Un des premiers modèles d'indexation de documents qui utilise des termes comme descripteurs était une structure de treillis, cela une vingtaine d'années avant l'arrivée de l'analyse formelle de concepts (FCA pour "Formal Concept Analysis"), qui s'affirme maintenant comme un formalisme théorique important et solide pour l'analyse de données et la découverte de connaissances. Actuellement, la communauté en recherche d'information (RI) s'intéresse particulièrement à des techniques avancées pour la recherche des documents qui relèvent des probabilités et des statistiques. En parallèle, l'intérêt de la communauté FCA au développement de techniques qui font avancer l'état de l'art en RI tout en offrant des fonctionnalités sémantiques lui est toujours bien vivant. Dans cette thèse, nous présentons un ensemble de contributions sur ce que nous avons appelé les systèmes FCA de recherche d'information ("FCA-based IR systems''). Nous avons divisé nos contributions en deux parties, à savoir l'extraction et l'indexation. Pour la récupération, nous proposons une nouvelle technique qui exploite les relations sémantiques entre les descripteurs dans un corpus de documents. Pour l'indexation, nous proposons un nouveau modèle qui permet de mettre en oeuvre un modèle vectoriel d'indexation des documents s'appuyant sur un treillis de concepts (ou treillis de Galois). En outre, nous proposons un modèle perfectionné pour l'indexation hétérogène dans lequel nous combinons le modèle vectoriel et le modèle de recherche booléen. Finalement, nous présentons une technique de fouille de données inspiré de l'indexation des documents, à savoir un modèle d'énumération exhaustive des biclusters en utilisant la FCA. Le biclustering est une nouvelle technique d'analyse de données dans laquelle les objets sont liés via la similitude dans certains attributs de l'espace de description, et non pas par tous les attributs comme dans le "clustering'' standard. En traduisant ce problème en termes d'analyse formelle de concepts, nous pouvons exploiter l'algorithmique associée à la FCA pour développer une technique d'extraction de biclusters de valeurs similaires. Nous montrons le très bon comportement de notre technique, qui fonctionne mieux que les techniques actuelles de biclustering avec énumération exhaustive / One of the first models ever to be considered as an index for documents using terms as descriptors, was a lattice structure, a couple of decades before the arrival of Formal Concept Analysis (FCA) as a solid theory for data mining and knowledge discovery.While the Information Retrieval (IR) community has shifted to more advanced techniques for document retrieval, like probabilistic and statistic paradigms, the interest of the FCA community on developing techniques that would improve the state-of-the-art in IR while providing relevance feedback and semantic based features, never decayed. In this thesis we present a set of contributions on what we call FCA-based IR systems. We have divided our contributions in two sets, namely retrieval and indexing. For retrieval, we propose a novel technique that exploits semantic relations among descriptors in a document corpus and a new concept lattice navigation strategy (called cousin concepts), enabling us to support classification-based reasoning to provide better results compared with state-of-the-art retrieval techniques. The basic notion in our strategy is supporting query modification using "term replacements'' using the lattice structure and semantic similarity. For indexing, we propose a new model that allows supporting the vector space model of retrieval using concept lattices. One of the main limitations of current FCA-based IR systems is related to the binary nature of the input data required for FCA to generate a concept lattice. We propose the use of pattern structures, an extension of FCA to deal with complex object descriptions, in order to support more advanced retrieval paradigms like the vector space model. In addition, we propose an advanced model for heterogeneous indexing through which we can combine the vector space model and the Boolean retrieval model. The main advantage of this approach is the ability of supporting indexing of convex regions in an arbitrary vectorial space built from a document collection. Finally, we move forward to a mining model associated with document indexing, namely exhaustive bicluster enumeration using FCA. Biclustering is an emerging data analysis technique in which objects are related by similarity under certain attributes of the description space, instead of the whole description space like in standard clustering. By translating this problem to the framework of FCA, we are able to exploit the robust machinery associated with the computation of concept lattices to provide an algorithm for mining biclusters based on similar values. We show how our technique performs better than current exhaustive enumeration biclustering techniques.

