Towards a pervasive data mining engine: architecture overview

Current data mining engines are difficult to use, requiring optimizations by data mining experts in order to provide optimal results. To solve this problem a new concept was devised, by maintaining the functionality of current data mining tools and adding pervasive characteristics such as invisibility and ubiquity which focus on their users, providing better ease of use and usefulness, by providing autonomous and intelligent data mining processes. This article introduces an architecture to implement a data mining engine, composed by four major components: database; Middleware (control); Middleware (processing); and interface. These components are interlinked but provide independent scaling, allowing for a system that adapts to the user’s needs. A prototype has been developed in order to test the architecture. The results are very promising and showed their functionality and the need for further improvements.

Estudio de los modos de vida e historia biológica de las poblaciones humanas de la región central de argentina desde el registro bioarqueológico. Lifestyles and biological history of human populations of the central region of argentina from bioarchaeological record.

Se pretende aportar al estudio de la estructura, historia biológica y estilos de vida de las poblaciones que habitaron la región central de Argentina durante el Holoceno, desde una perspectiva que combina los aportes teóricos y metodológicos de la Genética del paisaje y la Bioarqueología. Interesa a) identificar barreras de diferenciación morfológica entre poblaciones, b) poner a prueba modelos poblacionales para explicar la variación observada e identificar las variables que contribuyan a dicha diferenciación, c) evaluar la congruencia de los resultados obtenidos, d) reconstruir los patrones de movilidad residencial de las poblaciones, e) estudiar sus patrones dietarios considerando diferencias temporales y espaciales, f) identificar indicadores de diversos tipos de estrés (nutricional, funcional), así como traumas, g) estudiar las historias tafonómicas del registro bioarqueológico regional, y h) proponer un modelo para explicar el poblamiento y la evolución local de las poblaciones que habitaron esta región, a partir de la información arqueológica y bioantropológica. Para el análisis de los patrones espaciales de variación biológica se trabajará a partir del registro de rasgos epigenéticos craneales, medidas lineales y datos obtenidos a partir de morfometría geométrica sobre fotografías en 2D sobre muestras arqueológicas procedentes de esta región y de otras regiones geográficas de la Argentina. Para el análisis de la estructura de la población se trabajará a partir del cálculo de la matriz R para datos morfológicos y sus estimaciones derivadas (distancia D², Fst, coordenadas principales) y la aplicación del modelo de Harpending y Ward. Desde la genética del paisaje, se realizarán análisis de autocorrelación espacial, barreras genéticas y análisis geoestadísticos (kriging). Para el estudio de los modos de vida a partir del registro bioarqueológico se relevarán patologías dento-alveolares y alteraciones vinculadas con la salud bucal tales como desgaste dental –a nivel micro y macroscópico- caries, abscesos, pérdidas dentales antemortem, cálculos, hipoplasias, marcadores esqueletales de salud y lesiones traumáticas. Se analizarán isótopos estables (δ13C, δ15N, 86Sr y 87Sr) en restos óseos humanos de diversos sitios arqueológicos con el objetivo de reconstruir patrones dietarios y analizar la movilidad residencial y migración de las poblaciones. Paralelamente, se establecerán procedimientos de control tafonómico de los restos óseos, y se harán análisis específicos para estudiar las historias tafonómicas y evaluar el grado de integridad de los contextos de depositación y de las colecciones en general. Estimamos que el análisis de los patrones espaciales y temporales de variabilidad morfológica craneofacial, así como el estudio de las dietas a partir de información isotópica y bioarqueológica, de las migraciones y la movilidad residencial de las poblaciones a partir de isótopos de estroncio, la reconstrucción de comportamientos y actividades cotidianas a partir de marcadores de estrés músculo-esqueletal, en un marco cronológico y espacial constituye un aporte novedoso y eficaz que permitirá incrementar de manera substancial la información sobre la evolución de las poblaciones originarias del centro del territorio argentino. The aim of this project is to study the structure, biological history and lifestyles of the people that inhabitated the central region of Argentina during the Holocene, from a perspective that combines theoretical and methodological contributions of Landscape Genetics and Bioarchaeology. To analyze the spatial patterns of biological variation we consider epigenetic cranial traits, linear measurements and data obtained from geometric morphometric on 2D photographs. Morphological variation will be focused on landscape genetics (autocorrelation, genetic barriers and geostatistical analysis –kriging-) and population structure (matrix R, D², Fst, principal coordinates, Harpendig and Ward model). For the study of lifestyles from bioarchaeological record we consider alveolar pathologies and disorders related to oral health such as tooth wear, micro and macroscopic level, caries, abscesses, antemortem tooth loss, hypoplasia, markers skeletal health and traumatic injuries, as well as taphonomic processes. Stable isotopes will be analyzed (δ13C, d15N, 86Sr and 87Sr) in human skeletal remains from various archaeological sites in order to reconstruct and analyze dietary patterns of residential mobility and migration of populations. It will be established procedures of taphonomic control on skeletal remains, analysis to study taphonomic histories and assess the degree of completeness of depositional context and collection, in general terms. We consider that analysis of spatial and temporal patterns of variability in craniofacial morphology and the study of health and diets from isotopic and bioarchaeological data, migration and residential mobility patterns from strontium isotopes, as well as activity patterns from stress markers is a novel and effective contribution that will substantially increase the information about the local evolution of populations that inhabitated the center of Argentina.

