Pattern Discovery from Event Data

Events are ubiquitous in real-life. With the rapid rise of the popularity of social media channels, massive amounts of event data, such as information about festivals, concerts, or meetings, are increasingly created and shared by users on the Internet. Deriving insights or knowledge from such social media data provides a semantically rich basis for many applications, for instance, social media marketing, service recommendation, sales promotion, or enrichment of existing data sources. In spite of substantial research on discovering valuable knowledge from various types of social media data such as microblog data, check-in data, or GPS trajectories, interestingly there has been only little work on mining event data for useful patterns. In this thesis, we focus on the discovery of interesting, useful patterns from datasets of events, where information about these events is shared by and spread across social media platforms. To deal with the existence of heterogeneous event data sources, we propose a comprehensive framework to model events for pattern mining purposes, where each event is described by three components: context, time, and location. This framework allows one to easily define how events are related in terms of conceptual, temporal, and spatial (geographic) relationships. Moreover, we also take into account hierarchies for contexts, time, and locations of events, which naturally exist as useful background knowledge to derive patterns at different levels of abstraction and granularity. Based on this framework, we focus on the following problems: (i) mining interval-based event sequence patterns, (ii) mining periodic event patterns, and (iii) extracting semantic annotations for locations of events. Generally, the first two problems consider correlations of events whereas the last one takes correlations of event components into account. In particular, the first problem is a generalization of mining sequential patterns from traditional data, where patterns representing complex temporal relationships among events can be discovered at different levels of abstraction and granularity. The second problem is to find periodic event patterns, where a notion of relaxed periodicity is formulated for events as well as for groups of events that co-occur. The third~problem is to extract semantic annotations for locations on the basis of exploiting correlations of contexts, time, and locations of events. For the three problems above, we respectively propose novel and efficient approaches. Our experiments clearly indicate that extracted patterns and knowledge can be well utilized in various useful tasks, such as event prediction, semantic search for locations, or topic-based clustering of locations

Harmonic duality : from interval ratios and pitch distance to spectra and sensory dissonance

Dissonance curves are the starting point for an investigation into a psychoacoustically informed harmony. Its main hypothesis is that harmony consists of two independent but intertwined aspects operating simultaneously, namely proportionality and linear pitch distance. The former aspect is related to intervallic characters, the latter to ‘high’, ‘low’, ‘bright’ and ‘dark’, therefore to timbre. This research derives from the development of tools for algorithmic composition which extract pitch materials from sound signals, analyzing them according to their timbral and harmonic properties, putting them into motion through diverse rhythmic and textural procedures. The tools and the reflections derived from their use offer fertile ideas for the generation of instrumental scores, electroacoustic soundscapes and interactive live-electronic systems.LEI Universiteit LeidenResearch in and through artistic practic

Towards the Automatic Analysis of Metric Modulations

PhDThe metrical structure is a fundamental aspect of music, yet its automatic analysis from audio recordings remains one of the great challenges of Music Information Retrieval (MIR) research. This thesis is concerned with addressing the automatic analysis of changes of metrical structure over time, i.e. metric modulations. The evaluation of automatic musical analysis methods is a critical element of the MIR research and is typically performed by comparing the machine-generated estimates with human expert annotations, which are used as a proxy for ground truth. We present here two new datasets of annotations for the evaluation of metrical structure and metric modulation estimation systems. Multiple annotations allowed for the assessment of inter-annotator (dis)agreement, thereby allowing for an evaluation of the reference annotations used to evaluate the automatic systems. The rhythmogram has been identified in previous research as a feature capable of capturing characteristics of rhythmic content of a music recording. We present here a direct evaluation of its ability to characterise the metrical structure and as a result we propose a method to explicitly extract metrical structure descriptors from it. Despite generally good and increasing performance, such rhythm features extraction systems occasionally fail. When unpredictable, the failures are a barrier to usability and development of trust in MIR systems. In a bid to address this issue, we then propose a method to estimate the reliability of rhythm features extraction. Finally, we propose a two-fold method to automatically analyse metric modulations from audio recordings. On the one hand, we propose a method to detect metrical structure changes from the rhythmogram feature in an unsupervised fashion. On the other hand, we propose a metric modulations taxonomy rooted in music theory that relies on metrical structure descriptors that can be automatically estimated. Bringing these elements together lays the ground for the automatic production of a musicological interpretation of metric modulations.EPSRC award 1325200 and Omnifone Ltd

