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Studies on data mining are being pursued in many different research areas, such as Machine Learning, Statistics, and Databases. The work presented in this thesis is based on the database perspective of data mining. The main focuses are on the temporal aspects of data mining problems, especially association rule discovery, and issues on the integration of data mining and database systems. Firstly, a theoretical framework for temporal data mining is proposed in this thesis. Within this framework, not only potential patterns but also temporal features associated with the patterns are expected to be discovered. Calendar time expressions are suggested to represent temporal features and the minimum frequency of patterns is introduced as a new threshold in the model of temporal data mining. The framework also emphasises the necessary components to support temporal data mining tasks. As a specialisation of the proposed framework, the problem of mining temporal association rules is investigated. The methodology adopted in this thesis is eventually discovering potential temporal rules by alternatively using special search techniques for various restricted problems in an interactive and iterative process. Three forms of interesting mining tasks for temporal association rules with certain constraints are identified. These tasks are the discovery of valid time periods of association rules, the discovery of periodicities of association rules, and the discovery of association rules with temporal features. The search techniques and algorithms for those individual tasks are developed and presented in this thesis. Finally, an integrated query and mining system (IQMS) is presented in this thesis, covering the description of an interactive query and mining interface (IQMI) supplied by the IQMS system, the presentation of an SQL-like temporal mining language (TML) with the ability to express various data mining tasks for temporal association rules, and the suggestion of an IQMI-based interactive data mining process. The implementation of this system demonstrates an alternative approach for the integration of the DBMS and data mining functions.

Various works have demonstrated the usage of action as a critical component in allowing autonomous agents to learn about objects in the environment. The importance of memory becomes evident when these agents try to learn about complex objects. This necessity primarily stems from the fact that simpler agents behave reactively to stimuli in their attempt to learn about the nature of the object. However, complex objects have the property of giving rise to temporally varying sensory data as the agent interacts with the object. Therefore, reactive behavior becomes a hindrance in learning these complex objects, thus, prompting the need for memory. A straightforward approach to memory, visual memory, is where sensory data is directly represented. Another mechanism is skill-based memory or habit formation. In the latter mechanism the sequence of actions performed for a task is retained. The main hypothesis of this thesis is that since action seems to play an important role in simple perceptual understanding it may also serve as a good memory representation. In order to test this hypothesis a series of comparative tests were carried out to determine the merits of each of these representations. It turns out that skill memory performs significantly better at recognition tasks than visual memory. Furthermore, it was demonstrated in a related experiment that action forms a good intermediate representation of the sensory data. This provides support to theories that propose that various sensory modalities can ideally be represented in terms of action. This thesis successfully extends action to the role of understanding of complex objects.

With the rapidly growing volumes of data from various sources, new tools and computational theories are required to extract useful information (knowledge) from large databases. Data mining techniques such as association rules have been proved to be effective in searching hidden knowledge in a large database. However, if we want to extract knowledge from data with temporal components, it becomes necessary to incorporate temporal semantics with the traditional data mining techniques. As mining techniques evolves, mathematical techniques become more involved to help improve the quality and diversity of mining. Fuzzy theory is one that has been adopted for this purpose. Up to now, many approaches have been proposed to discover temporal association rules or fuzzy association rules, respectively. However, no work is contributed on mining fuzzy temporal patterns. We propose in this thesis two data mining systems for discovering fuzzy temporal association rules and fuzzy periodic association rules, respectively. The mined patterns are expressed in fuzzy temporal and periodic association rules which satisfy the temporal requirements specified by the user. Temporal requirements specified by human beings tend to be ill-defined or uncertain. To deal with this kind of uncertainty, a fuzzy calendar algebra is developed to allow users to describe desired temporal requirements in fuzzy calendars easily and naturally. Moreover, the fuzzy calendar algebra helps the construction of desired time intervals in which interesting patterns are discovered and presented in terms of fuzzy temporal and periodic association rules. In our system of mining fuzzy temporal association rules, a border-based mining algorithm is proposed to find association rules incrementally. By keeping useful information of the database in a border, candidate itemsets can be computed in an efficient way. Updating of the discovered knowledge due to addition and deletion of transactions can also be done efficiently. The kept information can be used to help save the work of counting and unnecessary scans over the updated database can be avoided. Simulation results show the effectiveness of the proposed system for mining fuzzy temporal association rules. In our mining system for discovering fuzzy periodic association rules, we develop techniques for discovering patterns with periodicity. Patterns with periodicity are those that occur at regular time intervals, and therefore there are two aspects to the problem: finding the pattern, and determining the periodicity. The difficulty of the task lies in the problem of discovering these regular time intervals, i.e., the periodicity. Periodicites in the database are usually not very precise and have disturbances, and might occur at time intervals in multiple time granularities. To discover the patterns with fuzzy periodicity, we utilize the information of crisp periodic patterns to obtain a lower bound for generating candidate itemsets with fuzzy periodicities. Experimental results have shown that our system is effective in discovering fuzzy periodic association rules.

