O crescimento acelerado da internet proporcionou uma quantidade grande de informações acessíveis aos usuários. Ainda que tal quantidade possua algumas vantagens, os usuários que possuem pouca ou nenhuma experiência para escolher uma alternativa dentre as várias apresentadas terão dificuldades em encontrar informações (ou itens, considerando o escopo deste trabalho) úteis e que atendam às suas necessidades. Devido a esse contexto, os sistemas de recomendação foram desenvolvidos para auxiliar os usuários a encontrar itens relevantes e personalizados. Tais sistemas são divididos em diversas arquiteturas. Como exemplo estão as arquiteturas baseadas em: conteúdo, filtro colaborativo e conhecimento. Para este trabalho, a primeira arquitetura foi explorada. A arquitetura baseada em conteúdo recomenda itens ao usuário com base na similaridade desses aos itens que o usuário mostrou interesse no passado. Por consequência, essa arquitetura possui a limitação de, geralmente, realizar recomendações com baixa serendipidade, uma vez que os itens recomendados tendem a ser semelhantes àqueles observados pelo o usuário e, portanto, não apresentam novidade ou surpresa. Diante desta limitação, o aspecto de serendipidade tem destaque nas discussões apresentadas neste trabalho. Assim, o objetivo deste trabalho é minimizar o problema da baixa serendipidade das recomendações por meio da utilização da análise de similaridades parciais implementada usando ensemble de agrupamentos. Para alcançar este objetivo, estratégias de recomendação baseadas em conteúdo implementadas usando agrupamento e ensemble de agrupamento foram propostas e avaliadas neste trabalho. A avaliação contou com análises qualitativas sobre as recomendações produzidas e com um estudo com usuários. Nesse estudo, quatro estratégias de recomendação de notícias foram avaliadas, incluindo as duas propostas neste trabalhos, uma estratégia baseada em recomendação aleatória, e uma estratégia baseada em coagrupamento. As avaliações consideraram aspectos de relevância, surpresa e serendipidade de recomendações. Esse último aspecto é descrito como itens que apresentam tanto surpresa quanto relevância ao usuário. Os resultados de ambas análises mostraram a viabilidade da utilização de agrupamento como base de recomendação, uma vez que o ensemble de agrupamentos obteve resultados satisfatórios em todos os aspectos, principalmente em surpresa, enquanto a estratégia baseada em agrupamento simples obteve os melhores resultados em relevância e serendipidade / The accelerated growth of the internet has provided a large amount of information accessible to users. Although this amount of information has some advantages, users who have little or no experience in choosing one of several alternatives will find it difficulty to find useful information (or items, considering the scope of this work) that meets their needs. Due to this context, recommender systems have been developed to help users find relevant and personalized items. Such systems are divided into several architectures as content-based, collaborative filtering and knowledge-based. The first architecture was explored in this work. The content-based architecture recommends items to the user based on their similarity to items that the user has shown interest in the past. Consequently, this architecture has the limitation of generally making recommendations with low serendipity, since the recommended items tend to be similar to those observed by the user and, therefore, do not present novelty or surprise. Given this limitation, the aspect of serendipity is highlighted in the discussions presented in this work. Thus, the objective of this work is to minimize the problem of the low serendipity of the recommendations through the use of the partial similarity analysis implemented using cluster ensemble. To achieve this goal, content-based recommendation strategies implemented using clustering and cluster ensemble were proposed and evaluated. The evaluation involved qualitative analysis of the recommendations and a study with users. In such a study, four news recommendation strategies were evaluated including the two strategies proposed in this work, a strategy based on random recommendation, and a strategy based on co-clustering. The evaluations considered aspects of relevance, surprise and serendipity of recommendations. This last aspect is described as items that present both surprise and relevance to the user. The results of both analyzes showed the feasibility of using clustering as the basis of recommendation, since cluster ensemble had satisfactory results in all aspects, mainly in surprise, whereas the simple clustering-based strategy obtained the best results in relevance and serendipity