La cascarilla cerámica y su uso innovador

The ceramic shell is a material mainly used for making foundry molds. This research demonstrates that ceramic shell can be used for making sculptures with exceptional definition in its finish. The research has identified a number of advantages of the material to meet the challenges of an artist during the making of a sculpture. The research has been developed in six stages: In the first stage data were collected from the chaff as the process material. This was the starting point for research. In the second stage, we have set the appropriate composition of the slurry, both in percentage and type of binder, and firing curve. To this end, we evaluated the application characteristics, thickness, drying, mechanical strength, the reduction coefficient and porosity. In the third stage it was observed that the husk is suitable for all types of materials acting as support. It was also found that the slurry can be used with various sculptural processes: modeling, molding using silicone or plaster mold, shuttering, with internal metal frame, and so on. In addition, we have established methods to repair and modify the husk by hand and power tools. In the fourth stage we have found ways to modify the surface of the husk with other minerals that affect the structure: introduction of filing of copper, bronze and iron in the slurry ceramics, different staining procedure in hot or cold, by enamel slip, and so on. In the fifth stage sculptures were made using the methods established in the previous stages, to verify this hypothesis. The sixth stage, which is annexed, contains a new method to process the ceramic shell as a mold in casting that emerged from the proven methods in the investigation.

Managing Business Processes in Corporate Expansion

Yrityksen laajentuessa kansainvälisesti, olemassa olevat rutiinit jäävät vanhoiksi ja liiketoimintaprosessien johtaminen muuttuu. Kyseisten prosessien täytyy olla läpinäkyviä ja tietovirtojen hyvin suunniteltuja. Prosessien harmonisointi aiheuttaa haasteita yrityksessä ja konsernin etu tulee ottaa huomioon. Ahlstrom konserni laajentuu merkittävästi kaikilla liiketoiminta-alueillaan ja kansainvälinen laajentuminen vie Ahlstrom Glassfibre Oy:n täysin uuteen tilanteeseen. Liiketoimintaprosessien johtamiseen vaikuttavat konsernin ohjaus, mahdollisuudet muutosten implementoimiseksi, toimintaympäristön tekijät ja järjestelmien muodostama arkkitehtuuri. Tässä tutkimuksessa keskitytään ydinprosessien tietovirtoihin ja työ on tehty Karhulan tehtaalla Suomessa. Johtamismallin luomiseksi vaaditaan yrityksessä ongelmia määrittelevää työskentelyä. Tämä ongelmanmääritys oli työn tärkein tavoite. Ongelma-alueiden tutkimuksen pohjalta muodostettiin ratkaisu, jossa käsiteltiin systemaattisen liiketoimintaprosessien johtamisen mahdollisuuksia ja vaatimuksia. Lopputuloksena voidaan todeta, että suurin painopiste löytyy informaatioteknologian ja liiketoiminnan rajapinnoista. Tähän työhön liittyvät myös prossien harmonisointi ja integrointi.