This thesis aims to seek interesting patterns from massive amounts of Flickr data in Sweden with pro- posed new clustering strategies. The aim can be further divided into three objectives. The first one is to acquire large amount of timestamped geolocation data from Flickr servers. The second objective is to develop effective and efficient methods to process the data. More specifically, the methods to be developed are bifold, namely, the preprocessing method to solve the “Big Data” issue encountered in the study and the new clustering method to extract spatio-temporal patterns from data. The third one is to analyze the extracted patterns with scaling analysis techniques in order to interpret human social activities underlying the Flickr Data within the urban envrionment of Sweden. During the study, the three objectives were achieved sequentially. The data employed for this study was vector points downloaded through Flickr Application Programming Interface (API). After data ac- quisition, preprocessing was performed on the raw data. The whole dataset was firstly separated by year based on the temporal information. Then data of each year was accumulated with its former year(s) so that the evovling process can be explored. After that, large datasets were splitted into small pieces and each piece was clipped, georeferenced, and rectified respectively. Then the pieces were merged together for clustering. With respect to clustering, the strategy was developed based on the Delaunay Triangula- tion (DT) and head/tail break rule. After that, the generated clusters were analyzed with scaling analysis techniques and spatio-temporal patterns were interpreted from the analysis results. It has been found that the spatial pattern of the human social activities in the urban environment of Sweden generally follows the power-law distribution and the cities defined by human social activities are evolving as time goes by. To conclude, the contributions of this research are threefold and fulfill the objectives of this study, respectively. Firstly, large amount of Flickr data is acquired and collated as a contribution to other aca- demic researches related to Flickr. Secondly, the clustering strategy based on the DT and head/tail break rule is proposed for spatio-temporal pattern seeking. Thirdly, the evolving of the cities in terms of human activities in Sweden is detected from the perspective of scaling. Future work is expected in major two aspects, namely, data and data processing. For the data aspect, the downloaded Flickr data is expected to be employed by other studies, especially those closely related to human social activities within urban environment. For the processing aspect, new algorithms are expected to either accelerate the processing process or better fit machines with super computing capacities.

A análise de uma população em longo prazo permite a identificação da ausência ou presença de variações nos padrões de ciclo de vida, de distribuição espaço-temporal e dinâmica populacional. O ciclo de vida do camarão sete-barbas Xiphopenaeus kroyeri foi investigado na Enseada de Ubatuba, litoral norte do Estado de São Paulo (23º25\' - 23º27\'S / 45º00\' - 45º03\' W) ao longo de um intervalo de treze anos. Amostras de material biológico, de água de fundo e de sedimento foram coletadas em quatro pontos de amostragem em três períodos de 12 meses cada: janeiro a dezembro de 1998, julho de 2006 a junho de 2007 e setembro de 2010 a agosto de 2011. Dados obtidos em 1999 foram incluídos para as análises de crescimento individual, de longevidade e de idade de maturação. Altas abundâncias de fêmeas maduras e de jovens foram respectivamente associadas a valores de temperatura da água de fundo acima e abaixo da média da região. Indivíduos adultos predominaram em pontos com variação temporal da composição granulométrica do sedimento enquanto que os jovens se estabeleceram naqueles em que o sedimento permaneceu fino entre os períodos. Em 1998, a abundância de jovens, o peso individual de machos e fêmeas de todas as categorias demográficas, a idade de maturação morfológica e fisiológica e a longevidade foram maiores do que nos outros períodos. Os parâmetros da função de crescimento de machos e fêmeas variaram entre os períodos, sem apresentarem uma tendência temporal clara. Os padrões anuais de reprodução e recrutamento foram bastante semelhantes entre os períodos. As alterações nos fatores ambientais