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Metalearning attracted considerable interest in the machine learning community in the last years. Yet, some disagreement remains on what does or what does not constitute a metalearning problem and in which contexts the term is used in. This survey aims at giving an all-encompassing overview of the research directions pursued under the umbrella of metalearning, reconciling different definitions given in scientific literature, listing the choices involved when designing a metalearning system and identifying some of the future research challenges in this domain.

This paper offers a theory of communication visibility based on a field study of the implementation of a new enterprise social networking site in a large financial services organization. The emerging theory suggests that once invisible communication occurring between others in the organization becomes visible for third parties, those third parties could improve their metaknowledge (i.e., knowledge of who knows what and who knows whom ). Communication visibility, in this case made possible by the enterprise social networking site, leads to enhanced awareness of who knows what and whom through two interrelated mechanisms: message transparency and network translucence. Seeing the contents of other’s messages helps third-party observers make inferences about coworkers' knowledge. Tangentially, seeing the structure of coworkers' communication networks helps third-party observers make inferences about those with whom coworkers regularly communicate. The emerging theory further suggests that enhanced metaknowledge can lead to more innovative products and services and less knowledge duplication if employees learn to work in new ways. By learning vicariously rather than through experience, workers can more effectively recombine existing ideas into new ideas and avoid duplicating work. Moreover, they can begin to proactively aggregate information perceived daily rather than engaging in reactive search after confronting a problem. I discuss the important implications of this emerging theory of communication visibility for work in the knowledge economy.

PurposeEnterprise social media can be the organizational transactive memory in which the knowledge dialogue provides users with the metaknowledge to support knowledge transfer. The purpose of this study is to examine a mediation model to show how perceived critical mass, openness and affiliation climate affect organizational knowledge transfer through the mediation of improving the metaknowledge of who knows what and whom.Design/methodology/approachTo test the mediation model and corresponding hypotheses, this study employs structural equation modeling analysis using 264 valid questionnaires.FindingsThe study found the two mediators fully explained the effects of the three preconditions on knowledge transfer.Originality/valueThese results help us to better understand the benefits of enterprise social media and the functions of transactive memory in organizations.

Why do Internet, financial service, and beer commercials dominate Super Bowl advertising? How do political ceremonies establish authority? Why does repetition characterize anthems and ritual speech? Why were circular forms favored for public festivals during the French Revolution? This book answers these questions using a single concept: common knowledge. Game theory shows that in order to coordinate its actions, a group of people must form \"common knowledge.\" Each person wants to participate only if others also participate. Members must have knowledge of each other, knowledge of that knowledge, knowledge of the knowledge of that knowledge, and so on. Michael Chwe applies this insight, with striking erudition, to analyze a range of rituals across history and cultures. He shows that public ceremonies are powerful not simply because they transmit meaning from a central source to each audience member but because they let audience members know what other members know. For instance, people watching the Super Bowl know that many others are seeing precisely what they see and that those people know in turn that many others are also watching. This creates common knowledge, and advertisers selling products that depend on consensus are willing to pay large sums to gain access to it. Remarkably, a great variety of rituals and ceremonies, such as formal inaugurations, work in much the same way. By using a rational-choice argument to explain diverse cultural practices, Chwe argues for a close reciprocal relationship between the perspectives of rationality and culture. He illustrates how game theory can be applied to an unexpectedly broad spectrum of problems, while showing in an admirably clear way what game theory might hold for scholars in the social sciences and humanities who are not yet acquainted with it. In a new afterword, Chwe delves into new applications of common knowledge, both in the real world and in experiments, and considers how generating common knowledge has become easier in the digital age.