Ocean surface winds drive dynamics of transoceanic aerial movements

Global wind patterns influence dispersal and migration processes of aerial organisms, propagules and particles, which ultimately could determine the dynamics of colonizations, invasions or spread of pathogens. However, studying how wind-mediated movements actually happen has been hampered so far by the lack of high resolution global wind data as well as the impossibility to track aerial movements. Using concurrent data on winds and actual pathways of a tracked seabird, here we show that oceanic winds define spatiotemporal pathways and barriers for large-scale aerial movements. We obtained wind data from NASA SeaWinds scatterometer to calculate wind cost (impedance) models reflecting the resistance to the aerial movement near the ocean surface. We also tracked the movements of a model organism, the Cory's shearwater (Calonectris diomedea), a pelagic bird known to perform long distance migrations. Cost models revealed that distant areas can be connected through"wind highways" that do not match the shortest great circle routes. Bird routes closely followed the low-cost"wind-highways" linking breeding and wintering areas. In addition, we found that a potential barrier, the near surface westerlies in the Atlantic sector of the Intertropical Convergence Zone (ITCZ), temporally hindered meridional trans-equatorial movements. Once the westerlies vanished, birds crossed the ITCZ to their winter quarters. This study provides a novel approach to investigate wind-mediated movements in oceanic environments and shows that large-scale migration and dispersal processes over the oceans can be largely driven by spatiotemporal wind patterns.

Data Consistency by a Metadata Management Solution

This thesis consists of three main theoretical themes: quality of data, success of information systems, and metadata in data warehousing. Loosely defined, metadata is descriptive data about data, and, in this thesis, master data means reference data about customers, products etc. The objective of the thesis is to contribute to an implementation of a metadata management solution for an industrial enterprise. The metadata system incorporates a repository, integration, delivery and access tools, as well as semantic rules and procedures for master data maintenance. It targets to improve maintenance processes and quality of hierarchical master data in the case company’s informational systems. That should bring benefits to whole organization in improved information quality, especially in cross-system data consistency, and in more efficient and effective data management processes. As the result of this thesis, the requirements for the metadata management solution in case were compiled, and the success of the new information system and the implementation project was evaluated.

Georeferenced database generation with the purpose of hydrologic molding in reservoirs of the hydrographic basin of Jaguaribe river in the state of Ceará, Brazil

The edafoclimatic conditions of the Brazilian semiarid region favor the water loss by surface runoff. The state of Ceará, almost completely covered by semiarid, has developed public policies for the construction of dams in order to attend the varied water demand. Several hydrological models were developed to support decisive processes in the complex management of reservoirs. This study aimed to establish a methodology for obtaining a georeferenced database suitable for use as input data in hydrological modeling in the semiarid of Ceará. It was used images of Landsat satellite and SRTM Mission, and soil maps of the state of Ceará. The Landsat images allowed the determination of the land cover and the SRTM Mission images, the automatic delineation of hydrographic basins. The soil type was obtained through the soil map. The database was obtained for Jaguaribe River hydrographic basin, in the state of Ceará, and is applicable to hydrological modeling based on the Curve Number method for estimating the surface runoff.

Applications of Industrial Statistics

This dissertation examines knowledge and industrial knowledge creation processes. It looks at the way knowledge is created in industrial processes based on data, which is transformed into information and finally into knowledge. In the context of this dissertation the main tool for industrial knowledge creation are different statistical methods. This dissertation strives to define industrial statistics. This is done using an expert opinion survey, which was sent to a number of industrial statisticians. The survey was conducted to create a definition for this field of applied statistics and to demonstrate the wide applicability of statistical methods to industrial problems. In this part of the dissertation, traditional methods of industrial statistics are introduced. As industrial statistics are the main tool for knowledge creation, the basics of statistical decision making and statistical modeling are also included. The widely known Data Information Knowledge Wisdom (DIKW) hierarchy serves as a theoretical background for this dissertation. The way that data is transformed into information, information into knowledge and knowledge finally into wisdom is used as a theoretical frame of reference. Some scholars have, however, criticized the DIKW model. Based on these different perceptions of the knowledge creation process, a new knowledge creation process, based on statistical methods is proposed. In the context of this dissertation, the data is a source of knowledge in industrial processes. Because of this, the mathematical categorization of data into continuous and discrete types is explained. Different methods for gathering data from processes are clarified as well. There are two methods for data gathering in this dissertation: survey methods and measurements. The enclosed publications provide an example of the wide applicability of statistical methods in industry. In these publications data is gathered using surveys and measurements. Enclosed publications have been chosen so that in each publication, different statistical methods are employed in analyzing of data. There are some similarities between the analysis methods used in the publications, but mainly different methods are used. Based on this dissertation the use of statistical methods for industrial knowledge creation is strongly recommended. With statistical methods it is possible to handle large datasets and different types of statistical analysis results can easily be transformed into knowledge.