provocadas por variações na dinâmica de massas de água, pela ocorrência de El Niño e alterações na intensidade de pesca foram consideradas como possíveis agentes relacionadas às variações nos padrões do ciclo de vida da espécie na região / Long-term studies on a population provide detection of the presence or absence of interannual variation in patterns of its life cycle, spatio-temporal distribution, and dynamics. This study investigate the population of the seabob shrimp Xiphopenaeus kroyeri within a period of 13 years in Ubatuba Bay, northern coast of São Paulo state, Brazil (23º25\' - 23º27\'S / 45º00\' - 45º03\' W). Shrimp, bottom water and sediment samples were collected from four sampling sites during three 12-month periods: January-December 1998, July 2006-June 2007, and September 2010-August 2011. Monthly data collected in 1999 were included in growth, longevity and maturation age analyses. High abundance of mature females and juveniles were associated to the occurrence of temperature values below and above the region average, respectively. Adults predominated in sites that showed temporal variation of sediment texture while juveniles occurred in sites where sediment remained fine between the study periods. In the 1998 period values of juveniles were more abundant, individual weight of all demographic categories was higher, both morphological and physiological maturity was attained later and lifespan was longer than on the following periods. Growth function parameters of males and females varied between periods with no clear temporal trend. Monthly patterns of reproduction and recruitment were similar between the study periods. Changes in the environmental conditions caused by variations in the dynamics of the local water masses, occurrence of El Niño and fishery intensity were considered as possible factors related to the interannual variations in the life cycle pattern of X. kroyeri in the study region

The role of language has been identified as crucial in the cognitive development of young children, and has been observed on different time-scales. In particular, the real-time verbal mediation of behaviour has been studied in the context of private speech use and self-regulation, pioneered by Vygotsky and continued by others who followed this line of research. However previous studies have mainly attempted to find correlations between speech and self-regulatory behaviour, but have been unable to capture the dynamic and real-time temporal interactions between these phenomena. Hence, without being able to carry out a contextual analysis of the actual instances of temporal co-occurrence between speech and behaviour, correlational analysis is limited in determining the various kinds of verbal mediation that children spontaneously employ as strategies during problem-solving and while exercising self-regulation. The current study proposes ‘temporal pattern analysis’ as an effective method of extracting significantly recurring patterns of task-relevant speech and goal-directed behaviour, as they repeatedly occur in a stream of naturalistic behaviour which may also contain other temporally random events. These recurring temporal patterns are then contextually analysed, considering the pragmatic content of the speech involved and the goal-directedness of the behaviour towards a specific goal of the episode. Goal-directed episodes of behaviour in eight typically-developing preschool children were video-recorded during their self-initiated activities in the classroom as well as during a problem-solving task held in a laboratory setting. The proposed method of temporal and contextual analysis was used to examine the role of both private as well as social speech in the verbal mediation of self-regulatory behaviour during goal-attainment. A Contextual Model of Verbal Mediation was proposed in the study to account for the diverse functions that both social and private speech perform during verbal mediation of one’s own and others’ behaviour in a goal-directed setting, depending on the specific social and task-related context. A dynamic framework of assessment of performance was developed in the study, to account for both successful attempts at self-regulation as well as failures of self-regulation. The study also attempted to determine any consistent group differences in the styles of verbal mediation employed by the children, across the classroom and the laboratory settings.