It is widely acknowledged that there is a shortage of software developers with the right skills and knowledge. In respect of their university education, students want to take courses and carry out projects that clearly relate to their lives and their goals. The software development industry on the other hand, expects students to be educated in courses and projects, which are relevant for their professional career and equip them to be well-prepared for the workplace. In the middle, between the students and the industry, is the university that is expected to meet the needs of the students on the one side and the software industry on the other side. The unique contribution of this research is the development of a framework for relevant software development education by addressing the question: How can universities ensure that software development education provides knowledge and skill sets that are relevant to both the software development industry and software development students? The literature study investigates the software development class, focusing on the students and the educators. Furthermore, a review of the software development workplace is done with attention to the software developers and their employers. The problems and challenges facing three role players in software development education, namely the students, the university and the industry are investigated. Lastly, the role of the university in relevant software development education is considered with a specific focus on curricula. In the empirical study a questionnaire was developed to investigate the relevance of software development education from the perspective of the students. The questionnaire enquired about students’ interests in each of a list of software development topics and further questions relating to students’ views and needs for a relevant education are presented. The questionnaire was completed by 297 software development students and it was found that although a gap exists between students' needs and software development education, students’ education does have a predominantly social relevance and also a moderate personal and professional relevance. A second questionnaire was developed to investigate the relevance of software development education as it pertains to the software industry. The questionnaire enquired about the perceptions of professional software developers regarding what topics they learned from their formal education and the importance of these topics to their actual work. The questionnaire was completed by 214 software development professionals and again it was found that there is a gap between the industry’s needs and software development education. Questions related to the industry’s needs, as well as an open-ended question at the end of the questionnaire offered rich insights into the industry’s view of its new graduates and the problems and challenges surrounding software development education. The quantitative data, as well as the qualitative data offered solutions to these problems and challenges. The students’ views are compared with the professional software developers’ views to investigate the compatibility between the relevance of software development education for students and the relevance for the software industry. The analysis reveals matching and differing views. A framework for relevant software development education was developed to address the gap between software development education and the students’ needs, as well as the gap between software development education and the industry’s needs. The problems and challenges that might cause SD education to be less relevant are presented and recommendations to industry and university for relevant software development education are made. / PhD (Natural Sciences Education), North-West University, Potchefstroom Campus, 2015

The purpose of the study was to investigate the rigour and relevance of IS research; as researchers and practitioners are divided and living in a different world of aspiration m conducting research. This division is as a result of many reasons. The gap between researchers and practitioners has promulgated debate and argument among the two that has lasted for years. Many believed that IS research is effective and others opposed it. Others within or outside the discipline consider whether IS research output affects and impacts decision making in the industry. Meanwhile, the debate on rigour and relevance has lasted for decades but, in reality, the differences gap still persists, in spite of efforts by researchers. Their efforts and hard-work seem not to be very effective. This study seeks to determine whether practitioners meet their needs and expectations and whether they address them through the rigour and relevance of IS/academic research. It is also to determine whether this debate which has lingered over the years is worth it. The growing problems and needs in the practitioners' world call for an investigation into this rigour and relevance. There is an on-going criticism that IS research lacks rigour, relevance. effective communication and acceptance in the field as noted in the literature. The identified problem under investigation now is lack of rigour, relevance and other issues such as consistency, transparency, communication and inaccessibi lity in IS research. The population for the study comprised academic lecturers attending the South African Institute for Computer Scientists and Information Technologists (SAICSIT 2012) conference and North-West University IS and Computer Science (Mafikeng Campus) academics. The population was 90 lecturers/academics and the sample size of 73 answered the questionnaires. / Thesis (M.Com.(Information Systems) North-West University, Mafikeng Campus, 2013