Aqueous-phase reforming of renewables for selective hydrogen production in the presence of supported platinum catalysts

The evolution of our society is impossible without a constant progress in life-important areas such as chemical engineering and technology. Innovation, creativity and technology are three main components driving the progress of chemistry further towards a sustainable society. Biomass, being an attractive renewable feedstock for production of fine chemicals, energy-rich materials and even transportation fuels, captures progressively new positions in the area of chemical technology. Knowledge of heterogeneous catalysis and chemical technology applied to transformation of biomass-derived substances will open doors for a sustainable economy and facilitates the discovery of novel environmentally-benign processes which probably will replace existing technologies in the era of biorefinary. Aqueous-phase reforming (APR) is regarded as a promising technology for production of hydrogen and liquids fuels from biomass-derived substances such as C3-C6 polyols. In the present work, aqueous-phase reforming of glycerol, xylitol and sorbitol was investigated in the presence of supported Pt catalysts. The catalysts were deposited on different support materials, including Al2O3, TiO2 and carbons. Catalytic measurements were performed in a laboratory-scale continuous fixedbed reactor. An advanced analytical approach was developed in order to identify reaction products and reaction intermediates in the APR of polyols. The influence of the substrate structure on the product formation and selectivity in the APR reaction was also investigated, showing that the yields of the desired products varied depending on the substrate chain length. Additionally, the influence of bioethanol additive in the APR of glycerol and sorbitol was studied. A reaction network was advanced explaining the formation of products and key intermediates. The structure sensitivity in the aqueous-phase reforming reaction was demonstrated using a series of platinum catalysts supported on carbon with different Pt cluster sizes in the continuous fixed-bed reactor. Furthermore, a correlation between texture physico-chemical properties of the catalysts and catalytic data was established. The effect of the second metal (Re, Cu) addition to Pt catalysts was investigated in the APR of xylitol showing a superior hydrocarbon formation on PtRe bimetallic catalysts compared to monometallic Pt. On the basis of the experimental data obtained, mathematical modeling of the reaction kinetics was performed. The developed model was proven to successfully describe experimental data on APR of sorbitol with good accuracy.

Hankinnan prosessien systemaattinen kehittäminen

Tämän pro gradu -tutkielman tavoitteena oli standardoida ja kehittää hankinnan prosesseja systemaattisesti. Prosessien standardoiminen edesauttaa organisaation itseohjautuvuutta ja parantaa organisaation kyvykkyyttä. Tämä tutkielma tuottaa uutta tutkimustietoa tutkimusaukkoon hankinnan prosessien systemaattisesta kehittämisestä. Tutkielman teoriaosassa käsitellään prosessiajattelua, ISO 9001 standardin vaikutusta hankintatoimintaan, tunnistetaan hankinnan prosesseja ja esitetään erilaisia hankinnan prosesseihin soveltuvia LEAN Six Sigma kehitystyökaluja. Tutkielman empiirinen osio on toteutettu toimeksiantona suurelle teollisuusyritykselle. Tämän tutkielman empiirisessä osiossa on yhdistelty kvalitatiiviselle ja kvantitatiiviselle tutkimukselle ominaisia tutkimusmetodologioita. Tutkimusmetodologioiden yhdisteleminen tuottaa lisäarvoa tutkielman toteutukselle ja parantaa työn luotettavuutta. Tässä tutkielmassa käytetyt tutkimusmenetelmät koostuvat kvantitatiiviselle tutkimukselle ominaisesta kyselystä hankinnan prosessien nykytilan selvittämiseksi sekä kvalitatiivisen tutkimuksen tutkimusmenetelmille ominaisesta tapaustutkimuksesta. Kyselyn avulla muodostettiin analyysi hankinnan prosessien nykytilasta, jonka pohjalta toimeksiantajayritykselle ehdotettiin kehitettäviä hankinnan prosesseja. Lopulliseksi kehityskohteeksi valittu prosessi määriteltiin aivoriihessä kerätyn tiedon perusteella kehityspotentiaalin esille tuovasta nelikentästä. Kehitettävä prosessi asemoitui samalla tapaustutkimuksella tutkittavaksi tapaukseksi. Kehitettäväksi prosessiksi valittiin saapuvan tavaran vastaanotto ja visuaalinen tarkastaminen. Prosessia kehitettiin mallintamalla ja LEAN Six Sigma menetelmiä hyödyntäen. Prosessimallinnuksen sekä LEAN Six Sigma menetelmien tueksi kerättiin tietoa aivoriihistä ja teemahaastatteluista. Tutkielman tuloksena toimeksiantajayritys sai kokonaiskuvan hankinnan prosessien nykytilasta, kehitetyn tavoiteprosessin ja työohjeen saapuvan tavaran vastaanotolle ja visuaaliselle tarkastukselle sekä jatkossa hankinnan prosessien standardoimista ja kehittämistä helpottavan hankinnan prosessin systemaattisen kehittämismallin. Hankinnan prosessin systemaattinen kehittämismalli on uutta tutkimustietoa, joka asemoituu hankinnan prosessien kehittämisen tutkimusaukkoon. Hankinnan prosessin systemaattista kehittämismallia ei tämän tutkielman pohjalta voida yleistää, koska tutkielma on toteutettu toimeksiantajayrityksen lähtökohdista. Johtopäätöksenä voidaan todeta, että toimeksiantajayritys, muut organisaatiot sekä tutkimuskenttä tarvitsevat lisää tietoa hankinnan prosessien kehittämisestä. Hankinnan prosessien kehittämistä tulisi tutkia enemmän ja erityisesti tässä tutkielmassa esitettyä kehittämismallia tulisi jatkossa testata niin, että kehittämismallin toimivuus voitaisiin yleistää.