O crescimento acelerado da internet proporcionou uma quantidade grande de informações acessíveis aos usuários. Ainda que tal quantidade possua algumas vantagens, os usuários que possuem pouca ou nenhuma experiência para escolher uma alternativa dentre as várias apresentadas terão dificuldades em encontrar informações (ou itens, considerando o escopo deste trabalho) úteis e que atendam às suas necessidades. Devido a esse contexto, os sistemas de recomendação foram desenvolvidos para auxiliar os usuários a encontrar itens relevantes e personalizados. Tais sistemas são divididos em diversas arquiteturas. Como exemplo estão as arquiteturas baseadas em: conteúdo, filtro colaborativo e conhecimento. Para este trabalho, a primeira arquitetura foi explorada. A arquitetura baseada em conteúdo recomenda itens ao usuário com base na similaridade desses aos itens que o usuário mostrou interesse no passado. Por consequência, essa arquitetura possui a limitação de, geralmente, realizar recomendações com baixa serendipidade, uma vez que os itens recomendados tendem a ser semelhantes àqueles observados pelo o usuário e, portanto, não apresentam novidade ou surpresa. Diante desta limitação, o aspecto de serendipidade tem destaque nas discussões apresentadas neste trabalho. Assim, o objetivo deste trabalho é minimizar o problema da baixa serendipidade das recomendações por meio da utilização da análise de similaridades parciais implementada usando ensemble de agrupamentos. Para alcançar este objetivo, estratégias de recomendação baseadas em conteúdo implementadas usando agrupamento e ensemble de agrupamento foram propostas e avaliadas neste trabalho. A avaliação contou com análises qualitativas sobre as recomendações produzidas e com um estudo com usuários. Nesse estudo, quatro estratégias de recomendação de notícias foram avaliadas, incluindo as duas propostas neste trabalhos, uma estratégia baseada em recomendação aleatória, e uma estratégia baseada em coagrupamento. As avaliações consideraram aspectos de relevância, surpresa e serendipidade de recomendações. Esse último aspecto é descrito como itens que apresentam tanto surpresa quanto relevância ao usuário. Os resultados de ambas análises mostraram a viabilidade da utilização de agrupamento como base de recomendação, uma vez que o ensemble de agrupamentos obteve resultados satisfatórios em todos os aspectos, principalmente em surpresa, enquanto a estratégia baseada em agrupamento simples obteve os melhores resultados em relevância e serendipidade / The accelerated growth of the internet has provided a large amount of information accessible to users. Although this amount of information has some advantages, users who have little or no experience in choosing one of several alternatives will find it difficulty to find useful information (or items, considering the scope of this work) that meets their needs. Due to this context, recommender systems have been developed to help users find relevant and personalized items. Such systems are divided into several architectures as content-based, collaborative filtering and knowledge-based. The first architecture was explored in this work. The content-based architecture recommends items to the user based on their similarity to items that the user has shown interest in the past. Consequently, this architecture has the limitation of generally making recommendations with low serendipity, since the recommended items tend to be similar to those observed by the user and, therefore, do not present novelty or surprise. Given this limitation, the aspect of serendipity is highlighted in the discussions presented in this work. Thus, the objective of this work is to minimize the problem of the low serendipity of the recommendations through the use of the partial similarity analysis implemented using cluster ensemble. To achieve this goal, content-based recommendation strategies implemented using clustering and cluster ensemble were proposed and evaluated. The evaluation involved qualitative analysis of the recommendations and a study with users. In such a study, four news recommendation strategies were evaluated including the two strategies proposed in this work, a strategy based on random recommendation, and a strategy based on co-clustering. The evaluations considered aspects of relevance, surprise and serendipity of recommendations. This last aspect is described as items that present both surprise and relevance to the user. The results of both analyzes showed the feasibility of using clustering as the basis of recommendation, since cluster ensemble had satisfactory results in all aspects, mainly in surprise, whereas the simple clustering-based strategy obtained the best results in relevance and serendipity