It is widely acknowledged that there is a shortage of software developers with the right skills and knowledge. In respect of their university education, students want to take courses and carry out projects that clearly relate to their lives and their goals. The software development industry on the other hand, expects students to be educated in courses and projects, which are relevant for their professional career and equip them to be well-prepared for the workplace. In the middle, between the students and the industry, is the university that is expected to meet the needs of the students on the one side and the software industry on the other side. The unique contribution of this research is the development of a framework for relevant software development education by addressing the question: How can universities ensure that software development education provides knowledge and skill sets that are relevant to both the software development industry and software development students? The literature study investigates the software development class, focusing on the students and the educators. Furthermore, a review of the software development workplace is done with attention to the software developers and their employers. The problems and challenges facing three role players in software development education, namely the students, the university and the industry are investigated. Lastly, the role of the university in relevant software development education is considered with a specific focus on curricula. In the empirical study a questionnaire was developed to investigate the relevance of software development education from the perspective of the students. The questionnaire enquired about students’ interests in each of a list of software development topics and further questions relating to students’ views and needs for a relevant education are presented. The questionnaire was completed by 297 software development students and it was found that although a gap exists between students' needs and software development education, students’ education does have a predominantly social relevance and also a moderate personal and professional relevance. A second questionnaire was developed to investigate the relevance of software development education as it pertains to the software industry. The questionnaire enquired about the perceptions of professional software developers regarding what topics they learned from their formal education and the importance of these topics to their actual work. The questionnaire was completed by 214 software development professionals and again it was found that there is a gap between the industry’s needs and software development education. Questions related to the industry’s needs, as well as an open-ended question at the end of the questionnaire offered rich insights into the industry’s view of its new graduates and the problems and challenges surrounding software development education. The quantitative data, as well as the qualitative data offered solutions to these problems and challenges. The students’ views are compared with the professional software developers’ views to investigate the compatibility between the relevance of software development education for students and the relevance for the software industry. The analysis reveals matching and differing views. A framework for relevant software development education was developed to address the gap between software development education and the students’ needs, as well as the gap between software development education and the industry’s needs. The problems and challenges that might cause SD education to be less relevant are presented and recommendations to industry and university for relevant software development education are made. / PhD (Natural Sciences Education), North-West University, Potchefstroom Campus, 2015

Algorithms are part of most online activities but act largely in the background and remain hidden to the general public. They are programmed pieces of software that are designed to consume massive amounts of data and progress it into easy consumable pieces of information. Furthermore, that software is able to draw connections between pieces of information and filter it based on relevance or other criteria. What these criteria are and what they are based on often remains a well-kept secret. Companies such as Facebook, Google, Twitter and Netflix all use algorithms to make sense of the ever-increasing amount of Data and suggest posts, movies or search results. With more and more people getting their news stories trough social media platforms and search engines, algorithms play an important role in the way we receive news. That lead to the questions of what power algorithms have over the news we see and what power they have over news organisations and journalism. To answer these broad questions, it was decided to focus on one large news organisations and examine what role algorithms play. The news organisation chosen for this research was The Guardian. In order to investigate these how and if algorithms are used, interviews with eight experts working at The Guardian were conducted. The informants were developers, engineers, product managers, editors and journalists in order to get a broader spectrum of possible frames in place. So as to analyse the interviews, tables were created to understand the way algorithms in relation to the institution of The Guardian and the power of editors were framed by the interviewees. One of the results that could be observed through the interviews and analysis was that algorithms will play an increasingly large role in The Guardian and possibly share their influence with editors. It can also be found that technology and news organisations will become more and more intertwined and data from users will be collected and analysed. The last part of the thesis discusses the impact of the results in a broader context and what further research can be done.