A análise de uma população em longo prazo permite a identificação da ausência ou presença de variações nos padrões de ciclo de vida, de distribuição espaço-temporal e dinâmica populacional. O ciclo de vida do camarão sete-barbas Xiphopenaeus kroyeri foi investigado na Enseada de Ubatuba, litoral norte do Estado de São Paulo (23º25\' - 23º27\'S / 45º00\' - 45º03\' W) ao longo de um intervalo de treze anos. Amostras de material biológico, de água de fundo e de sedimento foram coletadas em quatro pontos de amostragem em três períodos de 12 meses cada: janeiro a dezembro de 1998, julho de 2006 a junho de 2007 e setembro de 2010 a agosto de 2011. Dados obtidos em 1999 foram incluídos para as análises de crescimento individual, de longevidade e de idade de maturação. Altas abundâncias de fêmeas maduras e de jovens foram respectivamente associadas a valores de temperatura da água de fundo acima e abaixo da média da região. Indivíduos adultos predominaram em pontos com variação temporal da composição granulométrica do sedimento enquanto que os jovens se estabeleceram naqueles em que o sedimento permaneceu fino entre os períodos. Em 1998, a abundância de jovens, o peso individual de machos e fêmeas de todas as categorias demográficas, a idade de maturação morfológica e fisiológica e a longevidade foram maiores do que nos outros períodos. Os parâmetros da função de crescimento de machos e fêmeas variaram entre os períodos, sem apresentarem uma tendência temporal clara. Os padrões anuais de reprodução e recrutamento foram bastante semelhantes entre os períodos. As alterações nos fatores ambientais provocadas por variações na dinâmica de massas de água, pela ocorrência de El Niño e alterações na intensidade de pesca foram consideradas como possíveis agentes relacionadas às variações nos padrões do ciclo de vida da espécie na região / Long-term studies on a population provide detection of the presence or absence of interannual variation in patterns of its life cycle, spatio-temporal distribution, and dynamics. This study investigate the population of the seabob shrimp Xiphopenaeus kroyeri within a period of 13 years in Ubatuba Bay, northern coast of São Paulo state, Brazil (23º25\' - 23º27\'S / 45º00\' - 45º03\' W). Shrimp, bottom water and sediment samples were collected from four sampling sites during three 12-month periods: January-December 1998, July 2006-June 2007, and September 2010-August 2011. Monthly data collected in 1999 were included in growth, longevity and maturation age analyses. High abundance of mature females and juveniles were associated to the occurrence of temperature values below and above the region average, respectively. Adults predominated in sites that showed temporal variation of sediment texture while juveniles occurred in sites where sediment remained fine between the study periods. In the 1998 period values of juveniles were more abundant, individual weight of all demographic categories was higher, both morphological and physiological maturity was attained later and lifespan was longer than on the following periods. Growth function parameters of males and females varied between periods with no clear temporal trend. Monthly patterns of reproduction and recruitment were similar between the study periods. Changes in the environmental conditions caused by variations in the dynamics of the local water masses, occurrence of El Niño and fishery intensity were considered as possible factors related to the interannual variations in the life cycle pattern of X. kroyeri in the study region

De nombreuses données sont enregistrées dans le cadre d'applications variées et leur analyse est un challenge abordé par de nombreuses études. Parmi ces différentes applications, cette thèse est motivée par l'analyse de parcours patients pour mener des études de pharmaco-épidémiologie. La pharmaco-épidémiologie est l'étude des usages et effets de produits de santé au sein de populations définies. Le but est donc d'automatiser ce type d'étude en analysant des données. Parmi les méthodes d'analyses de données, les approches d'extraction de motifs extraient des descriptions de comportements, appelées motifs, caractérisant ces données. L'intérêt principal de telles approches est de donner un aperçu des comportements décrivant les données. Dans cette thèse, nous nous intéressons à l'extraction de motifs temporels discriminants au sein de séquences temporelles, c'est-à-dire une liste d'évènements datés. Les motifs temporels sont des motifs représentant des comportements par leur dimension temporelle. Les motifs discriminants sont des motifs représentant les comportements apparaissant uniquement pour une sous-population bien définie. Alors que les motifs temporels sont essentiels pour décrire des données temporelles et que les motifs discriminants le sont pour décrire des différences de comportement, les motifs temporels discriminants ne sont que peu étudiés. Dans cette thèse, le modèle de chronique discriminante est proposé pour combler le manque d'approches d'extraction de motifs temporels discriminants. Une chronique est un motif temporelle représentable sous forme de graphe dont les nœuds sont des évènements et les arêtes sont des contraintes temporelles numériques. Le modèle de chronique a été choisi pour son expressivité concernant la dimension temporelle. Les chroniques discriminantes sont, de ce fait, les seuls motifs temporels discriminants représentant numériquement l'information temporelle. Les contributions de cette thèse sont : (i) un algorithme d'extraction de chroniques discriminantes (DCM), (ii) l'étude de l'interprétabilité du modèle de chronique au travers de sa généralisation et (iii) l'application de DCM sur des données de pharmaco-épidémiologie. L'algorithme DCM est dédié à l'extraction de chroniques discriminantes et basé sur l'algorithme d'extraction de règles numériques Ripperk . Utiliser Ripperk permet de tirer