what is currently done and planned to bring advanced Data Mining methodologies in the case of the DAME (DAta Mining & Exploration) project.Comment: Pages 845-849 1rs International Conference on Frontiers in Diagnostics Technologie