Thesis (D.Litt.)--Stellenbosch University, 2000. / ENGLISH ABSTRACT: Relevance theory has seriously challenged the theoretical soundness of formal and functional equivalence as Bible translation methods. In Translation and relevance: Cognition and context, Gutt (1991) argued that relevance theory provides translators with the best available framework for understanding and practicing translation. In his effort to provide a comprehensive account of translation, he proposed two new approaches to translation: direct translation and indirect translation. He did not, however, develop direct and indirect translation into well-defined approaches to translation. This study explores the viability of direct and indirect translation as approaches to Bible translation. First, by applying insights drawn from relevance theory, it spells out the theoretical and practical implications of these approaches in an attempt to develop them into well-defined translation methods. The explication of the two new approaches shows how and why relevance theoretic approaches to translation differ from formal and functional equivalence. In addition to describing the general approach of direct and indirect translation, it also demonstrates how each approach handles specific translation issues such as figurative language, implicit information, ambiguity, and gender-biased language. Then, by using them to translate the epistle to Titus, the study tests the practical effectiveness of each new approach. This lengthy application yields many examples of how relevance theory provides translators with valuable guidance for making difficult translation decisions. It emphasises the need for translators to take measures to bridge the contextual gap between the source context and the receptor context, illustrating how this can be done by providing footnotes in a direct translation or by explicating implicit information in an indirect translation. The study closes with a brief assessment of the two new approaches and some suggestions for further research. The conclusions show both the value and the limitations of the results of this study. / AFRIKAANSE OPSOMMING: Relevansieteorie bevraagteken ernstig die teoretiese basis van formele en funksionele ekwivalensie as metodes van Bybelvertaling. Gutt (1991) het in Translation and relevance: Cognition and context geargumenteer dat relevansieteorie vertalers voorsien van die beste beskikbare raamwerk vir die verstaan en beoefening van vertaling. In sy poging om 'n omvattende beskrywing van vertaling daar te stel, het hy twee nuwe benaderings voorgestel: direkte vertaling en indirekte vertaling. Hy het egter nie direkte en indirekte vertaling ontwikkel tot goed gedefinieerde benaderings tot vertaling nie. Hierdie studie ondersoek die lewensvatbaarheid van direkte en indirekte vertaling as benaderings tot Bybelvertaling. Eerstens word aan die hand van insigte ontleen aan relevansieteorie die teoretiese en praktiese implikasies van hierdie benaderings verken met die doel om dit te ontwikkel tot goed gedefineerde metodes van vertaling. Die uiteensetting van hierdie twee nuwe benaderings toon hoe en waarom relevansieteoretiese benaderings tot vertaling verskil van formele en funksionele ekwivalensie. Benewens 'n beskrywing van die algemene benadering van direkte en indirekte vertaling, demonstreer die uiteensetting hoe elke benadering spesifieke aangeleenthede soos beeldspraak, implisiete inligting, dubbelsinnigheid en gender-bevooroordeelde taal, in vertaalpraktyk hanteer. Vervolgens stel die ondersoek die praktiese effektiwiteit van elke nuwe benadering op die proef deur dit te gebruik om die brief aan Titus te vertaal. Hierdie omvangryke toepassing lewer verskeie voorbeelde waar relevansieteorie vertalers van waardevolle riglyne voorsien om moeilike besluite oor vertaling te maak. Dit benadruk die noodsaaklikheid vir vertalers om spesiale maatreels te tref om die kontekstuele gaping te oorbrug tussen die bronkonteks en die reseptorkonteks, en word geillustreer deur in 'n direkte vertaling voetnotas te gebruik en deur in 'n indirekte vertaling implisiete inligting eksplisiet te maak. Die ondersoek word afgesluit met 'n kort evaluering van die twee benaderings en met enkele voorstelle vir verdere navorsing. Die gevolgtrekking toon beide die waarde en die beperkings van die resultate van hierdie ondersoek.