Latitude, longitude, and beyond:mining mobile objects' behavior

Rapid advancements in Micro-Electro-Mechanical Systems (MEMS), and wireless communications, have resulted in a surge in data generation. Mobility data is one of the various forms of data, which are ubiquitously collected by different location sensing devices. Extensive knowledge about the behavior of humans and wildlife is buried in raw mobility data. This knowledge can be used for realizing numerous viable applications ranging from wildlife movement analysis, to various location-based recommendation systems, urban planning, and disaster relief. With respect to what mentioned above, in this thesis, we mainly focus on providing data analytics for understanding the behavior and interaction of mobile entities (humans and animals). To this end, the main research question to be addressed is: How can behaviors and interactions of mobile entities be determined from mobility data acquired by (mobile) wireless sensor nodes in an accurate and efficient manner? To answer the above-mentioned question, both application requirements and technological constraints are considered in this thesis. On the one hand, applications requirements call for accurate data analytics to uncover hidden information about individual behavior and social interaction of mobile entities, and to deal with the uncertainties in mobility data. Technological constraints, on the other hand, require these data analytics to be efficient in terms of their energy consumption and to have low memory footprint, and processing complexity

Big Data in Organizations and the Role of Human Resource Management

Big data are changing the way we work. This book conveys a theoretical understanding of big data and the related interactions on a socio-technological level as well as on the organizational level. Big data challenge the human resource department to take a new role. An organization’s new competitive advantage is its employees augmented by big data

Artech 2008: proceedings of the 4th International Conference on Digital Arts

ARTECH 2008 is the fourth international conference held in Portugal and Galicia on the topic of Digital Arts. It aims to promote contacts between Iberian and International contributors concerned with the conception, production and dissemination of Digital and Electronic Art. ARTECH brings the scientific, technological and artistic community together, promoting the interest in the digital culture and its intersection with art and technology as an important research field, a common space for discussion, an exchange of experiences, a forum for emerging digital artists and a way of understanding and appreciating new forms of cultural expression. Hosted by the Portuguese Catholic University’s School of Arts (UCP-EA) at the City of Porto, ARTCH 2008 falls in alignment with the main commitment of the Research Center for Science and Technology of the Arts (CITAR) to promote knowledge in the field of the Arts trough research and development within UCP-AE and together with the local and international community. The main areas proposed for the conference were related with sound, image, video, music, multimedia and other new media related topics, in the context of emerging practice of artistic creation. Although non exclusive, the main topics of the conference are usually: Art and Science; Audio-Visual and Multimedia Design; Creativity Theory; Electronic Music; Generative and Algorithmic Art; Interactive Systems for Artistic Applications; Media Art history; Mobile Multimedia; Net Art and Digital Culture; New Experiences with New Media and New Applications; Tangible and Gesture Interfaces; Technology in Art Education; Virtual Reality and Augmented Reality. The contribution from the international community was extremely gratifying, resulting in the submission of 79 original works (Long Papers, Short Papers and installation proposals) from 22 Countries. Our Scientific Committee reviewed these submissions thoroughly resulting in a 73% acceptance ratio of a diverse and promising body of work presented in this book of proceedings. This compilation of articles provides an overview of the state of the art as well as a glimpse of new tendencies in the field of Digital Arts, with special emphasis in the topics: Sound and Music Computing; Technology Mediated Dance; Collaborative Art Performance; Digital Narratives; Media Art and Creativity Theory; Interactive Art; Audiovisual and Multimedia Design.info:eu-repo/semantics/publishedVersio