[pt] Fortuidade pode ser definida como a descoberta de algo que não está sendo buscado. Em outras palavras, fortuidade trata da descoberta de informação que provê valiosas intuições ao desvendar conhecimento inesperado. O tópico vem recebendo bastante atenção na literatura, uma vez que precisão pode ser justificadamente relaxada com o objetivo de aumentar a satisfação do usuário. Uma área que pode se beneficiar com fortuidade é a área de dados interligados, um gigantesco espaço de dados no qual dados são disponibilizados publicamente. Buscar e extrair informação relevante se torna uma tarefa desafiadora à medida que cada vez mais dados se tornam disponíveis nesse ambiente. Esta tese contribui para enfrentar este desafio de duas maneiras. Primeiro, apresenta um processo de orquestração de consulta que introduz três estratégias para injetar padrões de fortuidade no processo de consulta. Os padrões de fortuidade são inspirados em características básicas de eventos fortuitos, como analogia e perturbação, e podem ser usados para estender os resultados com informações adicionais, sugerindo consultas alternativas ou reordenando os resultados. Em segundo lugar, introduz uma base de dados que pode ser utilizada para comparar diferentes abordagens de obtenção de conteúdo fortuito. A estratégia adotada para construção dessa base de dados consiste em dividir o universo de dados em partições com base em um atributo global e conectar entidades de diferentes partições de acordo com o número de caminhos compartilhados. / [en] Serendipity is defined as the discovery of a thing when one is not searching for it. In other words, serendipity means the discovery of information that provides valuable insights by unveiling unanticipated knowledge. The topic is receiving increased attention in the literature, since the precision requirement may be justifiably relaxed in order to improve user satisfaction. A field that can benefit from serendipity is the Web of Data, an immense global data space where data is publicly available. As more and more data become available in this data space, searching and extracting relevant information becomes a challenging task. This thesis contributes to addressing this challenge in two ways. First, it presents a query orchestration process that introduces three strategies to inject serendipity patterns in the query process. The serendipity patterns are inspired by basic characteristics of serendipitous events, such as, analogy and disturbance, and can be used for augmenting the results with additional information, suggesting alternative queries or rebalancing the results. Second, it introduces a benchmark dataset that can be used to compare different approaches for locating serendipitous content. The strategy adopted for constructing the dataset consists of dividing the dataset into partitions based on a global feature and linking entities from different partitions according to the number of paths they share.

Introduction. Studies have been conducted on serendipitous encounters in the physical library environment. In this study, we aimed instead to look at features in the online library catalog that can lead to serendipitous en-counters. The aim was also to see if libraries took active steps to promote serendipity in their online library cata-logs. Method. A heuristic evaluation of four online library catalogs was conducted. The set of heuristics used was based on previous research, with the aim of identifying facets of a serendipitous environment. Semi-structured interviews were also conducted with librarians from three of the researched libraries. The results from the heuristic evaluation and the transcripts of the interviews formed the data for the analysis. Analysis. Thematic analyses were carried out on the data. The data from the heuristic evaluation and the interviews were analyzed and presented separately, leading up to a joint summary. Results. Most of the online library catalogs had features like "Similar items" and book recommendations, which can lead to serendipitous encounters. Librarians often experience a lack of influence over their online library catalogs. Librarians identified problems such as patrons expecting their online library catalog to function more like a web search engine, for example, Google Search. Conclusion. The online library catalogs have features that promote serendipitous encounters but we identified problems in how they are best designed. Using an integrated interface for the online library catalog and the library's website was one way to give the librarians more influence over their interface, which increased their likelihood to provide it with more information and content. We suggest further research with an extensive approach of serendi-pitous encounters not only in the online library catalog but also in other digital library environments such as web-sites, social media, blogs and apps. This is a two years master’s thesis in Library and Information Science.

Coincidence as the animator of the independent Czech art of the 1960s We are currently progressing to viewing coincidence as a phenomenon. While coincidence cannot be explained, it needs to be understood. It may be an important program principle of the universe, where coincidence may give life and matters a different direction, and it is undoubtedly part of all of our creative and resourceful efforts. Therefore, we treasure coincidence and in art, we even intentionally call for it frequently. Naturally, the history of art gives us many examples, where coincidence helped an artist to revive their imagination and strengthened their ability to improvise. Dealing with coincidence and activating coincidence intentionally or unintentionally have always been one of the most tantalising moments of many creative endeavours. It is interesting to observe how the role of coincidence and its impact in art, as well as in a human life intermittently diminishes only to resurface again as if in connection with measuring the powers of the acting individual and the current being. It is exciting to follow the complex movement of coincidence in the wide field of potential meanings and understanding, somewhere between Freedom, Necessity, Fate, Fortune, Higher Power or perhaps Providence, and examine the complexity of...