Financial markets have many different key actors, but one of the most important ones are the financial analysts. They are considered as experts in gathering and disseminating the information that firms produce, to those that seek it, such as stock recommendations and reports on firms. Related to this is a growing interest in society toward disclosures in regards of CSR as well as ESG. There has been considerable discussion in academia of whether or not CSR can be considered to be value relevant. This is a question which relate to both institutional and legitimacy perspectives in terms of theory, but also discussions in regards to agency and stakeholder theory as well:   Has value relevance of CSR disclosures increased in stock recommendations for the Nordic markets?   Thereby, the main purpose of this thesis is to find out whether or not there has been a shifting view of CSR over time, which would be evidenced in an increasing legitimization of CSR in terms of an increasing value-relevance to financial analysts. This would also be related to a shifting institutional logic, whereby it would be possible to relate to a shift in the view of the firm and its role in society. This is both looked at purely from the starting point of the dataset to the end point, but also for two different periods of time, so as to test if there is a different view of the issue after the financial crisis. In addition to this main purpose, this thesis furthermore sets out to answer whether CSR is value-relevant or not in different subsegments, such as nations, industries and the different types of recommendations that exist.   To answer the research question, an objectivist and positivist stance is taken, which subsequently leads the authors to utilize quantitative methods and statistical analysis to the data. Here, different panel models are fitted to the data to account effects that exist within it. To explain the findings, a theoretical framework is built upon three different levels: societal, firm and individual level. Here, on the societal level theories such as institutional theory as well as legitimacy theory are dealt with. On the firm level, agency theory and stakeholder theory as well as theoretical views of CSR forms the basis, and the individual level deals with theory related to the financial analyst.   In looking at the results and the analysis, one cannot draw the conclusion that there has been a shifting view of the value-relevance of CSR. Financial analysts appear to not find it value-relevant in issuing their stock recommendations, except for two cases: namely in terms of the industrial sector Basic Materials and the Buy recommendations. In terms of Basic Materials, it appears to be value-relevant in a positive manner. In regards to the Buy recommendation, it appears to have a negative effect on the value-relevance. All in all, this thesis cannot find evidence for a value-relevance of CSR to financial analysts in the Nordic markets. Essentially, the view of it appears to be pessimistic.

After three decades of research, instructional communication scholars find themselves facing several key challenges. These range from an overemphasis in past studies on variable-analytic, atheoretical research to a lack of connection to learning outcomes. Many in the field contend that the time has come for instructional communication researchers to define instructional communication theories, test hypotheses, tie research efforts to learning outcomes, and clarify key terms. The present study addressed these shortcomings by proposing the Content Relevance Centric Theory and testing related hypotheses. The research occurred in a professional training environment and involved the use of a modified content relevance instrument that assessed both teacher communication characteristics and message content relevance. The study gathered data from 247 trainees. Results indicate the importance of the construct as a predictor of trainee behavioral intentions both directly and when mediated by both trainee state motivation and trainer credibility. Study outcomes also question the role of trainee engagement in learning and the connection between behavioral intentions and learning application.

An image retrieval system needs to be able to communicate with people using a common language, if it is to serve its user's information need. I propose techniques for interactive image search with the help of visual attributes, which are high-level semantic visual properties of objects (like "shiny" or "natural"), and are understandable by both people and machines. My thesis explores attributes as a novel form of user input for search. I show how to use attributes to provide relevance feedback for image search; how to optimally choose what to seek feedback on; how to ensure that the attribute models learned by a system align with the user's perception of these attributes; how to automatically discover the shades of meaning that users employ when applying an attribute term; and how attributes can help learn object category models. I use attributes to provide a channel on which the user of an image retrieval system can communicate her information need precisely and with as little effort as possible. One-shot retrieval is generally insufficient, so interactive retrieval systems seek feedback from the user on the currently retrieved results, and adapt their relevance ranking function accordingly. In traditional interactive search, users mark some images as "relevant" and others as "irrelevant", but this form of feedback is limited. I propose a novel mode of feedback where a user directly describes how high-level properties of retrieved images should be adjusted in order to more closely match her envisioned target images, using relative attribute feedback statements. For example, when conducting a query on a shopping website, the user might state: "I want shoes like these, but more formal." I demonstrate that relative attribute feedback is more powerful than traditional binary feedback. The images believed to be most relevant need not