L’analyse de composants émotionnels dans des stratégies d’apprentissage

Un certain nombre de théories pédagogiques ont été établies depuis plus de 20 ans. Elles font appel aux réactions de l’apprenant en situation d’apprentissage, mais aucune théorie pédagogique n’a pu décrire complètement un processus d’enseignement en tenant compte de toutes les réactions émotionnelles de l’apprenant. Nous souhaitons intégrer les émotions de l’apprenant dans ces processus d’apprentissage, car elles sont importantes dans les mécanismes d’acquisition de connaissances et dans la mémorisation. Récemment on a vu que le facteur émotionnel est considéré jouer un rôle très important dans les processus cognitifs. Modéliser les réactions émotionnelles d’un apprenant en cours du processus d’apprentissage est une nouveauté pour un Système Tutoriel Intelligent. Pour réaliser notre recherche, nous examinerons les théories pédagogiques qui n’ont pas considéré les émotions de l’apprenant. Jusqu’à maintenant, aucun Système Tutoriel Intelligent destiné à l’enseignement n’a incorporé la notion de facteur émotionnel pour un apprenant humain. Notre premier objectif est d’analyser quelques stratégies pédagogiques et de détecter les composantes émotionnelles qui peuvent y être ou non. Nous cherchons à déterminer dans cette analyse quel type de méthode didactique est utilisé, autrement dit, que fait le tuteur pour prévoir et aider l’apprenant à accomplir sa tâche d’apprentissage dans des conditions optimales. Le deuxième objectif est de proposer l’amélioration de ces méthodes en ajoutant les facteurs émotionnels. On les nommera des « méthodes émotionnelles ». Le dernier objectif vise à expérimenter le modèle d’une théorie pédagogique améliorée en ajoutant les facteurs émotionnels. Dans le cadre de cette recherche nous analyserons un certain nombre de théories pédagogiques, parmi lesquelles les théories de Robert Gagné, Jerome Bruner, Herbert J. Klausmeier et David Merrill, pour chercher à identifier les composantes émotionnelles. Aucune théorie pédagogique n’a mis l’accent sur les émotions au cours du processus d’apprentissage. Ces théories pédagogiques sont développées en tenant compte de plusieurs facteurs externes qui peuvent influencer le processus d’apprentissage. Nous proposons une approche basée sur la prédiction d’émotions qui est liée à de potentielles causes déclenchées par différents facteurs déterminants au cours du processus d’apprentissage. Nous voulons développer une technique qui permette au tuteur de traiter la réaction émotionnelle de l’apprenant à un moment donné au cours de son processus d’apprentissage et de l’inclure dans une méthode pédagogique. Pour atteindre le deuxième objectif de notre recherche, nous utiliserons un module tuteur apprenant basé sur le principe de l’éducation des émotions de l’apprenant, modèle qui vise premièrement sa personnalité et deuxièmement ses connaissances. Si on défini l’apprenant, on peut prédire ses réactions émotionnelles (positives ou négatives) et on peut s’assurer de la bonne disposition de l’apprenant, de sa coopération, sa communication et l’optimisme nécessaires à régler les problèmes émotionnels. Pour atteindre le troisième objectif, nous proposons une technique qui permet au tuteur de résoudre un problème de réaction émotionnelle de l’apprenant à un moment donné du processus d’apprentissage. Nous appliquerons cette technique à une théorie pédagogique. Pour cette première théorie, nous étudierons l’effet produit par certaines stratégies pédagogiques d’un tuteur virtuel au sujet de l’état émotionnel de l’apprenant, et pour ce faire, nous développerons une structure de données en ligne qu’un agent tuteur virtuel peut induire à l’apprenant des émotions positives. Nous analyserons les résultats expérimentaux en utilisant la première théorie et nous les comparerons ensuite avec trois autres théories que nous avons proposées d’étudier. En procédant de la sorte, nous atteindrons le troisième objectif de notre recherche, celui d’expérimenter un modèle d’une théorie pédagogique et de le comparer ensuite avec d’autres théories dans le but de développer ou d’améliorer les méthodes émotionnelles. Nous analyserons les avantages, mais aussi les insuffisances de ces théories par rapport au comportement émotionnel de l’apprenant. En guise de conclusion de cette recherche, nous retiendrons de meilleures théories pédagogiques ou bien nous suggérerons un moyen de les améliorer.