Qualifiée d’« oeuvre steganographique » par son auteur, L’Histoire veritable ou Le Voyage des princes fortunez (1610) inaugure le roman alchimique en France en réactivant le modèle littéraire de l’Hypnerotomachia Poliphili « alchimisé » par Nazari et Gohory, puis édité par Béroalde de Verville (1556-1626) en 1600. Longtemps méconnu, il est redécouvert par E. Vordemann (1933) qui identifie sa source principale, traduction italienne de contes orientaux, le Peregrinaggio di tre figliuoli del re di Serendippo, de Cristoforo Armeno (1557). Eclairée par les recherches béroaldiennes qui ont suivi l’étude fondatrice de V.-L. Saulnier, notre thèse propose une édition commentée du roman qui met en valeur de nombreuses sources, le contexte de la genèse de l’oeuvre et ses modèles littéraires. La mise en fiction de l’alchimie s’articule avec la conception rationnelle ou grivoise de cet art chez Béroalde, écrivain polygraphe et médecin alchimiste. On assiste ainsi au renouvellement de l’écriture romanesque stimulant par ses jeux une « juste curiosité » du lecteur. L’étude met enfin en regard deux textes plus politiques de Béroalde, son poème L’Idée de la république (1584) et son discours anonyme, De la guerre (1589). / Described as an « oeuvre steganographique » by its author, L’Histoire veritable ou Le Voyage des princes fortunez (1610) opens the way to alchemical novel in France, by reactivating the literary model of Hypnerotomachia Poliphili, « alchemized » by Nazari and Gohory before being edited by Beroalde de Verville (1556-1626), in 1600. Left in the dark for a long time, it was rediscovered by E. Vordemann (1933) who identified its main source, an Italian translation of Eastern tales, Peregrinaggio di tre figliuoli del re di Serendippo, by Cristoforo Armeno (1557). Enlightened by the essays on Beroalde, which followed the pioneering study by V.-L. Saulnier, our thesis provides a critical edition that reveals many sources, its genesis’ context and its literary models. The study shows how the fictional motif of alchemy deals with the scientific or bawdy conception of this art in the work of Beroalde, a polygraph writer and an alchemist doctor, and also how it renews the novelistic way of writing by stimulating a « juste curiosité » with its games. At last, it compares two texts by Beroalde, considered more political, his poem L’Idée de la république (1584), and his anonymous discourse, De la guerre (1589).

When the human mind searches concept space for solutions to a given condition we have a choice between conventional and creative thinking. But what are the probabilities of improving a given situation using creative thinking compared with conventional thinking? To answer this question we are extending the meaning of creativity beyond human creativity. We view creativity as an optimised search strategy applicable to the larger set of all teleonomic systems and term this creativity teleonomic creativity. We argue that an analog process is common to all manifestations of creativity within teleonomic systems and describe this process and its cause. In order to show this process and to make quantitative comparisons, we utilise the metaphor of an adaptive fitness landscape and simple statistical techniques. The term fitness in our case describes the condition of a well-defined property being suitable for a purpose, rather than an overall evaluation of many complex interactions measuring reproductive success. We define creativity as the successful attempt of either individuals or populations to gain higher fitness via exploration of global fitness peaks as opposed to the exploitation of a currently occupied local peak. We then show mathematically how the inclusion of creativity in a search can dramatically increase the chances of finding appropriate solutions. We also recognise that creative behaviour is most successful when the environmentis unstable. We note the existence of a strategic meta-parameter that allows self-adaptation when tuned via a feedback loop from the environment. We show that creativity can be understood as a random process with an optimal setting for the standard deviation that maximises the probability of hitting a target of higher fitness. We support our claims with computer simulations and observe several occurrences of teleonomic creativity in nature. In addition we measure the entropy of a teleonomic system via the phase-space of internal variables and observe a sudden entropy increase during the onset of creative behaviour in a teleonomic system. Our investigations also enable us to rationalise the processes, conditions and phenomena surrounding human creativity such as mistakes, madness, serendipity, humor, analogy making and interpret the function of creativity promoters and inhibitors. Our findings may also allow us to incorporate creativity into artificial computer models. We speculate that creativity is an emerging property of any teleonomic system and as such ubiquitous in nature.