avantage de son efficacité et de son heuristique incomplète évitant la génération de motifs redondants. La généralisation de cet algorithme permet de remplacer Ripperk par n'importe quel algorithme de machine learning. Les motifs extraits ne sont donc plus forcément des chroniques mais une forme généralisée de celles-ci. Un algorithme de machine learning plus expressif extrait des chroniques généralisées plus expressives mais impacte négativement leur interprétabilité. Le compromis entre ce gain en expressivité, évalué au travers de la précision de classification, et cette perte d'interprétabilité, est comparé pour plusieurs types de chroniques généralisées. L'intérêt des chroniques discriminantes à représenter des comportements et l'efficacité de DCM est validée sur des données réelles et synthétiques dans le contexte de classification à base de motifs. Des chroniques ont finalement été extraites à partir des données de pharmaco-épidémiologie et présentées aux cliniciens. Ces derniers ont validés l'intérêt de celles-ci pour décrire des comportements d'épidémiologie discriminants. / Data are recorded for a wide range of application and their analysis is a great challenge addressed by many studies. Among these applications, this thesis was motivated by analyzing care pathway data to conduct pharmaco-epidemiological studies. Pharmaco-epidemiology is the study of the uses and effects of healthcare products in well defined populations. The goal is then to automate this study by analyzing data. Within the data analysis approaches, pattern mining approaches extract behavior descriptions, called patterns, characterizing the data. Patterns are often easily interpretable and give insights about hidden behaviors described by the data. In this thesis, we are interested in mining discriminant temporal patterns from temporal sequences, i.e. a list of timestamped events. Temporal patterns represent expressively behaviors through their temporal dimension. Discriminant patterns are suitable adapted for representing behaviors occurring specifically in small subsets of a whole population. Surprisingly, if temporal patterns are essential to describe timestamped data and discriminant patterns are crucial to identify alternative behaviors that differ from mainstream, discriminant temporal patterns received little attention up to now. In this thesis, the model of discriminant chronicles is proposed to address the lack of interest in discriminant temporal pattern mining approaches. A chronicle is a temporal pattern representable as a graph whose nodes are events and vertices are numerical temporal constraints. The chronicle model was choosen because of its high expressiveness when dealing with temporal sequences and also by its unique ability to describe numerically the temporal dimension among other discriminant pattern models. The contribution of this thesis, centered on the discriminant chronicle model, is threefold: (i) a discriminant chronicle model mining algorithm (DCM), (ii) the study of the discriminant chronicle model interpretability through its generalization and (iii) the DCM application on a pharmaco-epidemiology case study. The DCM algorithm is an efficient algorithm dedicated to extract discriminant chronicles and based on the Ripperk numerical rule learning algorithm. Using Ripperk allows to take advantage to its efficiency and its incomplete heuristic dedicated to avoid redundant patterns. The DCM generalization allows to swap Ripperk with alternative machine learning algorithms. The extracted patterns are not chronicles but a generalized form of chronicles. More expressive machine learning algorithms extract more expressive generalized chronicles but impact negatively their interpretability. The trade-off between this expressiveness gain, evaluated by classification accuracy, and this interpretability loss, is compared for several types of generalized chronicles. The interest of the discriminant chronicle model and the DCM efficiency is validated on synthetic and real datasets in pattern-based classification context. Finally, chronicles are extracted from a pharmaco-epidemiology dataset and presented to clinicians who validated them to be interesting to describe epidemiological behaviors.

Wildfire processes in Canada are expected to change as a result of climate change. Predictive modeling of wildfire occurrence and susceptibility requires knowledge of ignition expectations and landscape conditions leading to burn. This research examines and quantifies the spatial and temporal patterns of wildfire across Canada with focus on wildfire occurrence and national scale drivers of susceptibility. Baseline ignition expectations and trends are identified and used to create unique fire ignition regimes, assess anthropogenic influence on ignitions, and determine regions with anomalously high ignitions. The aspatial and spatial characteristics of land cover were characterized for pre- and post-fire landscapes. These included land cover composition, configuration, and abiotic covariates. Temporal trends in forest pattern following ignition are examined and national scale drivers of wildfire susceptibility determined. Fire ignition regimes and anomalous ignition regions provide spatially explicit outputs for exploring ignition expectation in Canada. Wildfire was identified to burn mainly in coniferous forests with little fragmentation. Fragmentation increased after wildfire and regeneration of pre-fire forest pattern took 20 years. Additionally, anthropogenic proximity positively influenced ignition expectation, ignition trend, and wildfire susceptibility. This research provides broad scale methods to assess wildfire occurrence and susceptibility across Canada and will facilitate understanding of changing wildfire processes in the future. Additionally, this research highlights the importance of anthropogenic activity on natural fire processes.