be most informative for reducing the system's uncertainty, so it might be beneficial to seek feedback on something other than the top-ranked images. I propose to guide the user through a coarse-to-fine search using a relative attribute image representation. At each iteration of feedback, the user provides a visual comparison between the attribute in her envisioned target and a "pivot" exemplar, where a pivot separates all database images into two balanced sets. The system actively determines along which of multiple such attributes the user's comparison should next be requested, based on the expected information gain that would result. The proposed attribute search trees allow us to limit the scan for candidate images on which to seek feedback to just one image per attribute, so it is efficient both for the system and the user. No matter what potentially powerful form of feedback the system offers the user, search efficiency will suffer if there is noise on the communication channel between the user and the system. Therefore, I also study ways to capture the user's true perception of the attribute vocabulary used in the search. In existing work, the underlying assumption is that an image has a single "true" label for each attribute that objective viewers could agree upon. However, multiple objective viewers frequently have slightly different internal models of a visual property. I pose user-specific attribute learning as an adaptation problem in which the system leverages any commonalities in perception to learn a generic prediction function. Then, it uses a small number of user-labeled examples to adapt that model into a user-specific prediction function. To further lighten the labeling load, I introduce two ways to extrapolate beyond the labels explicitly provided by a given user. While users differ in how they use the attribute vocabulary, there exist some commonalities and groupings of users around their attribute interpretations. Automatically discovering and exploiting these groupings can help the system learn more robust personalized models. I propose an approach to discover the latent factors behind how users label images with the presence or absence of a given attribute, from a sparse label matrix. I then show how to cluster users in this latent space to expose the underlying "shades of meaning" of the attribute, and subsequently learn personalized models for these user groups. Discovering the shades of meaning also serves to disambiguate attribute terms and expand a core attribute vocabulary with finer-grained attributes. Finally, I show how attributes can help learn object categories faster. I develop an active learning framework where the computer vision learning system actively solicits annotations from a pool of both object category labels and the objects' shared attributes, depending on which will most reduce total uncertainty for multi-class object predictions in the joint object-attribute model. Knowledge of an attribute's presence in an image can immediately influence many object models, since attributes are by definition shared across subsets of the object categories. The resulting object category models can be used when the user initiates a search via keywords such as "Show me images of cats" and then (optionally) refines that search with the attribute-based interactions I propose. My thesis exploits properties of visual attributes that allow search to be both effective and efficient, in terms of both user time and computation time. Further, I show how the search experience for each individual user can be improved, by modeling how she uses attributes to communicate with the retrieval system. I focus on the modes in which an image retrieval system communicates with its users by integrating the computer vision perspective and the information retrieval perspective to image search, so the techniques I propose are a promising step in closing the semantic gap. / text

Venture capital funds are active investors in technology-based firms in Taiwan. However, there is very little evidence on the influence of VC funds’ investments in the investee firms. This study examines the relations between venture-backing and two issues, earnings management and value relevance, in the technology-based industry. For the issue of the relationship between venture-backing and earnings management, four hypotheses are derived to test the above connections. Three different proxies of earnings management are employed to conduct this analysis: cross-sectional modified Jones model, performance-matched modified Jones model and unexpected accounts receivable model. Empirical evidence shows that there is a negative association between venture-backing and abnormal accruals. Specifically, age of VC funds, percentage of VC funds’ shareholdings on investee firms, and VC funds invested by the government are negatively related with abnormal accruals in most of analyses. These findings indicate that VC funds in Taiwan provide monitoring functions on financial reporting of their invstee firms. For the issue of value relevance of venture-backing information, five hypotheses are derived to test the above connections. Ohlson (1995) model is used for the examination. Empirical evidence shows that venture-backing information is value relevant in the TSE market, but not in the OTC market. The sufficiency of financial information has an impact on value relevance of venture capital information. Value relevance of venture-backing information in the TSE market increases with VC funds’ investments and VC funds’ government investments, but not with VC funds’ age in most of analyses. These findings indicate that investors treat venture-backing information as value-relevant information only in the TSE market, but not in the OTC market. In addition, several tests are performed to determine the sensitivity of the results to a potential selection bias in the research design. The results of this analysis are mixed. Therefore, this paper cannot rule out selection bias as a potential alternative explanation for the findings.