Many organizations are trying to re-create the ‘Google experience’, to find and exploit their own corporate information. However, there is evidence that finding information in the workplace using search engine technology has remained difficult, with socio-technical elements largely neglected in the literature. Explication of the factors and generative mechanisms (ultimate causes) to effective search task outcomes (user satisfaction, search task performance and serendipitous encountering) may provide a first step in making improvements. A transdisciplinary (holistic) lens was applied to Enterprise Search and Discovery capability, combining critical realism and activity theory with complexity theories to one of the world’s largest corporations. Data collection included an in-situ exploratory search experiment with 26 participants, focus groups with 53 participants and interviews with 87 business professionals. Thousands of user feedback comments and search transactions were analysed. Transferability of findings was assessed through interviews with eight industry informants and ten organizations from a range of industries. A wide range of informational needs were identified for search filters, including a need to be intrigued. Search term word co-occurrence algorithms facilitated serendipity to a greater extent than existing methods deployed in the organization surveyed. No association was found between user satisfaction (or self assessed search expertise) with search task performance and overall performance was poor, although most participants had been satisfied with their performance. Eighteen factors were identified that influence search task outcomes ranging from user and task factors, informational and technological artefacts, through to a wide range of organizational norms. Modality Theory (Cybersearch culture, Simplicity and Loss Aversion bias) was developed to explain the study observations. This proposes that at all organizational levels there are tendencies for reductionist (unimodal) mind-sets towards search capability leading to ‘fixes that fail’. The factors and mechanisms were identified in other industry organizations suggesting some theory generalizability. This is the first socio-technical analysis of Enterprise Search and Discovery capability. The findings challenge existing orthodoxy, such as the criticality of search literacy (agency) which has been neglected in the practitioner literature in favour of structure. The resulting multifactorial causal model and strategic framework for improvement present opportunities to update existing academic models in the IR, LIS and IS literature, such as the DeLone and McLean model for information system success. There are encouraging signs that Modality Theory may enable a reconfiguration of organizational mind-sets that could transform search task outcomes and ultimately business performance.

The human being and her behavior is complex. Research has shown serendipity and chance to play a great part in the scientific research praxis, still the complexity of human information retrieval is not fully acknowledged in modern libraries. This master thesis compares two different worldviews; the mechanistic and the organic. This in order to understand why information seeking today is increasingly linear when human information behavior is not. The way people believe the world to work reflects on how libraries and information seeking work. The mechanistic worldview, comparing the world to a machine, is rooted in humanity since the seventeenth century and is still shaping our world and institutions. Today databases and linear searches are pushing physical books off shelves to make room for computers and searching on limiting linear mechanical terms instead of complex human ones. This pattern often occurs without adequate questioning and online information is argued to be even more available to patrons than the physical library.  This thesis uses complexity theory and philosophical method to broaden perspectives and question linear searches in scientific information retrieval. It aims to highlight the importance of complex information retrieval and physical browsing for scientific innovation and creativity. Erdelez's original information encountering method was used to obtain source material for philosophical analysis. Philosophical method and complexity theory is used throughout the text to analyze the linear worldview leading up to a joint argumentative summary at the end of every chapter bringing the text forward.  The thesis contains a field study with semi-structured interviews with librarians at the Picture Collection, New York Public Library. This highlights the value of physical browsing through the strong criticism that arose from patrons when the library wanted to archive the unique and browsable research collection.  The result of the thesis argues that the linear technological development in libraries with less physical collections, librarian encounters, passive information gathering and random information paths without underlying commercial drivers create more like-mindedness instead of innovation. This significantly reducing the possibility of interdisciplinary discoveries. A technical development that at an alarming rate shifts information from being sought by people, to people being sought by information.  This is a two years master’s thesis in Library and Information Science.

Lost&Found Videothek is the concept for an interactive video library thought for users engaged in an exploratory research mode, in which content is organized according to a collaborative, subjective and implicit indexing system for the enhancement of serendipity. This idea was the result of a design-based research with a user-centered approach in the field of information retrieval. With the use of design methods such as heuristic UX evaluation, co-sketching, and other original design experiments, the project aimed at identifying the most valuable qualities of physical and digital libraries in order to integrate them within one retrieval system.