Reflections on practical approaches to involving children and young people in the data analysis process

This article reflects on key methodological issues emerging from children and young people's involvement in data analysis processes. We outline a pragmatic framework illustrating different approaches to engaging children, using two case studies of children's experiences of participating in data analysis. The article highlights methods of engagement and important issues such as the balance of power between adults and children, training, support, ethical considerations, time and resources. We argue that involving children in data analysis processes can have several benefits, including enabling a greater understanding of children's perspectives and helping to prioritise children's agendas in policy and practice. (C) 2007 The Author(s). Journal compilation (C) 2007 National Children's Bureau.

RACORO extended-term, aircraft observations of boundary-layer clouds

A first-of-a-kind, extended-term cloud aircraft campaign was conducted to obtain an in-situ statistical characterization of continental boundary-layer clouds needed to investigate cloud processes and refine retrieval algorithms. Coordinated by the Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign operated over the ARM Southern Great Plains (SGP) site from 22 January to 30 June 2009, collecting 260 h of data during 59 research flights. A comprehensive payload aboard the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft measured cloud microphysics, solar and thermal radiation, physical aerosol properties, and atmospheric state parameters. Proximity to the SGP's extensive complement of surface measurements provides ancillary data that supports modeling studies and facilitates evaluation of a variety of surface retrieval algorithms. The five-month duration enabled sampling a range of conditions associated with the seasonal transition from winter to summer. Although about two-thirds of the cloud flights occurred in May and June, boundary-layer cloud fields were sampled under a variety of environmental and aerosol conditions, with about 77% of the flights occurring in cumulus and stratocumulus. Preliminary analyses illustrate use of these data to analyze cloud-aerosol relationships, characterize the horizontal variability of cloud radiative impacts, and evaluate surface-based retrievals. We discuss how an extended-term campaign requires a simplified operating paradigm that is different from that used for typical, short-term, intensive aircraft field programs.

Pocket data mining - big data on small devices

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.

A survey of data mining techniques for social media analysis

Social network has gained remarkable attention in the last decade. Accessing social network sites such as Twitter, Facebook LinkedIn and Google+ through the internet and the web 2.0 technologies has become more affordable. People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters. The heavy reliance on social network sites causes them to generate massive data characterised by three computational issues namely; size, noise and dynamism. These issues often make social network data very complex to analyse manually, resulting in the pertinent use of computational means of analysing them. Data mining provides a wide range of techniques for detecting useful knowledge from massive datasets like trends, patterns and rules [44]. Data mining techniques are used for information retrieval, statistical modelling and machine learning. These techniques employ data pre-processing, data analysis, and data interpretation processes in the course of data analysis. This survey discusses different data mining techniques used in mining diverse aspects of the social network over decades going from the historical techniques to the up-to-date models, including our novel technique named TRCM. All the techniques covered in this survey are listed in the Table.1 including the tools employed as well as names of their authors.