The commonly-used large-scale knowledge bases have been facing challenges in open domain question answering tasks which are caused by the loose knowledge association and weak structural logic of triplet-based knowledge. To find a way out of this dilemma, this work proposes a novel metaknowledge enhanced approach for open domain question answering. We design an automatic approach to extract metaknowledge and build a metaknowledge network from Wiki documents. For the purpose of representing the directional weighted graph with hierarchical and semantic features, we present an original graph encoder GE4MK to model the metaknowledge network. Then, a metaknowledge enhanced graph reasoning model MEGr-Net is proposed for question answering, which aggregates both relational and neighboring interactions comparing with R-GCN and GAT. Experiments have proved the improvement of metaknowledge over main-stream triplet-based knowledge. We have found that the graph reasoning models and pre-trained language models also have influences on the metaknowledge enhanced question answering approaches.

Purpose – This paper aims to introduce knowledge discrimination to consumer research. It also examines the antecedent effects of objective knowledge and confidence in knowledge on consumer knowledge discrimination. Research in psychology has sought to distinguish between calibration and discrimination, two related skills in probabilistic judgments. Though consumer research has sought to examine knowledge calibration, the construct of knowledge discrimination has not attracted any attention. Design/methodology/approach – The paper reports on three studies which use a cross-sectional design using a structured questionnaire. The hypotheses are tested using regression. In addition, the paper also reports the results of an experimental study. Findings – The paper finds that the objective knowledge has a positive effect on discrimination. But confidence in knowledge does not have a consistent effect on discrimination. The paper also finds that feedback improves discrimination. Research limitations/implications – The study adds a new dimension to the examination of metaknowledge and metacognitions in the consumer domain. Practical implications – The study suggests some ways in which companies/government agencies can improve consumer knowledge discrimination. Social implications – Knowledge discrimination is expected to reduce consumer vulnerability and enhance consumer competence. Originality/value – This is the first study to examine knowledge discrimination in the consumer domain. Prior research has observed that there could be a trade-off between calibration and discrimination. Hence, the study of knowledge discrimination can inform the study of knowledge calibration.

Hydroinformatics is the name of a new way of applying knowledge as this knowledge is utilised in the worlds of the waters. This new way of applying knowledge, which is developing generally within our present-day societies, is concerned with ways to access and employ electronically encapsulated information, which itself becomes knowledge just to the extent that it is genuinely accessed and authentically employed. The knowledge of how to apply knowledge in the new way is thus itself a certain kind of ‘metaknowledge’.

Our research investigates the relationship between the metacognitive process and the writing performance of students in the first semesters of university. We formulate the hypothesis that the metacognition and the writing performance have a strong and positive relationship. A questionnaire was constructed to measure the metacognition process of students (n= 45). Also, an instrument to evaluate texts was elaborated to measure writing performance. Despite the importance of metaknowledge was emphasized, the data relativizes the relationship between self-regulation and performance. The results are observed according to the evaluation criteria of texts in the context analyzed. [PUBLICATION ABSTRACT]

This paper considers different subjective measures of conscious and unconscious knowledge in a concept formation paradigm. In particular, free verbal reports are compared with two subjective measures, the zero-correlation and the guessing criteria, based on trial-by-trial confidence ratings (a type of on-line verbal report). Despite the fact that free verbal reports are frequently dismissed as being insensitive measures of conscious knowledge, a considerable bulk of research on implicit learning has traditionally relied on this measure of consciousness, because it is widely regarded as almost self-evident that the content of any conscious state that is intentional and conceptual can be expressed verbally. However, we found that the most recently developed subjective measures based on trial-by-trial confidence ratings provided a more sensitive measure of conscious and unconscious knowledge than free verbal reports. In a complementary way, the qualitative pattern of the free report and the confidence measures were similar, providing further evidence for the validity of the latter.[PUBLICATION ABSTRACT]

This chapter describes a scheme for using metareasoning in intelligent agents for self-adaptation of domain knowledge. In particular, it considers retrospective adaptation of the content of intermediate abstractions in an abstraction network used for compositional classification when the classifier makes an incorrect classification. It shows that if the intermediate abstractions in the abstraction network are organized such that each abstraction corresponds to a prediction about a percept in the world, then metaknowledge comes in the form of verification procedures associated with the abstractions, and metareasoning invokes the appropriate verification procedures in order to first perform structural credit assignment and then adapt the abstractions.